Artificial intelligence

3592: 18338:, vol. 98, no. 3 (May/June 2019), pp. 135–144. "Today's AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater." (p. 140.) 2715:

Google, Amazon) into voracious consumers of electric power. Projected electric consumption is so immense that there is concern that it will be fulfilled no matter the source. A ChatGPT search involves the use of 10 times the electrical energy as a Google search. The large firms are in haste to find power sources – from nuclear energy to geothermal to fusion. The tech firms argue that – in the long view – AI will be eventually kinder to the environment, but they need the energy now. AI makes the power grid more efficient and "intelligent", will assist in the growth of nuclear power, and track overall carbon emissions, according to technology firms.

64: 2471:. AI agents operate within the constraints of their programming, available computational resources, and hardware limitations. This means they are restricted to performing tasks within their defined scope and have finite memory and processing capabilities. In real-world applications, AI agents often face time constraints for decision-making and action execution. Many AI agents incorporate learning algorithms, enabling them to improve their performance over time through experience or training. Using machine learning, AI agents can adapt to new situations and optimise their behaviour for their designated tasks. 2384: 3608:, the annual number of AI-related laws passed in the 127 survey countries jumped from one passed in 2016 to 37 passed in 2022 alone. Between 2016 and 2020, more than 30 countries adopted dedicated strategies for AI. Most EU member states had released national AI strategies, as had Canada, China, India, Japan, Mauritius, the Russian Federation, Saudi Arabia, United Arab Emirates, U.S., and Vietnam. Others were in the process of elaborating their own AI strategy, including Bangladesh, Malaysia and Tunisia. The 4011: 1637: 713: 1074: 2726:, found "US power demand (is) likely to experience growth not seen in a generation…." and forecasts that, by 2030, US data centers will consume 8% of US power, as opposed to 3% in 2022, presaging growth for the electrical power generation industry by a variety of means.Data centers' need for more and more electrical power is such that they might max out the electrical grid. The Big Tech companies counter that AI can be used to maximize the utilization of the grid by all. 23097: 20288: 24113: 23680: 22534: 21524: 3507:, which allows companies to specialize them with their own data and for their own use-case. Open-weight models are useful for research and innovation but can also be misused. Since they can be fine-tuned, any built-in security measure, such as objecting to harmful requests, can be trained away until it becomes ineffective. Some researchers warn that future AI models may develop dangerous capabilities (such as the potential to drastically facilitate 21504: 23692: 22544: 22980: 1455: 22554: 18563: 795:, the agent knows exactly what the effect of any action will be. In most real-world problems, however, the agent may not be certain about the situation they are in (it is "unknown" or "unobservable") and it may not know for certain what will happen after each possible action (it is not "deterministic"). It must choose an action by making a probabilistic guess and then reassess the situation to see if the action worked. 1720: 3410:"scoffs at his peers' dystopian scenarios of supercharged misinformation and even, eventually, human extinction." In the early 2010s, experts argued that the risks are too distant in the future to warrant research or that humans will be valuable from the perspective of a superintelligent machine. However, after 2016, the study of current and future risks and possible solutions became a serious area of research. 1214: 4529: 9613: 20276: 3884:). By 2000, solutions developed by AI researchers were being widely used, although in the 1990s they were rarely described as "artificial intelligence". However, several academic researchers became concerned that AI was no longer pursuing its original goal of creating versatile, fully intelligent machines. Beginning around 2002, they founded the subfield of 4356:": "The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds." Searle counters this assertion with his Chinese room argument, which attempts to show that, even if a machine perfectly simulates human behavior, there is still no reason to suppose it also has a mind. 2627:". Experts disagree about how well and under what circumstances this rationale will hold up in courts of law; relevant factors may include "the purpose and character of the use of the copyrighted work" and "the effect upon the potential market for the copyrighted work". Website owners who do not wish to have their content scraped can indicate it in a " 1559: 4170:). "Scruffies" expect that it necessarily requires solving a large number of unrelated problems. Neats defend their programs with theoretical rigor, scruffies rely mainly on incremental testing to see if they work. This issue was actively discussed in the 1970s and 1980s, but eventually was seen as irrelevant. Modern AI has elements of both. 1791:(a token being usually a word, subword, or punctuation). Throughout this pretraining, GPT models accumulate knowledge about the world and can then generate human-like text by repeatedly predicting the next token. Typically, a subsequent training phase makes the model more truthful, useful, and harmless, usually with a technique called 2711:, forecasting electric power use. This is the first IEA report to make projections for data centers and power consumption for artificial intelligence and cryptocurrency. The report states that power demand for these uses might double by 2026, with additional electric power usage equal to electricity used by the whole Japanese nation. 5297:: "Whereas for decades, computer-science fields such as natural-language processing, computer vision, and robotics used extremely different methods, now they all use a programming method called "deep learning." As a result, their code and approaches have become more similar, and their models are easier to integrate into one another." 2922:

that a black person would re-offend and would underestimate the chance that a white person would not re-offend. In 2017, several researchers showed that it was mathematically impossible for COMPAS to accommodate all possible measures of fairness when the base rates of re-offense were different for whites and blacks in the data.

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solar activity, and distinguishing between signals and instrumental effects in gravitational wave astronomy. It could also be used for activities in space such as space exploration, including analysis of data from space missions, real-time science decisions of spacecraft, space debris avoidance, and more autonomous operation.

3962:, where large companies began investing billions in AI research. According to AI Impacts, about $ 50 billion annually was invested in "AI" around 2022 in the U.S. alone and about 20% of the new U.S. Computer Science PhD graduates have specialized in "AI". About 800,000 "AI"-related U.S. job openings existed in 2022. 17846:, historian of computing, writes (in what might be called "Dyson's Law") that "Any system simple enough to be understandable will not be complicated enough to behave intelligently, while any system complicated enough to behave intelligently will be too complicated to understand." (p. 197.) Computer scientist 2891:'s new image labeling feature mistakenly identified Jacky Alcine and a friend as "gorillas" because they were black. The system was trained on a dataset that contained very few images of black people, a problem called "sample size disparity". Google "fixed" this problem by preventing the system from labelling 4626:" super-intelligent computer. Asimov's laws are often brought up during lay discussions of machine ethics; while almost all artificial intelligence researchers are familiar with Asimov's laws through popular culture, they generally consider the laws useless for many reasons, one of which is their ambiguity. 4254:, in the same sense that human beings do. This issue considers the internal experiences of the machine, rather than its external behavior. Mainstream AI research considers this issue irrelevant because it does not affect the goals of the field: to build machines that can solve problems using intelligence. 5345:

Searle presented this definition of "Strong AI" in 1999. Searle's original formulation was "The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states." Strong AI is defined similarly

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In 2017, the European Union considered granting "electronic personhood" to some of the most capable AI systems. Similarly to the legal status of companies, it would have conferred rights but also responsibilities. Critics argued in 2018 that granting rights to AI systems would downplay the importance

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similarly describes it as "the ability to solve hard problems". The leading AI textbook defines it as the study of agents that perceive their environment and take actions that maximize their chances of achieving defined goals. These definitions view intelligence in terms of well-defined problems with

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Machines with intelligence have the potential to use their intelligence to make ethical decisions. The field of machine ethics provides machines with ethical principles and procedures for resolving ethical dilemmas. The field of machine ethics is also called computational morality, and was founded at

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estimated 47% of U.S. jobs are at "high risk" of potential automation, while an OECD report classified only 9% of U.S. jobs as "high risk". The methodology of speculating about future employment levels has been criticised as lacking evidential foundation, and for implying that technology, rather than

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If approved (this will be the first ever US re-commissioning of a nuclear plant), over 835 megahertz of power – enough for 800,000 homes – of energy will be produced. The cost for re-opening and upgrading is estimated at $ 1.6 billion (US) and is dependent on tax breaks for nuclear power contained in

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with human-annotated data to improve answers for new problems and learn from corrections. A 2024 study showed that the performance of some language models for reasoning capabilities in solving math problems not included in their training data was low, even for problems with only minor deviations from

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The regulation of artificial intelligence is the development of public sector policies and laws for promoting and regulating AI; it is therefore related to the broader regulation of algorithms. The regulatory and policy landscape for AI is an emerging issue in jurisdictions globally. According to AI

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Promotion of the wellbeing of the people and communities that these technologies affect requires consideration of the social and ethical implications at all stages of AI system design, development and implementation, and collaboration between job roles such as data scientists, product managers, data

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as "cancerous", because pictures of malignancies typically include a ruler to show the scale. Another machine learning system designed to help effectively allocate medical resources was found to classify patients with asthma as being at "low risk" of dying from pneumonia. Having asthma is actually a

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nuclear power plant to provide Microsoft with 100% of all electric power produced by the plant for 20 years. Reopening the plant, which suffered a partial nuclear meltdown in 1979, will require Constellation to get through strict regulatory processes which will include extensive safety scrutiny from

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hopes to "solve intelligence, and then use that to solve everything else". However, as the use of AI has become widespread, several unintended consequences and risks have been identified. In-production systems can sometimes not factor ethics and bias into their AI training processes, especially when

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allow AI programs to answer questions intelligently and make deductions about real-world facts. Formal knowledge representations are used in content-based indexing and retrieval, scene interpretation, clinical decision support, knowledge discovery (mining "interesting" and actionable inferences from

18034:' we mean realistic videos produced using artificial intelligence that actually deceive people, then they barely exist. The fakes aren't deep, and the deeps aren't fake. A.I.-generated videos are not, in general, operating in our media as counterfeited evidence. Their role better resembles that of 8232:

Horne, Robert I.; Andrzejewska, Ewa A.; Alam, Parvez; Brotzakis, Z. Faidon; Srivastava, Ankit; Aubert, Alice; Nowinska, Magdalena; Gregory, Rebecca C.; Staats, Roxine; Possenti, Andrea; Chia, Sean; Sormanni, Pietro; Ghetti, Bernardino; Caughey, Byron; Knowles, Tuomas P. J.; Vendruscolo, Michele (17

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directly or to solve as many specific problems as possible (narrow AI) in hopes these solutions will lead indirectly to the field's long-term goals. General intelligence is difficult to define and difficult to measure, and modern AI has had more verifiable successes by focusing on specific problems

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published a joint statement in November 2021 calling for a government commission to regulate AI. In 2023, OpenAI leaders published recommendations for the governance of superintelligence, which they believe may happen in less than 10 years. In 2023, the United Nations also launched an advisory body

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There are various conflicting definitions and mathematical models of fairness. These notions depend on ethical assumptions, and are influenced by beliefs about society. One broad category is distributive fairness, which focuses on the outcomes, often identifying groups and seeking to compensate for

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experts like Nicolas Firzli insist it may be too early to see the emergence of highly innovative AI-informed financial products and services: "the deployment of AI tools will simply further automatise things: destroying tens of thousands of jobs in banking, financial planning, and pension advice in

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Among the most difficult problems in knowledge representation are the breadth of commonsense knowledge (the set of atomic facts that the average person knows is enormous); and the sub-symbolic form of most commonsense knowledge (much of what people know is not represented as "facts" or "statements"

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The general problem of simulating (or creating) intelligence has been broken into subproblems. These consist of particular traits or capabilities that researchers expect an intelligent system to display. The traits described below have received the most attention and cover the scope of AI research.

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wrote in 1950 "I propose to consider the question 'can machines think'?" He advised changing the question from whether a machine "thinks", to "whether or not it is possible for machinery to show intelligent behaviour". He devised the Turing test, which measures the ability of a machine to simulate

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in the UK to discuss the near and far term risks of AI and the possibility of mandatory and voluntary regulatory frameworks. 28 countries including the United States, China, and the European Union issued a declaration at the start of the summit, calling for international co-operation to manage the

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discovered that COMPAS exhibited racial bias, despite the fact that the program was not told the races of the defendants. Although the error rate for both whites and blacks was calibrated equal at exactly 61%, the errors for each race were different—the system consistently overestimated the chance

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Artificial intelligence is used in astronomy to analyze increasing amounts of available data and applications, mainly for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights" for example for discovering exoplanets, forecasting

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Instead, the United States has developed a new area of dominance that the rest of the world views with a mixture of awe, envy, and resentment: artificial intelligence... From AI models and research to cloud computing and venture capital, U.S. companies, universities, and research labs – and their

5047:, it refers to a tendency in favor or against a certain group or individual characteristic, usually in a way that is considered unfair or harmful. A statistically unbiased AI system that produces disparate outcomes for different demographic groups may thus be viewed as biased in the ethical sense. 2998:

It is impossible to be certain that a program is operating correctly if no one knows how exactly it works. There have been many cases where a machine learning program passed rigorous tests, but nevertheless learned something different than what the programmers intended. For example, a system that

2965:, in Seoul, South Korea, presented and published findings that recommend that until AI and robotics systems are demonstrated to be free of bias mistakes, they are unsafe, and the use of self-learning neural networks trained on vast, unregulated sources of flawed internet data should be curtailed. 2929:

Criticism of COMPAS highlighted that machine learning models are designed to make "predictions" that are only valid if we assume that the future will resemble the past. If they are trained on data that includes the results of racist decisions in the past, machine learning models must predict that

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Prodigious power consumption by AI is responsible for the growth of fossil fuels use, and might delay closings of obsolete, carbon-emitting coal energy facilities. There is a feverish rise in the construction of data centers throughout the US, making large technology firms (e.g., Microsoft, Meta,

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AI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal information, raising concerns about intrusive data gathering and unauthorized access by third parties. The loss of privacy is further exacerbated by AI's ability to process and combine vast

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Artificial intelligent (AI) agents are software entities designed to perceive their environment, make decisions, and take actions autonomously to achieve specific goals. These agents can interact with users, their environment, or other agents. AI agents are used in various applications, including

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is the set of objects, relations, concepts, and properties used by a particular domain of knowledge. Knowledge bases need to represent things such as objects, properties, categories, and relations between objects; situations, events, states, and time; causes and effects; knowledge about knowledge

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Many of these algorithms are insufficient for solving large reasoning problems because they experience a "combinatorial explosion": They become exponentially slower as the problems grow. Even humans rarely use the step-by-step deduction that early AI research could model. They solve most of their

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released in 2024 a testing toolset called 'Inspect' for AI safety evaluations available under a MIT open-source licence which is freely available on GitHub and can be improved with third-party packages. It can be used to evaluate AI models in a range of areas including core knowledge, ability to

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or render certain groups invisible. Procedural fairness focuses on the decision process rather than the outcome. The most relevant notions of fairness may depend on the context, notably the type of AI application and the stakeholders. The subjectivity in the notions of bias and fairness makes it

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since the 1960s that human expertise depends on unconscious instinct rather than conscious symbol manipulation, and on having a "feel" for the situation, rather than explicit symbolic knowledge. Although his arguments had been ridiculed and ignored when they were first presented, eventually, AI

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In the past, technology has tended to increase rather than reduce total employment, but economists acknowledge that "we're in uncharted territory" with AI. A survey of economists showed disagreement about whether the increasing use of robots and AI will cause a substantial increase in long-term

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A program can make biased decisions even if the data does not explicitly mention a problematic feature (such as "race" or "gender"). The feature will correlate with other features (like "address", "shopping history" or "first name"), and the program will make the same decisions based on these

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where they received multiple versions of the same misinformation. This convinced many users that the misinformation was true, and ultimately undermined trust in institutions, the media and the government. The AI program had correctly learned to maximize its goal, but the result was harmful to

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In agriculture, AI has helped farmers identify areas that need irrigation, fertilization, pesticide treatments or increasing yield. Agronomists use AI to conduct research and development. AI has been used to predict the ripening time for crops such as tomatoes, monitor soil moisture, operate

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agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved". They had, however, underestimated the difficulty of the problem. In 1974, both the U.S. and British governments cut off exploratory research in response to the

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has guided AI research for most of its history. The unprecedented success of statistical machine learning in the 2010s eclipsed all other approaches (so much so that some sources, especially in the business world, use the term "artificial intelligence" to mean "machine learning with neural

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did not sign the joint statement, emphasising that in 95% of all cases, AI research is about making "human lives longer and healthier and easier." While the tools that are now being used to improve lives can also be used by bad actors, "they can also be used against the bad actors."

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that the human mind is an information processing system and that thinking is a form of computing. Computationalism argues that the relationship between mind and body is similar or identical to the relationship between software and hardware and thus may be a solution to the

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disclosed a declaration signed by 31 nations to set guardrails for the military use of AI. The commitments include using legal reviews to ensure the compliance of military AI with international laws, and being cautious and transparent in the development of this technology.

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management are growing. AI has been used to investigate if and how people evacuated in large scale and small scale evacuations using historical data from GPS, videos or social media. Further, AI can provide real time information on the real time evacuation conditions.

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Another definition has been adopted by Google, a major practitioner in the field of AI. This definition stipulates the ability of systems to synthesize information as the manifestation of intelligence, similar to the way it is defined in biological intelligence.

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Some authors have suggested in practice, that the definition of AI is vague and difficult to define, with contention as to whether classical algorithms should be categorised as AI, with many companies during the early 2020s AI boom using the term as a marketing

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in 2016 included an explicit statement that this right exists. Industry experts noted that this is an unsolved problem with no solution in sight. Regulators argued that nevertheless the harm is real: if the problem has no solution, the tools should not be used.

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severe risk factor, but since the patients having asthma would usually get much more medical care, they were relatively unlikely to die according to the training data. The correlation between asthma and low risk of dying from pneumonia was real, but misleading.

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add that "he additional project of making a machine conscious in exactly the way humans are is not one that we are equipped to take on." However, the question has become central to the philosophy of mind. It is also typically the central question at issue in

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People who have been harmed by an algorithm's decision have a right to an explanation. Doctors, for example, are expected to clearly and completely explain to their colleagues the reasoning behind any decision they make. Early drafts of the European Union's

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identified two problems in understanding the mind, which he named the "hard" and "easy" problems of consciousness. The easy problem is understanding how the brain processes signals, makes plans and controls behavior. The hard problem is explaining how this

4101:") simulated the high-level conscious reasoning that people use when they solve puzzles, express legal reasoning and do mathematics. They were highly successful at "intelligent" tasks such as algebra or IQ tests. In the 1960s, Newell and Simon proposed the 3100:

A lethal autonomous weapon is a machine that locates, selects and engages human targets without human supervision. Widely available AI tools can be used by bad actors to develop inexpensive autonomous weapons and, if produced at scale, they are potentially

1752:, and others. The reason that deep learning performs so well in so many applications is not known as of 2023. The sudden success of deep learning in 2012–2015 did not occur because of some new discovery or theoretical breakthrough (deep neural networks and 11507: 8841:

Pinaya, Walter H. L.; Graham, Mark S.; Kerfoot, Eric; Tudosiu, Petru-Daniel; Dafflon, Jessica; Fernandez, Virginia; Sanchez, Pedro; Wolleb, Julia; da Costa, Pedro F.; Patel, Ashay (2023). "Generative AI for Medical Imaging: extending the MONAI Framework".

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began to create images, audio, video and text that are indistinguishable from real photographs, recordings, films, or human writing. It is possible for bad actors to use this technology to create massive amounts of misinformation or propaganda. AI pioneer

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and neural networks, that are tolerant of imprecision, uncertainty, partial truth and approximation. Soft computing was introduced in the late 1980s and most successful AI programs in the 21st century are examples of soft computing with neural networks.

3278:". This scenario has been common in science fiction, when a computer or robot suddenly develops a human-like "self-awareness" (or "sentience" or "consciousness") and becomes a malevolent character. These sci-fi scenarios are misleading in several ways. 2479:

There are also thousands of successful AI applications used to solve specific problems for specific industries or institutions. In a 2017 survey, one in five companies reported having incorporated "AI" in some offerings or processes. A few examples are

3557:, the Montreal Declaration for Responsible AI, and the IEEE's Ethics of Autonomous Systems initiative, among others; however, these principles do not go without their criticisms, especially regards to the people chosen contributes to these frameworks. 1469:

Many problems in AI (including in reasoning, planning, learning, perception, and robotics) require the agent to operate with incomplete or uncertain information. AI researchers have devised a number of tools to solve these problems using methods from

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imaging as a key technique in fabrication. It has been suggested that AI can overcome discrepancies in funding allocated to different fields of research. New AI tools can deepen the understanding of biomedically relevant pathways. For example,

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well-defined solutions, where both the difficulty of the problem and the performance of the program are direct measures of the "intelligence" of the machine—and no other philosophical discussion is required, or may not even be possible.

5310:: "After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. Computers are smarter and learning faster than ever", and noted that the number of software projects that use machine learning at 3648:

poll, 35% of Americans thought it "very important", and an additional 41% thought it "somewhat important", for the federal government to regulate AI, versus 13% responding "not very important" and 8% responding "not at all important".

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affiliates in allied countries – appear to have an enormous lead in both developing cutting-edge AI and commercializing it. The value of U.S. venture capital investments in AI start-ups exceeds that of the rest of the world combined.

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reported that big AI companies have begun negotiations with the US nuclear power providers to provide electricity to the data centers. In March 2024 Amazon purchased a Pennsylvania nuclear-powered data center for $ 650 Million (US).

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Artificial Intelligence projects can have their ethical permissibility tested while designing, developing, and implementing an AI system. An AI framework such as the Care and Act Framework containing the SUM values—developed by the

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reactor on Lake Michigan. Closed since 2022, the plant is planned to be reopened in October 2025. The Three Mile Island facility will be renamed the Crane Clean Energy Center after Chris Crane, a nuclear proponent and former CEO of

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in a biological brain. It is trained to recognise patterns; once trained, it can recognise those patterns in fresh data. There is an input, at least one hidden layer of nodes and an output. Each node applies a function and once the

2088:. In 2023, it was reported that AI-guided drug discovery helped find a class of antibiotics capable of killing two different types of drug-resistant bacteria. In 2024, researchers used machine learning to accelerate the search for 4368:(has the ability to feel), and if so, to what degree. But if there is a significant chance that a given machine can feel and suffer, then it may be entitled to certain rights or welfare protection measures, similarly to animals. 16554: 2950:

difficult for companies to operationalize them. Having access to sensitive attributes such as race or gender is also considered by many AI ethicists to be necessary in order to compensate for biases, but it may conflict with

588:—the ability to complete any task performable by a human on an at least equal level—is among the field's long-term goals. To reach these goals, AI researchers have adapted and integrated a wide range of techniques, including 11589: 18328:

fails at tasks that require real humanlike reasoning or an understanding of the physical and social world.... ChatGPT seemed unable to reason logically and tried to rely on its vast database of... facts derived from online

553:). However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's 3922:

and the misuse of technology were catapulted into center stage at machine learning conferences, publications vastly increased, funding became available, and many researchers re-focussed their careers on these issues. The

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competition, winning against four of the world's best Gran Turismo drivers using deep reinforcement learning. In 2024, Google DeepMind introduced SIMA, a type of AI capable of autonomously playing nine previously unseen

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Several approaches aim to address the transparency problem. SHAP enables to visualise the contribution of each feature to the output. LIME can locally approximate a model's outputs with a simpler, interpretable model.

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Finance is one of the fastest growing sectors where applied AI tools are being deployed: from retail online banking to investment advice and insurance, where automated "robot advisers" have been in use for some years.

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is difficult to explain. For example, it is easy to imagine a color-blind person who has learned to identify which objects in their field of view are red, but it is not clear what would be required for the person to

15375: 11545: 11515: 3256:, about whether tasks that can be done by computers actually should be done by them, given the difference between computers and humans, and between quantitative calculation and qualitative, value-based judgement. 3301:

gives the example of household robot that tries to find a way to kill its owner to prevent it from being unplugged, reasoning that "you can't fetch the coffee if you're dead." In order to be safe for humanity, a

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social policy, creates unemployment, as opposed to redundancies. In April 2023, it was reported that 70% of the jobs for Chinese video game illustrators had been eliminated by generative artificial intelligence.

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Daniel Crevier wrote that "time has proven the accuracy and perceptiveness of some of Dreyfus's comments. Had he formulated them less aggressively, constructive actions they suggested might have been taken much

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and theoretical artificial intelligence. It can refer to anything that directs its behavior to accomplish goals, such as a person, an animal, a corporation, a nation, or in the case of AI, a computer program.

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There many other ways that AI is expected to help bad actors, some of which can not be foreseen. For example, machine-learning AI is able to design tens of thousands of toxic molecules in a matter of hours.

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stated in 2015 that "the worry that AI could do to white-collar jobs what steam power did to blue-collar ones during the Industrial Revolution" is "worth taking seriously". Jobs at extreme risk range from

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began to dominate industry benchmarks in 2012 and was adopted throughout the field. For many specific tasks, other methods were abandoned. Deep learning's success was based on both hardware improvements

16183: 3915:). Deep learning's success led to an enormous increase in interest and funding in AI. The amount of machine learning research (measured by total publications) increased by 50% in the years 2015–2019. 14216: 15350: 2349:, communications, sensors, integration and interoperability. Research is targeting intelligence collection and analysis, logistics, cyber operations, information operations, and semiautonomous and 776:, the agent has preferences—there are some situations it would prefer to be in, and some situations it is trying to avoid. The decision-making agent assigns a number to each situation (called the " 15741: 4391:

Progress in AI increased interest in the topic. Proponents of AI welfare and rights often argue that AI sentience, if it emerges, would be particularly easy to deny. They warn that this may be a

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survey, attitudes towards AI varied greatly by country; 78% of Chinese citizens, but only 35% of Americans, agreed that "products and services using AI have more benefits than drawbacks". A 2023

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Artificial intelligence was founded as an academic discipline in 1956, and the field went through multiple cycles of optimism, followed by periods of disappointment and loss of funding, known as

15040: 3444:, who coined the term, argues that developing friendly AI should be a higher research priority: it may require a large investment and it must be completed before AI becomes an existential risk. 23730: 14669: 9711: 4293:

or why it should feel like anything at all, assuming we are right in thinking that it truly does feel like something (Dennett's consciousness illusionism says this is an illusion). While human

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had been described by many people, as far back as the 1950s) but because of two factors: the incredible increase in computer power (including the hundred-fold increase in speed by switching to

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AI developers argue that this is the only way to deliver valuable applications. and have developed several techniques that attempt to preserve privacy while still obtaining the data, such as

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and others developed methods that handled incomplete and uncertain information by making reasonable guesses rather than precise logic. But the most important development was the revival of "

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agree with Turing that intelligence must be defined in terms of external behavior, not internal structure. However, they are critical that the test requires the machine to imitate humans. "

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The simplest AI applications can be divided into two types: classifiers (e.g., "if shiny then diamond"), on one hand, and controllers (e.g., "if diamond then pick up"), on the other hand.

14535: 8905: 3694:, which suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable form of mathematical reasoning. This, along with concurrent discoveries in 9160:

Gomaa, Islam; Adelzadeh, Masoud; Gwynne, Steven; Spencer, Bruce; Ko, Yoon; Bénichou, Noureddine; Ma, Chunyun; Elsagan, Nour; Duong, Dana; Zalok, Ehab; Kinateder, Max (1 November 2021).

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Kaplan, Andreas; Haenlein, Michael (2019). "Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence".

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like plans, goals, beliefs, and known facts. In the 1980s, some researchers began to doubt that this approach would be able to imitate all the processes of human cognition, especially

15645: 13808: 18534: 8703: 4388:, and that legislation should focus on user needs rather than speculative futuristic scenarios. They also noted that robots lacked the autonomy to take part to society on their own. 3868:

AI gradually restored its reputation in the late 1990s and early 21st century by exploiting formal mathematical methods and by finding specific solutions to specific problems. This "

3383:

announced his resignation from Google in order to be able to "freely speak out about the risks of AI" without "considering how this impacts Google." He notably mentioned risks of an

1095:

are programmed to speak conversationally or even to banter humorously; it makes them appear more sensitive to the emotional dynamics of human interaction, or to otherwise facilitate

16705: 11593: 10627: 10290: 3798:, a form of AI program that simulated the knowledge and analytical skills of human experts. By 1985, the market for AI had reached over a billion dollars. At the same time, Japan's 3348:

The opinions amongst experts and industry insiders are mixed, with sizable fractions both concerned and unconcerned by risk from eventual superintelligent AI. Personalities such as

1102:

However, this tends to give naïve users an unrealistic conception of the intelligence of existing computer agents. Moderate successes related to affective computing include textual

17955:

come from acting in the world and experiencing the consequences. Artificial intelligences – disembodied, strangers to blood, sweat, and tears – have no occasion for that." (p. 30.)

3733:

in 1956. The attendees became the leaders of AI research in the 1960s. They and their students produced programs that the press described as "astonishing": computers were learning

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methods can allow developers to see what different layers of a deep network for computer vision have learned, and produce output that can suggest what the network is learning. For

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was launched in June 2020, stating a need for AI to be developed in accordance with human rights and democratic values, to ensure public confidence and trust in the technology.

1729:

uses several layers of neurons between the network's inputs and outputs. The multiple layers can progressively extract higher-level features from the raw input. For example, in

24116: 8954: 2934:, some of these "recommendations" will likely be racist. Thus, machine learning is not well suited to help make decisions in areas where there is hope that the future will be 748:(things that humans assume are true until they are told differently and will remain true even when other facts are changing); and many other aspects and domains of knowledge. 17916:

Gertner, Jon. (2023) "Knowledge's Moment of Truth: Can the online encyclopedia help teach A.I. chatbots to get their facts right — without destroying itself in the process?"

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amounts of data, potentially leading to a surveillance society where individual activities are constantly monitored and analyzed without adequate safeguards or transparency.

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as a "gorilla". Eight years later, in 2023, Google Photos still could not identify a gorilla, and neither could similar products from Apple, Facebook, Microsoft and Amazon.

14915: 15367: 9632: 9487: 2958: 15821: 11660: 11537: 23723: 21398: 17140: 11081: 5089:) argues that machine learning "is fundamentally the wrong tool for a lot of domains, where you're trying to design interventions and mechanisms that change the world." 4003:

human conversation. Since we can only observe the behavior of the machine, it does not matter if it is "actually" thinking or literally has a "mind". Turing notes that

1399:

is a single, axiom-free rule of inference, in which a problem is solved by proving a contradiction from premises that include the negation of the problem to be solved.

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Economists have frequently highlighted the risks of redundancies from AI, and speculated about unemployment if there is no adequate social policy for full employment.

2623:

Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code; the output is then used under the rationale of "

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crosses its specified threshold, the data is transmitted to the next layer. A network is typically called a deep neural network if it has at least 2 hidden layers.

15415: 14715: 14264: 13464: 2210:, a particularly challenging real-time strategy game that involves incomplete knowledge of what happens on the map. In 2021, an AI agent competed in a PlayStation 17441: 14596: 12222: 9110: 788:

of all possible outcomes of the action, weighted by the probability that the outcome will occur. It can then choose the action with the maximum expected utility.

16366: 8317: 15575: 14579: 8988: 3706:, led researchers to consider the possibility of building an "electronic brain". They developed several areas of research that would become part of AI, such as 3317:

argues that AI does not require a robot body or physical control to pose an existential risk. The essential parts of civilization are not physical. Things like

2096:(the protein that characterises Parkinson's disease). They were able to speed up the initial screening process ten-fold and reduce the cost by a thousand-fold. 1371:

Given a problem and a set of premises, problem-solving reduces to searching for a proof tree whose root node is labelled by a solution of the problem and whose

23716: 22717: 12327: 16722: 16175: 11036: 3503:, have been made open-weight, meaning that their architecture and trained parameters (the "weights") are publicly available. Open-weight models can be freely 2315:

Some models have been developed to solve challenging problems and reach good results in benchmark tests, others to serve as educational tools in mathematics.

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Alternatively, dedicated models for mathematic problem solving with higher precision for the outcome including proof of theorems have been developed such as

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said, of his work on neural networks in the 1990s, "our labeled datasets were thousands of times too small. our computers were millions of times too slow."

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features as it would on "race" or "gender". Moritz Hardt said "the most robust fact in this research area is that fairness through blindness doesn't work."

24770: 24765: 17641: 9750: 5584: 4959: 4337:. This philosophical position was inspired by the work of AI researchers and cognitive scientists in the 1960s and was originally proposed by philosophers 2809:

content, and, to keep them watching, the AI recommended more of it. Users also tended to watch more content on the same subject, so the AI led people into

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Asada, M.; Hosoda, K.; Kuniyoshi, Y.; Ishiguro, H.; Inui, T.; Yoshikawa, Y.; Ogino, M.; Yoshida, C. (2009). "Cognitive developmental robotics: a survey".

3031:

provides a large number of outputs in addition to the target classification. These other outputs can help developers deduce what the network has learned.

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Bias and unfairness may go undetected because the developers are overwhelmingly white and male: among AI engineers, about 4% are black and 20% are women.

2500:

agricultural robots, conduct predictive analytics, classify livestock pig call emotions, automate greenhouses, detect diseases and pests, and save water.

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and speaking English. Artificial intelligence laboratories were set up at a number of British and U.S. universities in the latter 1950s and early 1960s.

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The various subfields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include

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argue continuing research into symbolic AI will still be necessary to attain general intelligence, in part because sub-symbolic AI is a move away from

14661: 8204: 3387:, and stressed that in order to avoid the worst outcomes, establishing safety guidelines will require cooperation among those competing in use of AI. 798:

In some problems, the agent's preferences may be uncertain, especially if there are other agents or humans involved. These can be learned (e.g., with

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that "Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war".

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eruption data starts from a random guess but then successfully converges on an accurate clustering of the two physically distinct modes of eruption.

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https://videovoice.org/ai-in-finance-innovation-entrepreneurship-vs-over-regulation-with-the-eus-artificial-intelligence-act-wont-work-as-intended/

3511:) and that once released on the Internet, they can't be deleted everywhere if needed. They recommend pre-release audits and cost-benefit analyses. 2698: 17624: 15145: 22590: 19449: 18303: 17383: 16616: 15934: 14182: 4975: 3625:

to provide recommendations on AI governance; the body comprises technology company executives, governments officials and academics. In 2024, the

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However, the symbolic approach failed on many tasks that humans solve easily, such as learning, recognizing an object or commonsense reasoning.

1142:

AI can solve many problems by intelligently searching through many possible solutions. There are two very different kinds of search used in AI:

24598: 23903: 18407: 13256: 13140: 8486: 4979: 4912:

Compared with symbolic logic, formal Bayesian inference is computationally expensive. For inference to be tractable, most observations must be

4112:

is the discovery that high-level "intelligent" tasks were easy for AI, but low level "instinctive" tasks were extremely difficult. Philosopher

1761: 24757: 24087: 24067: 15637: 14361: 13789: 3609: 15863: 15161:

Iphofen, Ron; Kritikos, Mihalis (3 January 2019). "Regulating artificial intelligence and robotics: ethics by design in a digital society".

13800: 12305: 11567: 651:"). The widespread use of AI in the 21st century exposed several unintended consequences and harms in the present and raised concerns about 18775: 18525: 17461: 16697: 16637: 14235:(1988). Continuous valued neural networks with two hidden layers are sufficient (Report). Department of Computer Science, Tufts University. 13776:

Bertini, M; Del Bimbo, A; Torniai, C (2006). "Automatic annotation and semantic retrieval of video sequences using multimedia ontologies".

11428: 9430: 5086: 2746: 1543:

Probabilistic algorithms can also be used for filtering, prediction, smoothing, and finding explanations for streams of data, thus helping

10619: 3686:

The study of mechanical or "formal" reasoning began with philosophers and mathematicians in antiquity. The study of logic led directly to

1783:(LLMs) that generate text based on the semantic relationships between words in sentences. Text-based GPT models are pretrained on a large 880:, the agent is rewarded for good responses and punished for bad ones. The agent learns to choose responses that are classified as "good". 17968: 17363: 17190: 16090: 15721: 3205: 843:

describes the rational behavior of multiple interacting agents and is used in AI programs that make decisions that involve other agents.

210: 175: 12148: 6244: 4140:: it can be difficult or impossible to understand why a modern statistical AI program made a particular decision. The emerging field of 3285:" to be an existential risk. Modern AI programs are given specific goals and use learning and intelligence to achieve them. Philosopher 3249:

to fast food cooks, while job demand is likely to increase for care-related professions ranging from personal healthcare to the clergy.

1733:, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits, letters, or faces. 854:

is the study of programs that can improve their performance on a given task automatically. It has been a part of AI from the beginning.

806:

can be used to weigh the value of exploratory or experimental actions. The space of possible future actions and situations is typically

792: 21570: 18197:, "Artificial Confidence: Even the newest, buzziest systems of artificial general intelligence are stymmied by the same old problems", 16960: 15838: 15002:; Kingsbury, B. (2012). "Deep Neural Networks for Acoustic Modeling in Speech Recognition – The shared views of four research groups". 13085: 12803: 9692: 9050: 8603:

Srivastava, Saurabh (29 February 2024). "Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap".

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between networked combat vehicles involving manned and unmanned teams. AI was incorporated into military operations in Iraq and Syria.

1792: 17408: 16318: 4665:. Dick considers the idea that our understanding of human subjectivity is altered by technology created with artificial intelligence. 4510: 2999:

could identify skin diseases better than medical professionals was found to actually have a strong tendency to classify images with a

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Arntz, Melanie; Gregory, Terry; Zierahn, Ulrich (2016), "The risk of automation for jobs in OECD countries: A comparative analysis",

13506: 11281: 10668: 8928: 5967: 4683: 4629:

Several works use AI to force us to confront the fundamental question of what makes us human, showing us artificial beings that have

3406:

also argued that "it's a mistake to fall for the doomsday hype on AI—and that regulators who do will only benefit vested interests."

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Frey, Carl Benedikt; Osborne, Michael A (1 January 2017). "The future of employment: How susceptible are jobs to computerisation?".

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Sensitive user data collected may include online activity records, geolocation data, video or audio. For example, in order to build

1736:

Deep learning has profoundly improved the performance of programs in many important subfields of artificial intelligence, including

684:

Early researchers developed algorithms that imitated step-by-step reasoning that humans use when they solve puzzles or make logical

23873: 20580: 19505: 17708: 17063: 15885: 14935: 14308: 10331: 3105:. Even when used in conventional warfare, it is unlikely that they will be unable to reliably choose targets and could potentially 274: 252: 35: 17804: 17541: 17494: 15099: 13204: 13166: 12698: 10733: 8775: 2308:

When natural language is used to describe mathematical problems, converters transform such prompts into a formal language such as

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expressed concern about AI enabling "authoritarian leaders to manipulate their electorates" on a large scale, among other risks.

2353:. AI technologies enable coordination of sensors and effectors, threat detection and identification, marking of enemy positions, 2263: 2219:

video games by observing screen output, as well as executing short, specific tasks in response to natural language instructions.

1897: 1796: 1003:(or "GPT") language models began to generate coherent text, and by 2023, these models were able to get human-level scores on the 188: 17: 24329: 16934: 16158: 14475: 14439: 13276: 12837: 11414: 9478: 8459: 3252:

From the early days of the development of artificial intelligence, there have been arguments, for example, those put forward by

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theory and economics. Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using

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Galvan, Jill (1 January 1997). "Entering the Posthuman Collective in Philip K. Dick's "Do Androids Dream of Electric Sheep?"".

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Expectation–maximization, one of the most popular algorithms in machine learning, allows clustering in the presence of unknown

3440:

Friendly AI are machines that have been designed from the beginning to minimize risks and to make choices that benefit humans.

2550:

Machine learning algorithms require large amounts of data. The techniques used to acquire this data have raised concerns about

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to choose the weights that will get the right output for each input during training. The most common training technique is the

1562: 1521: 112: 17739: 10965: 10434: 9549: 24785: 24780: 24147: 23665: 23425: 22312: 19905: 19416: 19376: 18707: 18216: 18024:, "Your Lying Eyes: People now use A.I. to generate fake videos indistinguishable from real ones. How much does it matter?", 17790: 17252: 17167: 17132: 17106: 16920: 16678: 16506: 16482: 16152: 16114: 15673: 15523: 15315: 15257: 14988: 14773: 14560: 14504: 14469: 14433: 14409: 14385: 14297: 14162: 14117: 14092: 13630: 13438: 13365: 13343: 13306: 13270: 13198: 13160: 13124: 13094: 9137: 9059: 9032: 8519:

Wurman, P. R.; Barrett, S.; Kawamoto, K. (2022). "Outracing champion Gran Turismo drivers with deep reinforcement learning".

7516: 4657: 4546:

Thought-capable artificial beings have appeared as storytelling devices since antiquity, and have been a persistent theme in

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Researchers in the 1960s and the 1970s were convinced that their methods would eventually succeed in creating a machine with

3578: 2545: 2327: 2043: 1935: 660: 625: 407: 333: 287: 242: 237: 18385:"Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence" 18187: 17173: 16887: 16446: 15263: 11017: 9454: 4044:

McCarthy defines intelligence as "the computational part of the ability to achieve goals in the world". Another AI founder,

2060:, medical professionals are ethically compelled to use AI, if applications can more accurately diagnose and treat patients. 1221:

for 3 different starting points; two parameters (represented by the plan coordinates) are adjusted in order to minimize the

23346: 22804: 22163: 21429: 20575: 20367: 20362: 20357: 18494: 16231: 11706: 4884: 3715: 3565: 3554: 2760: 1881: 1851: 992: 644: 18168:

Leffer, Lauren, "The Risks of Trusting AI: We must avoid humanizing machine-learning models used in scientific research",

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Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure

8702:

M. Nicolas, J. Firzli: Pensions Age/European Pensions magazine, "Artificial Intelligence: Ask the Industry" May June 2024

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suggests that an AI could use language to convince people to believe anything, even to take actions that are destructive.

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It has been argued AI will become so powerful that humanity may irreversibly lose control of it. This could, as physicist

2518:

AI has potential benefits and potential risks. AI may be able to advance science and find solutions for serious problems:

466:

and intelligence to take actions that maximize their chances of achieving defined goals. Such machines may be called AIs.

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is a hypothetical agent that would possess intelligence far surpassing that of the brightest and most gifted human mind.

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wrote that experts have pivoted "from the question of 'what they know' to the question of 'what they're doing with it'."

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Matthew Finio & Amanda Downie: IBM Think 2024 Primer, "What is Artificial Intelligence (AI) in Finance?" 8 Dec. 2023

8108:"The future of personalized cardiovascular medicine demands 3D and 4D printing, stem cells, and artificial intelligence" 3591: 2848:

if they learn from biased data. The developers may not be aware that the bias exists. Bias can be introduced by the way

24887: 24827: 24800: 24055: 23018: 21822: 20613: 19477: 19098: 18676: 17433: 16416:"On the impact of robotics in behavioral and cognitive sciences: from insect navigation to human cognitive development" 16351: 15966: 15954: 15918: 9102: 8218: 5205: 4523: 4319: 4264: 4102: 4038: 3674: 3391: 3294: 3044: 3009: 2581:

to listen to and transcribe some of them. Opinions about this widespread surveillance range from those who see it as a

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with specific solutions. The experimental sub-field of artificial general intelligence studies this area exclusively.

2639:) sued AI companies for using their work to train generative AI. Another discussed approach is to envision a separate 24752: 24712: 24637: 23792: 22469: 22297: 21827: 21342: 20969: 20776: 20632: 20310: 20088: 20083: 20036: 19717: 15567: 14571: 13417: 13395: 13238: 11644: 10176: 6208: 5975: 3068: 2987:

Many AI systems are so complex that their designers cannot explain how they reach their decisions. Particularly with

2513: 1967: 1525: 1432:

assigns a "degree of truth" between 0 and 1. It can therefore handle propositions that are vague and partially true.

1242:

is a type of local search that optimizes a set of numerical parameters by incrementally adjusting them to minimize a

1162: 769: 569: 318: 264: 230: 97: 17998:, vol. 329, no. 4 (November 2023), pp. 81–82. "This murder mystery competition has revealed that although NLP ( 17034: 14838:

Goodman, Bryce; Flaxman, Seth (2017). "EU regulations on algorithmic decision-making and a 'right to explanation'".

14059: 12784: 11062: 1597:") is labeled with a certain predefined class. All the observations combined with their class labels are known as a 1165:

algorithms search through trees of goals and subgoals, attempting to find a path to a target goal, a process called

24919: 24822: 24740: 24735: 23802: 22557: 21651: 21297: 19411: 18768: 17843: 15813: 14877: 14455: 14050: 10940:"Hugging Face CEO says he's focused on building a 'sustainable model' for the $ 4.5 billion open-source-AI startup" 4505: 4094: 3427: 2852:

is selected and by the way a model is deployed. If a biased algorithm is used to make decisions that can seriously

2340: 716:

An ontology represents knowledge as a set of concepts within a domain and the relationships between those concepts.

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E. McGaughey, 'Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy' (2022),

9654: 7160:

Warren, D.H.; Pereira, L.M.; Pereira, F. (1977). "Prolog-the language and its implementation compared with Lisp".

3872:" and "formal" focus allowed researchers to produce verifiable results and collaborate with other fields (such as 3464: 2645:

system of protection for creations generated by AI to ensure fair attribution and compensation for human authors.

810:

large, so the agents must take actions and evaluate situations while being uncertain of what the outcome will be.

24226: 23757: 22725: 21945: 20385: 20098: 10268: 8809: 7668: 5971: 5466: 4428: 4210: 4083: 3931: 3885: 3745: 2797:

user engagement (that is, the only goal was to keep people watching). The AI learned that users tended to choose

2266:. Therefore, they need not only a large database of mathematical problems to learn from but also methods such as 1119: 585: 82: 17093:. Affective Computing: A Review. Lecture Notes in Computer Science. Vol. 3784. Springer. pp. 981–995. 16579: 13985:

Cambria, Erik; White, Bebo (May 2014). "Jumping NLP Curves: A Review of Natural Language Processing Research ".

13936: 10811: 9742: 9373: 23863: 22787: 22765: 22576: 22236: 22198: 21855: 21563: 21484: 21424: 21022: 20268: 19435: 19285: 19218: 18294:, "In Front of Their Faces: Does facial-recognition technology lead police to ignore contradictory evidence?", 17691: 17617:"What is 'fuzzy logic'? Are there computers that are inherently fuzzy and do not apply the usual binary logic?" 10939: 8036: 7143: 6278: 5588: 1096: 799: 740: 498: 16105:

Merkle, Daniel; Middendorf, Martin (2013). "Swarm Intelligence". In Burke, Edmund K.; Kendall, Graham (eds.).

14135:

Ciresan, D.; Meier, U.; Schmidhuber, J. (2012). "Multi-column deep neural networks for image classification".

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and is capable of generating high-quality human-like text. These programs, and others, inspired an aggressive

3293:

goal to a sufficiently powerful AI, it may choose to destroy humanity to achieve it (he used the example of a

1087:

is an interdisciplinary umbrella that comprises systems that recognize, interpret, process, or simulate human

24949: 24882: 24872: 24697: 24692: 23341: 22984: 22950: 22378: 22355: 22085: 22075: 21017: 20706: 20481: 19406: 19233: 18885: 18792: 17242: 15468:"Using Commercial Knowledge Bases for Clinical Decision Support: Opportunities, Hurdles, and Recommendations" 14817: 7773: 6513: 5155:

Daniel Crevier wrote, "the conference is generally recognized as the official birthdate of the new science."

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statistical disparities. Representational fairness tries to ensure that AI systems do not reinforce negative

2751: 1885: 1463: 1107: 895: 17992:, which has stumped humans for decades, reveals the limitations of natural-language-processing algorithms", 15391: 3644:/Ipsos poll found that 61% of Americans agree, and 22% disagree, that AI poses risks to humanity. In a 2023 24747: 24707: 24196: 24094: 23954: 23883: 23617: 22459: 22047: 21955: 21860: 21636: 21621: 21459: 20856: 20813: 20766: 20761: 19958: 19951: 19051: 18825: 17939: 13921: 13312: 4764: 4689: 4645: 4572: 4315: 4206: 4014:

The Turing test can provide some evidence of intelligence, but it penalizes non-human intelligent behavior.

2105: 1700: 1012: 996: 24125: 15041:"Bill Gates on dangers of artificial intelligence: 'I don't understand why some people are not concerned'" 9526: 8864: 3841:

rejected "representation" in general and focussed directly on engineering machines that move and survive.

3238:

Unlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence;

2814:

society. After the U.S. election in 2016, major technology companies took steps to mitigate the problem .

2395:

gained widespread prominence. GenAI is AI capable of generating text, images, videos, or other data using

1902:

AI and machine learning technology is used in most of the essential applications of the 2020s, including:

24795: 24790: 24687: 24672: 24100: 23491: 23435: 22547: 22282: 21780: 21510: 20806: 20732: 20476: 20420: 19810: 19785: 19770: 19401: 18761: 18712: 18660: 17999: 9132:, Woodhead Publishing Series in Civil and Structural Engineering, Woodhead Publishing, pp. 185–204, 9125: 6944: 6598: 6557: 6532: 5044: 4695: 4185: 3504: 3102: 2881: 2839: 2704: 2613: 2270: 1745: 1703:

strengthen the connection between neurons that are "close" to each other—this is especially important in

1669: 1269: 1229: 1147: 918: 577: 269: 220: 117: 24424: 18578: 17921: 17351: 15970: 15198:

Jordan, M. I.; Mitchell, T. M. (16 July 2015). "Machine learning: Trends, perspectives, and prospects".

14998:

Hinton, G.; Deng, L.; Yu, D.; Dahl, G.; Mohamed, A.; Jaitly, N.; Senior, A.; Vanhoucke, V.; Nguyen, P.;

14553:

The Latest Answers to the Oldest Questions: A Philosophical Adventure with the World's Greatest Thinkers

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agreed, writing that "Artificial intelligence is not, by definition, simulation of human intelligence".

4029:

texts," they wrote, "do not define the goal of their field as making 'machines that fly so exactly like

3121:

and others disagreed. By 2015, over fifty countries were reported to be researching battlefield robots.

821:

that describes the probability that a particular action will change the state in a particular way and a

24847: 24817: 24206: 23655: 23051: 22955: 22891: 22519: 22168: 21134: 21069: 20670: 20440: 20430: 19150: 19140: 17616: 15539: 15137: 14399: 12445: 10650: 7691: 6966: 5217: 4758: 4740: 4737: – List of definitions of terms and concepts commonly used in the study of artificial intelligence 4707: 4432: 4163: 4117: 4086:. Critics argue that these questions may have to be revisited by future generations of AI researchers. 3784: 3633:". It was adopted by the European Union, the United States, the United Kingdom, and other signatories. 3209: 2274: 2015: 1691:

feed the output signal back into the input, which allows short-term memories of previous input events.

1684: 1257:, which aims to iteratively improve a set of candidate solutions by "mutating" and "recombining" them, 889: 866: 92: 15938: 13686:

Berdahl, Carl Thomas; Baker, Lawrence; Mann, Sean; Osoba, Osonde; Girosi, Federico (7 February 2023).

11538:"Countries agree to safe and responsible development of frontier AI in landmark Bletchley Declaration" 9200: 9124:

Sun, Yuran; Zhao, Xilei; Lovreglio, Ruggiero; Kuligowski, Erica (1 January 2024), Naser, M. Z. (ed.),

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This list of intelligent traits is based on the topics covered by the major AI textbooks, including:

4501: 4448: 4167: 3881: 3799: 3185: 3129: 2794: 2484:, medical diagnosis, military logistics, applications that predict the result of judicial decisions, 2400: 2135: 1987: 1757: 1625: 1233: 1050: 965: 773: 601: 593: 170: 18384: 13861: 12202: 8344: 8235:"Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning" 4215:

AI researchers are divided as to whether to pursue the goals of artificial general intelligence and

3787:

would never be useful for solving real-world tasks, thus discrediting the approach altogether. The "

3752:

predicted, "machines will be capable, within twenty years, of doing any work a man can do". In 1967

63: 24944: 24682: 24652: 24574: 24266: 23888: 23807: 22710: 22388: 22221: 21807: 21676: 21434: 20691: 20405: 20352: 20333: 19988: 19628: 19613: 19602: 19579: 19384: 18722: 18006:

they receive. This could cause for researchers who hope to use them to do things such as analyze

16005: 15771: 14636: 13932: 7707: 7551: 7487: 7466: 7318: 7256: 6990: 6294: 5854: 5576: 4497: 4233: 4105:: "A physical symbol system has the necessary and sufficient means of general intelligent action." 3900: 3582: 3275: 3064: 2978: 2031: 1857: 1688: 1601:. When a new observation is received, that observation is classified based on previous experience. 1582: 1537: 1483: 1301: 1254: 1008: 976:

believed that it was meaning and not grammar that was the key to understanding languages, and that

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problems using fast, intuitive judgments. Accurate and efficient reasoning is an unsolved problem.

565: 526: 294: 17768:, "Why Are There Still So Many Jobs? The History and Future of Workplace Automation" (2015) 29(3) 16465:

Pennachin, C.; Goertzel, B. (2007). "Contemporary Approaches to Artificial General Intelligence".

14765: 12223:"AI is closer than ever to passing the Turing test for 'intelligence'. What happens when it does?" 10785: 10760:"Juergen Schmidhuber, Renowned 'Father Of Modern AI,' Says His Life's Work Won't Lead To Dystopia" 8955:"Misinformation, mistakes and the Pope in a puffer: what rapidly evolving AI can – and can't – do" 3341:; they exist because there are stories that billions of people believe. The current prevalence of 2777: 2759:. The US government and the state of Michigan are investing almost $ 2 billion (US) to reopen the 647:, and by the early 2020s hundreds of billions of dollars were being invested in AI (known as the " 24837: 24812: 24647: 24642: 24241: 23292: 23287: 22903: 22876: 22705: 22449: 22383: 22090: 21750: 21479: 21464: 21117: 21112: 21012: 20661: 20461: 20226: 19973: 19968: 19941: 19876: 19830: 19825: 19760: 19653: 19083: 18692: 18002:) models are capable of incredible feats, their abilities are very much limited by the amount of 17827: 16323: 15869: 15610: 15513: 15420: 14287: 12295: 11330: 10408: 7559: 7272: 6310: 6100: 6096: 5809: 5751: 3431: 2951: 2756: 2246: 2092:

drug treatments. Their aim was to identify compounds that block the clumping, or aggregation, of

1963: 1865: 1487: 1277: 1236:

to find a solution to a problem. It begins with some form of guess and refines it incrementally.

1026:

is the ability to use input from sensors (such as cameras, microphones, wireless signals, active

814: 23708: 17857:

are, at their core, dead simple stupid. They work, but they work by brute force." (p. 198.)

17477: 16742: 16633: 16242:

Neumann, Bernd; Möller, Ralf (January 2008). "On scene interpretation with description logics".

16030:

McGarry, Ken (1 December 2005). "A survey of interestingness measures for knowledge discovery".

15757:

Lungarella, M.; Metta, G.; Pfeifer, R.; Sandini, G. (2003). "Developmental robotics: a survey".

15698:

The Narrative and the Algorithm: Genres of Credit Reporting from the Nineteenth Century to Today

5326:

wrote in 1983: "Simply put, there is wide disagreement in the field about what AI is all about."

4891:

wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".

4496:

argues that "artificial intelligence is the next stage in evolution", an idea first proposed by

3865:

can recognize handwritten digits, the first of many successful applications of neural networks.

1364:, in which nodes are labelled by sentences, and children nodes are connected to parent nodes by 780:") that measures how much the agent prefers it. For each possible action, it can calculate the " 24867: 24852: 24564: 24454: 24309: 24256: 24181: 23812: 23486: 23011: 22913: 22908: 22881: 22799: 22514: 22345: 22226: 21993: 21983: 21978: 21439: 21199: 20918: 20913: 20530: 20400: 20347: 20181: 20171: 19589: 19515: 19472: 19335: 19330: 19238: 18653: 16000: 15766: 15696: 14807: 14631: 13856: 12888: 11965: 8318:"Twenty years on from Deep Blue vs Kasparov: how a chess match started the big data revolution" 7599: 7070: 6449: 5281: 4619: 4440: 4004: 3994: 3631:

Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law

3621: 2309: 2252: 2195: 2113:

programs have been used since the 1950s to demonstrate and test AI's most advanced techniques.

2089: 1860:(GPUs) that were increasingly designed with AI-specific enhancements and used with specialized 1692: 1676:

algorithm. Neural networks learn to model complex relationships between inputs and outputs and

1621: 1617: 938: 877: 861:

analyzes a stream of data and finds patterns and makes predictions without any other guidance.

656: 165: 18632: 17960: 16086: 16060: 13688:"Strategies to Improve the Impact of Artificial Intelligence on Health Equity: Scoping Review" 11185:"A critical perspective on guidelines for responsible and trustworthy artificial intelligence" 6260:

Sensorless or "conformant" planning, contingent planning, replanning (a.k.a online planning):

5179:

wrote "for the next 20 years the field would be dominated by these people and their students."

4962:(1961). Deep or recurrent networks that learned (or used gradient descent) were developed by: 4482:

that are more capable and powerful than either. This idea, called transhumanism, has roots in

4158:"Neats" hope that intelligent behavior is described using simple, elegant principles (such as 3810:

market in 1987, AI once again fell into disrepute, and a second, longer-lasting winter began.

2930:

racist decisions will be made in the future. If an application then uses these predictions as

1080:, a robot head which was made in the 1990s; a machine that can recognize and simulate emotions 24939: 24722: 24662: 24554: 24359: 23767: 23597: 23451: 23061: 22839: 22700: 22599: 22484: 22454: 22444: 22340: 22254: 22130: 22070: 22037: 22027: 21910: 21875: 21865: 21802: 21671: 21646: 21641: 21606: 21469: 21454: 21419: 21107: 21007: 20875: 20565: 20550: 20031: 20026: 19978: 19946: 19936: 19895: 19675: 19552: 19458: 19320: 19310: 19248: 19198: 19172: 19078: 19073: 18960: 18935: 18810: 18003: 17646: 16496: 14333: 14107: 12300: 12140: 10708:"Rise of artificial intelligence is inevitable but should not be feared, 'father of AI' says" 10651:"Canadian artificial intelligence leader Geoffrey Hinton piles on fears of computer takeover" 10286: 8989:"How a fake image of a Pentagon explosion shared on Twitter caused a real dip on Wall Street" 6394: 6160: 5858: 5065: 4942:

Some form of deep neural networks (without a specific learning algorithm) were described by:

4752: 4334: 4298: 3691: 3653: 3521: 2211: 2179: 2175: 942: 858: 753: 724: 21337: 16992:

Smoliar, Stephen W.; Zhang, HongJiang (1994). "Content based video indexing and retrieval".

16840: 16790: 16107:

Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques

14757: 12758: 12729: 4710: – Ability of a computer to learn a specific task from data or experimental observation 4380:

are also sometimes proposed as a practical way to integrate autonomous agents into society.

4128:

reasoning can make many of the same inscrutable mistakes that human intuition does, such as

2995:

relationships between inputs and outputs. But some popular explainability techniques exist.

1446:. Other specialized versions of logic have been developed to describe many complex domains. 24934: 24892: 24877: 24842: 24832: 24677: 24434: 24133: 23858: 23547: 23471: 23236: 23196: 23046: 22886: 22849: 22829: 22745: 22626: 22244: 22216: 22188: 22183: 22012: 21988: 21940: 21923: 21918: 21900: 21890: 21885: 21847: 21797: 21792: 21709: 21655: 21489: 21444: 20890: 20835: 20681: 20676: 20011: 20006: 19881: 19765: 19670: 19643: 19525: 19355: 19088: 18732: 18439: 18239: 18121: 18062: 17731: 17527: 17469: 15295: 15207: 15073: 15011: 14785:"10 years later, deep learning 'revolution' rages on, say AI pioneers Hinton, LeCun and Li" 14374:

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

13144: 12421: 11490:

Milmo, Dan (3 November 2023). "Hope or Horror? The great AI debate dividing its pioneers".

10049: 8528: 8417: 8160: 6856: 4987: 4701: 4353: 4109: 3951: 3919: 2988: 2982: 2742: 2605: 2460: 2350: 2187: 1979: 1911: 1873: 1780: 1749: 1423: 1258: 1180: 1122:

should be able to solve a wide variety of problems with breadth and versatility similar to

1046: 818: 107: 17557:

Weng, J.; McClelland; Pentland, A.; Sporns, O.; Stockman, I.; Sur, M.; Thelen, E. (2001).

13841: 13522:

Anderson, Susan Leigh (2008). "Asimov's "three laws of robotics" and machine metaethics".

13498: 13456: 11508:"The Bletchley Declaration by Countries Attending the AI Safety Summit, 1–2 November 2023" 8: 24857: 24807: 24717: 24667: 24579: 24519: 24479: 24281: 24261: 24221: 24073: 23696: 23638: 23501: 23201: 23041: 22943: 22918: 22755: 22730: 22648: 22509: 22434: 22350: 22335: 22100: 21880: 21837: 21832: 21729: 21719: 21691: 21064: 21042: 20791: 20786: 20744: 20696: 20509: 20415: 20073: 19755: 19648: 19623: 19608: 19537: 19035: 18865: 18320: 18199: 18170: 17994: 17944: 17118:"'Godfather of AI' Geoffrey Hinton quits Google and warns over dangers of misinformation" 16655: 16062:

Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy

15908: 15611:

Law Library of Congress (U.S.). Global Legal Research Directorate, issuing body. (2019).

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However, technologies cannot improve exponentially indefinitely, and typically follow an

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associates a decision with each possible state. The policy could be calculated (e.g., by

807: 777: 685: 643:

outperformed previous AI techniques. This growth accelerated further after 2017 with the

609: 561: 514: 259: 31: 24590: 18568: 18443: 18243: 18125: 18066: 17735: 17473: 16516: 15814:"The case against killer robots, from a guy actually working on artificial intelligence" 15299: 15211: 15015: 14425:

Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer

13780:. 14th ACM international conference on Multimedia. Santa Barbara: ACM. pp. 679–682. 13722: 13687: 10327: 9347: 8626:"AI achieves silver-medal standard solving International Mathematical Olympiad problems" 8532: 8421: 8259: 8234: 8164: 4826:

This list of tools is based on the topics covered by the major AI textbooks, including:

3109:. In 2014, 30 nations (including China) supported a ban on autonomous weapons under the 3023:("Explainable Artificial Intelligence") program in 2014 to try to solve these problems. 2345:

Various countries are deploying AI military applications. The main applications enhance

2117:

became the first computer chess-playing system to beat a reigning world chess champion,

2056:

has the potential to increase patient care and quality of life. Through the lens of the

1624:

is reportedly the "most widely used learner" at Google, due in part to its scalability.

1191:" or "rules of thumb" can help prioritize choices that are more likely to reach a goal. 24484: 24459: 24399: 24324: 24251: 24201: 23607: 23582: 23572: 23537: 23481: 23461: 23408: 23381: 23319: 23231: 23165: 23066: 22960: 22673: 22658: 22631: 22474: 22373: 22249: 22206: 22115: 22057: 22042: 22032: 21817: 21616: 21449: 21027: 20456: 20425: 20395: 20221: 20176: 20063: 19886: 19707: 19542: 19532: 19388: 19263: 19113: 18784: 18737: 18727: 18697: 18463: 18371: 18263: 18145: 18096: 18083: 18050: 17780: 17683: 17589: 17532: 17313: 17300: 17275: 17009: 16879: 16828: 16802: 16778: 16546: 16438: 16259: 16223: 16074: 16047: 16018: 15784: 15713: 15492: 15467: 15329: 15231: 15186: 15091: 15027: 14865: 14847: 14694: 14168: 14140: 14002: 13735: 13675: 13585: 13539: 13353: 13187: 13149: 11263: 11220: 11165: 8869: 8843: 8732: 8630: 8604: 8181: 8148: 8080: 8055: 7555: 7504: 7394: 7139: 6928: 6864: 6860: 6824: 6004: 5515: 5444: 5061: 4719: 4704: – Process of solving new problems based on the solutions of similar past problems 4554: 4329: 4251: 4239: 4189: 3990: 3822: 3726: 3699: 3231: 3173: 3149: 3028: 2790: 2570: 2464: 2354: 2072: 1915: 1741: 1653: 1609: 1544: 1533: 1513: 1396: 1317: 1309: 1265: 1194: 1172: 1158: 1143: 1123: 1103: 1054: 1042: 1023: 973: 957: 946: 926: 922: 589: 482: 470: 459: 309: 15343:"Regulate AI? GOP much more skeptical than Dems that government can do it right: poll" 13870: 8405: 4567:, where a human creation becomes a threat to its masters. This includes such works as 3946:. The program was taught only the rules of the game and developed strategy by itself. 2262:

are working with probabilistic models, which can produce wrong answers in the form of

1589:

to determine the closest match. They can be fine-tuned based on chosen examples using

24509: 24404: 24364: 24039: 24014: 23832: 23684: 23648: 23577: 23506: 23393: 23179: 23081: 23056: 23004: 22782: 22735: 22494: 22424: 22403: 22365: 22173: 22140: 22120: 21812: 21724: 21598: 21515: 21503: 21307: 20959: 20830: 20823: 20595: 20570: 20560: 20514: 20499: 20410: 20280: 20053: 19910: 19700: 19665: 19559: 19498: 19325: 19182: 18800: 18527:

White Paper: On Artificial Intelligence – A European approach to excellence and trust

18455: 18375: 18363: 18343: 18267: 18255: 18212: 18137: 18100: 18088: 17988: 17882: 17865: 17796: 17786: 17687: 17675: 17581: 17352:"Amazon reportedly employs thousands of people to listen to your Alexa conversations" 17317: 17305: 17248: 17231: 17163: 17102: 16926: 16916: 16910: 16820: 16684: 16674: 16664: 16550: 16502: 16478: 16328: 16271: 16148: 16141: 16110: 16082: 16078: 15717: 15669: 15624: 15616: 15519: 15497: 15333: 15321: 15311: 15253: 15223: 15178: 15048: 15031: 14984: 14931: 14769: 14649: 14556: 14500: 14465: 14459: 14429: 14423: 14405: 14381: 14293: 14158: 14123: 14113: 14088: 14006: 13908: 13739: 13727: 13709: 13636: 13626: 13434: 13413: 13391: 13361: 13339: 13302: 13266: 13260: 13234: 13220: 13194: 13156: 13120: 13100: 13090: 13076: 12811: 11640: 11267: 11255: 11240:"Ethical issues in the development of artificial intelligence: recognizing the risks" 11224: 11212: 11204: 11169: 9381: 9220: 9181: 9133: 9055: 9028: 8962: 8783: 8748: 8544: 8494: 8441: 8433: 8353: 8291: 8264: 8186: 8129: 8085: 7512: 7434: 7236: 7098: 7066: 6896: 6852: 6469: 6080: 6040: 5963: 5448: 5436: 5347: 5249: 5188: 5172: 5156: 5040: 4971: 4920:

uses a Bayesian network with over 300 million edges to learn which ads to serve.

4651: 4421: 4255: 4216: 4141: 4018: 3986: 3803: 3730: 3707: 3665:, 16 global AI tech companies agreed to safety commitments on the development of AI. 3626: 3460: 3441: 3365: 3314: 3303: 3298: 3253: 3189: 2898: 2802: 2601: 2452: 2085: 1971: 1947: 1823: 1558: 1479: 1443: 1411: 1392: 1388: 1161:

searches through a tree of possible states to try to find a goal state. For example,

1092: 903: 881: 745: 538: 474: 447: 87: 39: 20151: 18895: 18501: 18226:

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; et al. (26 February 2015).

17593: 17013: 16883: 16832: 16263: 16051: 16022: 15804: 15190: 14493: 13679: 13589: 9101:

Ransbotham, Sam; Kiron, David; Gerbert, Philipp; Reeves, Martin (6 September 2017).

2084:(2021) demonstrated the ability to approximate, in hours rather than months, the 3D 1410:. However, backward reasoning with Horn clauses, which underpins computation in the 24549: 24499: 24444: 24379: 24369: 24299: 24276: 24061: 24034: 23934: 23782: 23633: 23511: 23496: 23371: 23363: 23282: 23241: 23226: 23174: 23076: 22928: 22844: 22760: 22740: 22695: 22690: 22327: 22211: 22178: 21973: 21895: 21784: 21770: 21765: 21714: 21701: 21626: 21579: 21260: 21250: 21057: 20851: 20801: 20796: 20739: 20727: 20605: 20585: 20555: 20545: 20251: 20206: 20186: 19722: 19712: 19695: 19167: 19160: 19125: 19093: 18915: 18447: 18399: 18355: 18247: 18149: 18129: 18078: 18070: 18021: 18007: 17877: 17851: 17720: 17667: 17573: 17295: 17287: 17223: 17094: 17001: 16871: 16812: 16782: 16770: 16668: 16536: 16528: 16470: 16442: 16430: 16303: 16287: 16251: 16227: 16215: 16066: 16039: 16010: 15926: 15788: 15776: 15705: 15548: 15487: 15479: 15303: 15215: 15170: 15019: 14869: 14857: 14645: 14641: 14256: 14172: 14150: 14080: 13994: 13973: 13962:

Buttazzo, G. (July 2001). "Artificial consciousness: Utopia or real possibility?".

13898: 13866: 13804: 13717: 13699: 13665: 13657: 13577: 13543: 13531: 13405: 11247: 11196: 11155: 9212: 9173: 9020: 8756: 8536: 8425: 8283: 8254: 8246: 8176: 8168: 8119: 8075: 8067: 7470: 7354: 7338: 7276: 7171: 6796: 6406: 6342: 5959: 5826: 5824: 5822: 5628: 5428: 5256:

write: "in almost all cases, these early systems failed on more difficult problems"

5225: 5011: 5003: 4995: 4967: 4963: 4930: 4770: 4129: 3830: 3758: 3749: 3596: 3500: 3435: 3141: 3055:

that associates patterns of neuron activations with human-understandable concepts.

2845: 2835: 2662: 2636: 2597: 2590: 2578: 2574: 2427: 2423: 2396: 2240: 2057: 2053: 1983: 1931: 1927: 1869: 1807: 1788: 1730: 1704: 1586: 1565: 1529: 1517: 1505: 1499: 1491: 1459: 1384: 1247: 1239: 1218: 1184: 1176: 961: 930: 851: 830: 781: 573: 502: 490: 463: 451: 225: 160: 145: 19108: 18467: 17893:"US Leadership in Artificial Intelligence Can Shape the 21st Century Global Order" 17671: 15307: 15235: 15174: 10786:"Andrew Ng: 'Do we think the world is better off with more or less intelligence?'" 9201:"Modelling and interpreting pre-evacuation decision-making using machine learning" 7963: 5830:

Psychological evidence of the prevalence of sub-symbolic reasoning and knowledge:

4435:. The improved software would be even better at improving itself, leading to what 2383: 2331:

the process, but I’m not sure it will unleash a new wave of pension innovation."

1640:

A neural network is an interconnected group of nodes, akin to the vast network of

24539: 24529: 24429: 24414: 24394: 24389: 24374: 24354: 24314: 24304: 24231: 23999: 23979: 23969: 23959: 23893: 23827: 23542: 23527: 23430: 23420: 23412: 23277: 23150: 23128: 23118: 22398: 22292: 22264: 22158: 22110: 22095: 22080: 21935: 21930: 21870: 21760: 21734: 21686: 21631: 21373: 21317: 21139: 20781: 20701: 20540: 20241: 20201: 20123: 20078: 19915: 19820: 19805: 19780: 19594: 19574: 19010: 18870: 18830: 18609: 18493:." Advances in neural information processing systems 30 (2017). Seminal paper on 18334: 18285: 18179: 17838: 17776: 17577: 17274:

Urbina, Fabio; Lentzos, Filippa; Invernizzi, Cédric; Ekins, Sean (7 March 2022).

17157: 16856: 16816: 16532: 16415: 16402: 16255: 15935:"A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence" 15780: 15683: 15411: 15279: 15247: 15243: 14102: 13649: 13468: 10992:"The open-source AI boom is built on Big Tech's handouts. How long will it last?" 10335: 9216: 7640: 7232: 6653: 6228: 6012: 5432: 5406: 5069: 5043:

is a systematic error or deviation from the correct value. But in the context of

5027: 4991: 4983: 4547: 4487: 4404: 4400: 4392: 3904: 3854: 3813:

Up to this point, most of AI's funding had gone to projects that used high-level

3662: 3613: 3456: 3380: 3349: 3271: 3177: 2823: 2678: 2617: 2294: 2093: 1753: 1737: 1673: 1475: 1313: 1062: 1058: 1035: 869:(where the program must learn to predict what category the input belongs in) and 865:

requires a human to label the input data first, and comes in two main varieties:

822: 102: 18049:

Jumper, John; Evans, Richard; Pritzel, Alexander; et al. (26 August 2021).

17384:"OpenAI has published the text-generating AI it said was too dangerous to share" 16474: 16200: 15638:"Will artificial intelligence destroy humanity? Here are 5 reasons not to worry" 9712:"Three Mile Island's Nuclear Plant to Reopen, Help Power Microsoft's AI Centers" 8760: 5819: 3397:

Other researchers, however, spoke in favor of a less dystopian view. AI pioneer

921:(NLP) allows programs to read, write and communicate in human languages such as 24534: 24494: 24489: 24464: 24439: 24409: 24344: 24339: 24334: 24319: 24271: 24216: 24176: 23822: 23660: 23476: 23466: 23388: 23331: 23272: 23211: 23206: 23191: 23123: 22933: 22653: 22504: 22408: 22307: 22153: 22125: 21347: 21312: 21302: 21127: 20885: 20711: 20504: 20466: 20435: 20292: 20161: 20021: 19660: 19569: 19270: 19120: 19015: 18925: 18890: 18860: 18845: 18815: 18742: 18605: 18486: 18296: 18074: 18026: 17833: 17819: 17291: 17227: 17214: 17021: 16723:"Computer says no: why making AIs fair, accountable and transparent is crucial" 16698:"Stephen Hawking, Elon Musk, and Bill Gates Warn About Artificial Intelligence" 16515:

Poria, Soujanya; Cambria, Erik; Bajpai, Rajiv; Hussain, Amir (September 2017).

15930: 15116: 14976: 14419: 14395: 14369: 14283: 14232: 14041: 14015: 13494: 13383: 13292: 13252: 12968: 12353:"AI or BS? How to tell if a marketing tool really uses artificial intelligence" 12089: 11866: 11251: 11200: 9567: 9177: 8679: 8540: 8250: 8172: 8124: 8107: 6414: 6008: 5307: 5233: 5229: 5108: 4999: 4955: 4917: 4888: 4746: 4662: 4590: 4493: 4455: 4373: 4285: 4280: 4179: 4137: 4113: 4079: 3896: 3818: 3774: 3657: 3553:

Other developments in ethical frameworks include those decided upon during the

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with humanity's morality and values so that it is "fundamentally on our side".

3157: 3110: 2974: 2877: 2869: 2810: 2798: 2670: 2582: 2519: 2485: 2481: 2118: 1991: 1903: 1815: 1787:

that can be from the Internet. The pretraining consists of predicting the next

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is a body of knowledge represented in a form that can be used by a program. An

736: 18427: 18426:

Silver, David; Huang, Aja; Maddison, Chris J.; et al. (28 January 2016).

18403: 18359: 18227: 18109: 16875: 16774: 16688: 16517:"A review of affective computing: From unimodal analysis to multimodal fusion" 16434: 16409:. presented and distributed at the 2007 Singularity Summit, San Francisco, CA. 16043: 16014: 15839:"What jobs will still be around in 20 years? Read this to prepare your future" 15628: 15553: 15534: 14962: 14154: 14127: 13640: 13581: 13535: 13151:

Artificial Intelligence: Structures and Strategies for Complex Problem Solving

11160: 8071: 6489: 5314:

increased from a "sporadic usage" in 2012 to more than 2,700 projects in 2015.

4634: 4533: 4188:

for many important problems. Soft computing is a set of techniques, including

3714:

design for "artificial neurons" in 1943, and Turing's influential 1950 paper '

1760:) and the availability of vast amounts of training data, especially the giant 980:

and not dictionaries should be the basis of computational language structure.

24913: 24559: 24544: 24524: 24514: 24469: 24449: 24419: 24291: 24211: 24029: 23974: 23944: 23612: 23567: 23251: 23246: 23221: 23216: 22965: 22792: 22393: 21681: 21292: 21272: 21189: 20868: 20491: 20471: 20211: 20146: 20118: 20046: 19775: 19690: 19350: 19275: 19228: 19145: 19135: 19040: 18995: 18990: 18965: 18940: 18930: 18910: 18835: 18702: 18367: 18015: 17847: 17679: 17656:"Artificial Intelligence and the Public Sector – Applications and Challenges" 17558: 17466:

Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace

17235: 16930: 16492: 16332: 16124: 15922: 15904: 15661: 15182: 15052: 15023: 14881: 14861: 14653: 14084: 13998: 13912: 13837: 13713: 13490: 13431:

The Brain Makers: Genius, Ego, And Greed In The Quest For Machines That Think

12943: 12815: 11259: 11239: 11208: 11184: 11143: 10620:""Godfather of artificial intelligence" talks impact and potential of new AI" 9385: 9224: 9185: 9161: 8966: 8787: 8498: 8437: 8357: 8295: 8133: 7742: 7310: 6088: 6084: 6016: 5703: 5440: 5273: 5265: 5213: 5195:

wrote "it was astonishing whenever a computer did anything kind of smartish".

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When the law was passed in 2018, it still contained a form of this provision.

5057: 4883:

discussed the centrality of learning as early as 1950, in his classic paper "

4851: 4674: 4608: 4584: 4483: 4471: 4458:, slowing when they reach the physical limits of what the technology can do. 4342: 4247: 4045: 3934:

companies began to deliver programs that created enormous interest. In 2015,

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For medical research, AI is an important tool for processing and integrating

1907: 1799:", although this can be reduced with RLHF and quality data. They are used in 1726: 1652:

An artificial neural network is based on a collection of nodes also known as

1605: 1552: 1349: 1243: 1222: 1134:

AI research uses a wide variety of techniques to accomplish the goals above.

888:

is a type of machine learning that runs inputs through biologically inspired

885: 640: 542: 478: 155: 18625:. BBC Radio 4 discussion with John Agar, Alison Adam & Igor Aleksander ( 18622: 17800: 17462:"The Coming Technological Singularity: How to Survive in the Post-Human Era" 17364:"A Complete Guide to SHAP – SHAPley Additive exPlanations for Practitioners" 17064:"Artificial Intelligence Index Report 2023/Chapter 6: Policy and Governance" 16219: 15219: 14075:

Challa, Subhash; Moreland, Mark R.; Mušicki, Darko; Evans, Robin J. (2011).

13358:

Introduction to Artificial Intelligence: from data analysis to generative AI

9614:"AI is exhausting the power grid. Tech firms are seeking a miracle solution" 9595:"AI already uses as much energy as a small country. It's only the beginning" 8929:"ChatGPT: Most Americans Know About It, But Few Actually Use the AI Chatbot" 8722: 8429: 7509:

Introduction to Artificial Intelligence: from data analysis to generative AI

6076: 6074: 4010: 3791:", a period when obtaining funding for AI projects was difficult, followed. 1819: 1636: 24569: 24474: 24349: 24191: 24155: 24019: 23949: 23762: 23376: 23351: 23336: 23309: 23299: 23160: 23071: 22869: 22668: 22489: 22148: 21378: 21209: 20624: 20302: 20256: 20236: 20191: 20166: 20156: 20128: 20058: 20016: 19890: 19844: 19815: 19795: 19305: 19295: 19290: 19253: 19203: 19000: 18980: 18970: 18900: 18820: 18459: 18311: 18259: 18141: 18092: 18011: 17926: 17897: 17585: 17457: 17309: 17122: 16824: 16283: 16136: 15563: 15509: 15501: 15325: 15283: 15227: 14999: 14940: 13785: 13731: 13224: 13080: 12916: 12664: 12536:, p. 24) A classic example of the "scruffy" approach to intelligence: 11216: 8548: 8445: 8268: 8190: 8089: 6490:"Artificial Intelligence (AI): What Is AI and How Does It Work? | Built In" 5351: 5294: 5269: 5253: 5221: 5192: 5176: 5160: 4947: 4615: 4563: 4558: 4475: 4467: 4444: 4385: 4377: 4323: 4259: 4133: 4125: 4075: 4022: 3924: 3807: 3711: 3703: 3617: 3599:

was held in 2023 with a declaration calling for international co-operation.

3508: 3476: 3307: 3286: 3223: 3219: 3137: 3094: 2914: 2632: 2555: 2439: 2435: 2431: 2207: 2171: 2151: 1955: 1569: 1073: 988: 969: 953: 884:

is when the knowledge gained from one problem is applied to a new problem.

873:(where the program must deduce a numeric function based on numeric input). 629: 510: 435: 299: 17721:"Artificial Intelligence as a Positive and Negative Factor in Global Risk" 17409:"The scary truth about AI copyright is nobody knows what will happen next" 16308: 16291: 14354:"Robots With Flawed AI Make Sexist And Racist Decisions, Experiment Shows" 13747:

Berryhill, Jamie; Heang, Kévin Kok; Clogher, Rob; McBride, Keegan (2019).

12328:"One of the Biggest Problems in Regulating AI Is Agreeing on a Definition" 9024: 8380:"AlphaGo retires from competitive Go after defeating world number one 3–0" 7175: 4372:(a set of capacities related to high intelligence, such as discernment or 3629:

created the first international legally binding treaty on AI, called the "

2692: 1612:

algorithm was the most widely used analogical AI until the mid-1990s, and

1608:

is the simplest and most widely used symbolic machine learning algorithm.

712: 597: 24626: 24504: 24384: 24246: 24186: 24157: 24024: 24009: 23817: 23777: 23398: 23324: 23314: 23304: 23267: 23184: 23145: 23096: 22864: 22859: 22680: 22479: 22105: 22017: 21474: 21245: 21154: 21149: 20771: 20749: 20590: 20246: 20231: 20216: 20196: 20113: 20041: 19858: 19848: 19835: 19800: 19750: 19680: 19633: 19520: 19510: 19371: 19345: 19155: 19068: 19045: 19020: 19005: 18905: 18880: 18855: 18850: 18194: 18043:

The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI

17861: 17765: 17209: 17025: 16906: 16852: 16070: 15709: 14377: 14045: 13778:

MM '06 Proceedings of the 14th ACM international conference on Multimedia

13426: 13112: 11702: 10305: 9693:"Microsoft deal would reopen Three Mile Island nuclear plant to power AI" 7334: 6326: 6071: 6057: 5805: 5277: 5015: 4951: 4880: 4365: 4349: 4338: 4193: 4026: 3999: 3982: 3846: 3842: 3814: 3802:

project inspired the U.S. and British governments to restore funding for

3794:

In the early 1980s, AI research was revived by the commercial success of

3719: 3695: 3687: 3384: 3169: 2865: 2793:

to guide users to more content. These AI programs were given the goal of

2686: 2641: 2410:

and 14% had tried it. The increasing realism and ease-of-use of AI-based

2167: 2147: 2081: 1803:, which allow people to ask a question or request a task in simple text. 1645: 1495: 1471: 1429: 1380: 840: 693: 689: 621: 328: 313: 22568: 19427: 18975: 18451: 18251: 18133: 16974:"ChatGPT-4 Creator Ilya Sutskever on AI Hallucinations and AI Democracy" 15483: 13670: 13661: 11331:

Law Library of Congress (U.S.). Global Legal Research Directorate (2019)

9014: 2430:

AI-generated photos. Widespread attention was gained by a fake photo of

1699:

use only a single layer of neurons; deep learning uses multiple layers.

764:

An "agent" is anything that perceives and takes actions in the world. A

23989: 23964: 23939: 23898: 23878: 22824: 22499: 22429: 22022: 21755: 21611: 21368: 21327: 21322: 21235: 21144: 21052: 20964: 20944: 20133: 19862: 19853: 19840: 19584: 19547: 19208: 19130: 19030: 18950: 18920: 18875: 18324:, vol. 329, no. 1 (July/August 2023), p. 7. "Despite its high IQ, 18291: 17952: 17326: 16469:. Cognitive Technologies. Berlin, Heidelberg: Springer. pp. 1–30. 14895:"Google's Photo App Still Can't Find Gorillas. And Neither Can Apple's" 14803: 14698: 14260: 13903: 13886: 13486: 12908: 11037:"Stability announces Stable Diffusion 3, a next-gen AI image generator" 8205:"AI discovers new class of antibiotics to kill drug-resistant bacteria" 8101: 8099: 7723: 5112: 4868: 4596: 4436: 4364:

It is difficult or impossible to reliably evaluate whether an advanced

3873: 3858: 3779: 3496: 3484: 3407: 3373: 3353: 3326: 3153: 2946: 2918: 2910: 2902: 2666: 2628: 2415: 2258: 2216: 2076: 1868:(CPUs) as the dominant means for large-scale (commercial and academic) 1861: 1696: 1372: 1188: 1110:, wherein AI classifies the affects displayed by a videotaped subject. 825:

that supplies the utility of each state and the cost of each action. A

688:. By the late 1980s and 1990s, methods were developed for dealing with 617: 605: 20287: 17005: 16597:"Revealed: The Authors Whose Pirated Books are Powering Generative AI" 16571: 16541: 15991:

McCauley, Lee (2007). "AI armageddon and the three laws of robotics".

15734:"Robots Will Take Jobs, but Not as Fast as Some Fear, New Report Says" 14733:"Elon Musk: artificial intelligence is our biggest existential threat" 14708:"Is artificial intelligence really an existential threat to humanity?" 13750:

Hello, World: Artificial Intelligence and its Use in the Public Sector

11500: 11429:"Council of Europe opens first ever global treaty on AI for signature" 8865:"Anthropic Said to Be Closing In on $ 300 Million in New A.I. Funding" 6703: 6050: 4478:

have predicted that humans and machines will merge in the future into

3230:. Risk estimates vary; for example, in the 2010s, Michael Osborne and 3184:. All these technologies have been available since 2020 or earlier—AI 3077:

Artificial intelligence provides a number of tools that are useful to

1795:(RLHF). Current GPT models are prone to generating falsehoods called " 24236: 24004: 23994: 23772: 23562: 23456: 23155: 22854: 22004: 21965: 21363: 21332: 21230: 21074: 21037: 20974: 20928: 20923: 20908: 20377: 19900: 19493: 19280: 19213: 19177: 18840: 18805: 18753: 18031: 17854: 17642:"Humans may be more likely to believe disinformation generated by AI" 17098: 14528:"Poll: AI poses risk to humanity, according to majority of Americans" 13977: 13941: 12540:

A modern example of neat AI and its aspirations in the 21st century:

12221:

Kirk-Giannini, Cameron Domenico; Goldstein, Simon (16 October 2023).

9431:"Getting the Innovation Ecosystem Ready for AI. An IP policy toolkit" 9126:"8 – AI for large-scale evacuation modeling: promises and challenges" 8776:"The US and 30 Other Nations Agree to Set Guardrails for Military AI" 6892: 6778: 5952: 5668: 5624: 5007: 4864: 4716: – Hypothetical concept of storing a personality in digital form 4630: 3943: 3888:(or "AGI"), which had several well-funded institutions by the 2010s. 3877: 3869: 3788: 3586: 3423: 3403: 3357: 3282: 3246: 3161: 3090: 3086: 3078: 3072: 3048: 3036: 2906: 2738: 2682: 2674: 2586: 2559: 2163: 2159: 2127: 2123: 1999: 1662: 1281: 1205:

of possible moves and counter-moves, looking for a winning position.

1202: 834: 697: 664: 636: 613: 554: 550: 363: 127: 18428:"Mastering the game of Go with deep neural networks and tree search" 17655: 17244:

UNESCO Science Report: the Race Against Time for Smarter Development

16844: 16670:

Human Compatible: Artificial Intelligence and the Problem of Control

11394: 11183:

Buruk, Banu; Ekmekci, Perihan Elif; Arda, Berna (1 September 2020).

10211: 10209: 8096: 7795: 4007:

but "it is usual to have a polite convention that everyone thinks."

3661:

challenges and risks of artificial intelligence. In May 2024 at the

3168:

aid in producing misinformation. Advanced AI can make authoritarian

1695:

is the most successful network architecture for recurrent networks.

1422:. Moreover, its efficiency is competitive with computation in other 23984: 23602: 23552: 23027: 22775: 22750: 22065: 21548: 21265: 21097: 19920: 19638: 18717: 18332:

Scharre, Paul, "Killer Apps: The Real Dangers of an AI Arms Race",

17033:. Dartmouth Summer Research Conference on Artificial Intelligence. 15394:. MIT Artificial Intelligence Laboratory, Humanoid Robotics Group. 14852: 14020: 13652:(2009), "The New Frontier of Human-Level Artificial Intelligence", 12122: 11637:

The Essential Turing: the ideas that gave birth to the computer age

11568:"Second global AI summit secures safety commitments from companies" 8848: 8651: 8609: 6834: 6139: 6137: 5928: 5146:"Electronic brain" was the term used by the press around this time. 5073: 4743: – Use of information technology to augment human intelligence 4623: 4579: 4369: 4070: 4058: 3939: 3912: 3908: 3826: 3734: 3645: 3605: 3338: 3318: 2873: 2786: 2654: 2624: 2523: 2492: 2456: 2206:

games. In 2019, DeepMind's AlphaStar achieved grandmaster level in

2191: 2068: 2064: 2049: 2019: 2003: 1943: 1765: 1598: 1356:) from other statements that are given and assumed to be true (the 1316:(which also operates on objects, predicates and relations and uses 1213: 1004: 977: 768:

has goals or preferences and takes actions to make them happen. In

752:

that they could express verbally). There is also the difficulty of

729: 581: 455: 443: 200: 122: 18590: 18180:"Content: Plug & Pray Film – Artificial Intelligence – Robots" 17947:

is what distinguishes us from machines. For biological creatures,

17057:. Vol. Section on Information Theory, part 2. pp. 56–62. 16807: 16761:

Scassellati, Brian (2002). "Theory of mind for a humanoid robot".

16201:"Future Progress in Artificial Intelligence: A Poll Among Experts" 15886:"Google's Gemini: is the new AI model really better than ChatGPT?" 15620: 15593:"What is Artificial Intelligence and How Does AI Work? TechTarget" 14823: 14145: 13704: 13134:

These were the four of the most widely used AI textbooks in 2008:

12394: 10435:"China's game art industry reportedly decimated by growing AI use" 10368: 9162:"A Framework for Intelligent Fire Detection and Evacuation System" 8564:"Google AI learns to play open-world video games by watching them" 7895: 7893: 7891: 7866: 7864: 5904: 4755:– Use of brain cells and brain organoids for intelligent computing 4061:, often even if they did "not actually use AI in a material way". 2677:. Some of these players already own the vast majority of existing 1391:

from the problem. In the more general case of the clausal form of

24622: 23738: 23532: 23113: 21388: 21225: 21179: 21102: 21002: 20997: 20949: 19618: 19223: 18325: 18307: 18035: 17654:

Wirtz, Bernd W.; Weyerer, Jan C.; Geyer, Carolin (24 July 2018).

14967: 14016:"Stephen Hawking warns artificial intelligence could end mankind" 11282:"AI Safety Institute releases new AI safety evaluations platform" 10669:"'50–50 chance' that AI outsmarts humanity, Geoffrey Hinton says" 10594:

Leaders' concerns about the existential risks of AI around 2015:

10287:"Security lapse exposed a Chinese smart city surveillance system" 10206: 9303: 8749:"Artificial intelligence as the basis of future control networks" 8666: 8106:

Bax, Monique; Thorpe, Jordan; Romanov, Valentin (December 2023).

5707: 5209: 5163:

called the conference "the inception of artificial intelligence."

4902:

AI winter § Machine translation and the ALPAC report of 1966

4396: 3959: 3935: 3738: 3641: 3334: 3181: 2782: 2551: 2527:

the AI algorithms are inherently unexplainable in deep learning.

2407: 2387:

Vincent van Gogh in watercolour created by generative AI software

2178:, who was the best Go player in the world. Other programs handle 2155: 2110: 2011: 1995: 1939: 1923: 1919: 1811: 1800: 1657: 1454: 1357: 1198: 802:), or the agent can seek information to improve its preferences. 785: 652: 648: 530: 494: 486: 439: 368: 18645: 17327:"Artificial intelligence could lead to extinction, experts warn" 15117:"Artificial Intelligence at Edinburgh University: a Perspective" 13296: 13104: 12699:"Nick Bostrom: How can we be certain a machine isn't conscious?" 11351: 11082:"Should we make our most powerful AI models open source to all?" 11018:"Mistral AI's New Language Model Aims for Open Source Supremacy" 10885: 10883: 10734:"'Father of AI' says tech fears misplaced: 'You cannot stop it'" 9890: 9888: 9199:

Zhao, Xilei; Lovreglio, Ruggiero; Nilsson, Daniel (1 May 2020).

7851: 7849: 7847: 7845: 7843: 7841: 7839: 7328: 6715: 6691: 6679: 6667: 6623: 6567: 6134: 4431:

produced sufficiently intelligent software, it might be able to

3172:

more competitive than liberal and decentralized systems such as

1449: 23918: 23587: 23138: 23133: 21403: 21383: 21255: 21047: 20390: 19685: 19340: 18637: 18010:. In some cases, there are few historical records on long-gone 17948: 16395:

Funding a Revolution: Government Support for Computing Research

15613:

Regulation of artificial intelligence in selected jurisdictions

15466:

Kuperman, G. J.; Reichley, R. M.; Bailey, T. C. (1 July 2006).

14756:

Goffrey, Andrew (2008). "Algorithm". In Fuller, Matthew (ed.).

14137:

2012 IEEE Conference on Computer Vision and Pattern Recognition

13233:(2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, 13228: 10858: 10856: 8011:"Mojo Rising: The resurgence of AI-first programming languages" 7905: 7888: 7876: 7861: 7826: 7824: 7822: 5480:

Warnings of overspecialization in AI from leading researchers:

5311: 5237: 4639: 4538: 4511:

Darwin Among the Machines: The Evolution of Global Intelligence

4479: 4030: 3955: 3480: 3106: 2992: 2765: 2419: 2199: 2027: 2023: 2007: 1877: 1719: 1641: 1576: 1415: 534: 15917: 12925: 12645: 12546: 11613: 11611: 10508: 8807: 8720: 8231: 5869:, pp. 23–46, 69–81, 169–233, 235–277, 281–298, 319–345), 5742:

Problem-solving, puzzle solving, game playing, and deduction:

5533: 5383: 5381: 5379: 5124:

See table 4; 9% is both the OECD average and the U.S. average.

1308:(which operates on statements that are true or false and uses 23557: 23105: 22770: 21204: 21184: 21174: 21169: 21164: 21159: 21122: 20954: 18985: 18288:, which produced human-level performance on some Atari games. 18108:

LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (28 May 2015).

18051:"Highly accurate protein structure prediction with AlphaFold" 16319:"How YouTube Drives People to the Internet's Darkest Corners" 15756: 15443:"GPUs Continue to Dominate the AI Accelerator Market for Now" 15286:(1982). "Judgment under uncertainty: Heuristics and biases". 14183:"Why 2015 Was a Breakthrough Year in Artificial Intelligence" 12998: 12671:. Searle's original presentation of the thought experiment., 12573: 12382: 11973: 11920: 11238:

Kamila, Manoj Kumar; Jasrotia, Sahil Singh (1 January 2023).

10880: 10409:"AI is already taking video game illustrators' jobs in China" 10221: 10194: 10156: 10144: 9885: 9291: 9243: 8487:"AI becomes grandmaster in 'fiendishly complex' StarCraft II" 8149:"Highly accurate protein structure prediction with AlphaFold" 7836: 7807: 7293: 7291: 7289: 7226: 7018: 5580: 4692: – Algorithm that selects actions for intelligent agents 4600:(1999). In contrast, the rare loyal robots such as Gort from 4528: 4223: 4159: 4098: 3947: 3637: 3492: 3475:

Active organizations in the AI open-source community include

3330: 3222:, but they generally agree that it could be a net benefit if 3148:

potential enemies of the state and prevent them from hiding.

3016: 3000: 2233: 2203: 2183: 1827: 1680:

in data. In theory, a neural network can learn any function.

1402:

Inference in both Horn clause logic and first-order logic is

1376: 1293: 1027: 546: 518: 17556: 17276:"Dual use of artificial-intelligence-powered drug discovery" 17273: 13746: 13598:"Ask the AI experts: What's driving today's progress in AI?" 13567: 13474:

Alter, Alexandra; Harris, Elizabeth A. (20 September 2023),

13298:

Artificial Intelligence: Foundations of Computational Agents

12163: 12014: 11986: 11977: 11969: 11896: 11848: 11812: 11756: 11744: 11303: 10853: 10311: 10269:"How China Uses High-Tech Surveillance to Subdue Minorities" 9100: 9016:

Artificial Intelligence, Foundations of Computational Agents

8460:"MuZero: Mastering Go, chess, shogi and Atari without rules" 7819: 7361:, sects. 12.5–12.6, 13.4–13.5, 14.3–14.5, 16.5, 20.2–20.3), 7000: 6190: 5940: 4887:". In 1956, at the original Dartmouth AI summer conference, 1268:

algorithms. Two popular swarm algorithms used in search are

23592: 22996: 21194: 19564: 19315: 19243: 17836:, "Ready for Robots? How to Think about the Future of AI", 16743:"Exploring LIME Explanations and the Mathematics Behind It" 16609:"Thinking Machines: The Search for Artificial Intelligence" 16292:"Computer Science as Empirical Inquiry: Symbols and Search" 15075:

Multilayer Feedforward Networks are Universal Approximators

15072:

Hornik, Kurt; Stinchcombe, Maxwell; White, Halbert (1989).

13887:"Towards Intelligent Regulation of Artificial Intelligence" 12240: 11608: 10966:"Google open sources tools to support AI model development" 10068: 9924: 9741:

Rainie, Lee; Keeter, Scott; Perrin, Andrew (22 July 2019).

9438: 9159: 8896:

Lanxon, Nate; Bass, Dina; Davalos, Jackie (10 March 2023).

7460: 7376: 5699: 5697: 5376: 4749: – Hypothetical process of digitally emulating a brain 4243: 3449: 2938:

than the past. It is descriptive rather than prescriptive.

2853: 2577:

has recorded millions of private conversations and allowed

1951: 506: 17053:

Solomonoff, Ray (1957). "An Inductive Inference Machine".

16384:

Association for the Advancement of Artificial Intelligence

15368:"Noam Chomsky on Where Artificial Intelligence Went Wrong" 14816:

Goodfellow, Ian; Bengio, Yoshua; Courville, Aaron (2016),

14809:

Speculations Concerning the First Ultraintelligent Machine

14074: 13801:"What happens when our computers get smarter than we are?" 11768: 11144:"A Unified Framework of Five Principles for AI in Society" 10576: 9123: 8840: 8590:

Improving mathematical reasoning with process supervision.

7783: 7286: 6709: 6178: 3376:, have expressed concerns about existential risk from AI. 756:, the problem of obtaining knowledge for AI applications. 24620: 18228:"Human-level control through deep reinforcement learning" 18225: 17191:"Transformers Revolutionized AI. What Will Replace Them?" 16793:(2015). "Deep Learning in Neural Networks: An Overview". 16615:. Vol. 2, no. 2. pp. 14–23. Archived from 16514: 15294:(4157). New York: Cambridge University Press: 1124–1131. 14815: 14334:"Machine learning: What is the transformer architecture?" 14309:"AI has already changed the world. This report shows how" 14209:"Commentary: Bad news. Artificial intelligence is biased" 13562:

OECD Social, Employment, and Migration Working Papers 189

13476:"Franzen, Grisham and Other Prominent Authors Sue OpenAI" 11732: 11108:"Understanding artificial intelligence ethics and safety" 11063:"How enterprises are using open source LLMs: 16 examples" 10496: 10056: 9912: 9655:"Energy-Guzzling AI Is Also the Future of Energy Savings" 9550:"In the Age of A.I., Tech's Little Guys Need Big Friends" 8056:"The potential for artificial intelligence in healthcare" 7750: 6784: 6056:

Representing knowledge about knowledge: Belief calculus,

5892: 5354:: "Stong AI – the assertion that machines that do so are 4990:(1982). Precursors to backpropagation were developed by: 3322: 2768:

who was responsible for Exelon spinoff of Constellation.

2170:-playing system to beat a professional Go player without 2131: 20391:

Covariance Matrix Adaptation Evolution Strategy (CMA-ES)

17212:(October 1950), "Computing Machinery and Intelligence", 12456:

Historical significance and philosophical implications:

11459: 10452: 10356: 10177:"New Anthropic Research Sheds Light on AI's 'Black Box'" 10108: 10096: 9873: 9455:"Big Tech is spending more than VC firms on AI startups" 9411: 9315: 7581: 7480: 7416: 7250: 5880: 5694: 5010:(1969); Backpropagation was independently developed by: 4415: 2959:

Conference on Fairness, Accountability, and Transparency

2689:, allowing them to entrench further in the marketplace. 1175:

are rarely sufficient for most real-world problems: the

639:. Funding and interest vastly increased after 2012 when 18425: 18315: 18048: 17842:, vol. 98, no. 4 (July/August 2019), pp. 192–198. 16634:"Five experts share what scares them the most about AI" 15472:

Journal of the American Medical Informatics Association

14134: 13775: 13756:. Paris: OECD Observatory of Public Sector Innovation. 13623:

Research handbook on the law of artificial intelligence

13485: 12563: 12561: 12475: 12192: 12190: 11959: 11836: 11415:"UN Announces Advisory Body on Artificial Intelligence" 11400: 11341: 11339: 10919: 9769: 7801: 7266: 6166: 5934: 5339: 4730:

Pages displaying short descriptions of redirect targets

4679:

Pages displaying short descriptions of redirect targets

3128:

to efficiently control their citizens in several ways.

2884:

studies how to prevent harms from algorithmic biases.

2693:

Substantial power needs and other environmental impacts

1383:, problem-solving search can be performed by reasoning 17943:, vol. LXXI, no. 1 (18 January 2024), pp. 27–28, 30. " 17048:– via std.com, pdf scanned copy of the original. 16653:

Rose, Steve (11 July 2023). "AI Utopia or dystopia?".

15465: 15071: 12804:"Give robots 'personhood' status, EU committee argues" 12439: 12370: 12220: 12106: 12104: 12102: 11949: 11947: 11824: 11590:"Frontier AI Safety Commitments, AI Seoul Summit 2024" 11382: 11372: 11370: 11368: 11366: 10868: 9900: 9837: 9633:"AI Data Centers and the Coming YS Power Demand Surge" 9255: 7978: 7680: 7203: 7201: 6425: 6423: 6376: 6034: 5910: 4761: – Form of business process automation technology 3737:

strategies, solving word problems in algebra, proving

3722:

and showed that "machine intelligence" was plausible.

2442:, as well as the usage in professional creative arts. 1547:

systems analyze processes that occur over time (e.g.,

23798:

Existential risk from artificial general intelligence

17961:"Human rights for robots? We're getting carried away" 17559:"Autonomous mental development by robots and animals" 15686:(1973). "Artificial Intelligence: A General Survey". 15278: 13685: 13388:

AI: The Tumultuous Search for Artificial Intelligence

13034: 13022: 13010: 12585: 12264: 12050: 11908: 11713:

Historical influence and philosophical implications:

11471: 11123: 11105: 10018: 9855: 9757: 9674:"Tech Industry Wants to Lock Up Nuclear Power for AI" 9279: 9231: 8808:

Newsom, Gavin; Weber, Shirley N. (6 September 2023).

8518: 7990: 5843: 4542:, the title standing for "Rossum's Universal Robots". 4309: 3748:

and considered this the goal of their field. In 1965

3266:

Existential risk from artificial general intelligence

2434:

wearing a white puffer coat, the fictional arrest of

2227:

In mathematics, special forms of formal step-by-step

1620:(SVM) displaced k-nearest neighbor in the 1990s. The 1201:

programs, such as chess or Go. It searches through a

18382: 18209:

Artificial intelligence: a guide for thinking humans

16407:

The Nature of Self-Improving Artificial Intelligence

14882:

Consumer Data: Increasing Use Poses Risks to Privacy

13247: 13067:

The two most widely used textbooks in 2023 (see the

12864:"Robot rights violate human rights, experts warn EU" 12633: 12597: 12558: 12511: 12487: 12187: 12175: 11932: 11447: 11336: 10907: 10687: 10532: 10520: 10486:

Tarnoff, Ben (4 August 2023). "Lessons from Eliza".

10132: 9815: 9813: 9793:"Why it's so damn hard to make AI fair and unbiased" 9399: 9327: 9198: 7503: 7446: 7402: 7362: 7244: 7212: 7159: 7119: 7078: 6908: 6872: 6804: 6635: 6540: 6350: 6112: 6065: 6044: 6024: 5983: 5866: 5780: 5755: 5585:

Microelectronics and Computer Technology Corporation

5511: 5509: 4835: 4808: 4407:

if sentient AI is created and carelessly exploited.

4005:

we can not determine these things about other people

3837:, and began to look into "sub-symbolic" approaches. 3537:

with other people sincerely, openly, and inclusively

2724:

AI Data Centers and the Coming US Power Demand Surge

1841: 906:(how much data is required), or by other notions of 23869:

Center for Human-Compatible Artificial Intelligence

18524: 17866:"Posthuman Rights: Dimensions of Transhuman Worlds" 17615: 17061: 16961:"How Google Plans to Solve Artificial Intelligence" 16393:(1999). "Developments in Artificial Intelligence". 13559: 13119:(3rd ed.). New Delhi: Tata McGraw Hill India. 13046: 12621: 12276: 12099: 11944: 11363: 11357: 10564: 10394: 10374: 10248: 10030: 9611: 9374:"How to Stop Your Data From Being Used to Train AI" 9076:"Why agents are the next frontier of generative AI" 8219:"AI speeds up drug design for Parkinson's ten-fold" 7618: 7616: 7388: 7198: 7193: 7036: 6766: 6727: 6611: 6597:Modern statistical and deep learning approaches to 6579: 6420: 5916: 5663: 5661: 3976: 692:or incomplete information, employing concepts from 17531: 16845:"Annotated History of Modern AI and Deep Learning" 16423:IEEE Transactions on Autonomous Mental Development 16140: 14492: 14181: 13570:IEEE Transactions on Autonomous Mental Development 13186: 13148: 12609: 12252: 10120: 9740: 9722: 9612:Halper, Evan; O'Donovan, Caroline (21 June 2024). 9501: 9477: 8898:"A Cheat Sheet to AI Buzzwords and Their Meanings" 8343: 8146: 7930: 7428: 6818: 6364: 6127:places abduction under "default reasoning". Luger 5619: 5617: 4184:Finding a provably correct or optimal solution is 3561:engineers, domain experts, and delivery managers. 2406:In March 2023, 58% of U.S. adults had heard about 1179:(the number of places to search) quickly grows to 18203:, vol. 327, no. 4 (October 2022), pp. 42–45. 18107: 17653: 16464: 15568:"How We Analyzed the COMPAS Recidivism Algorithm" 14572:"Will robots create more jobs than they destroy?" 13826:"artificial intelligence is a tool, not a threat" 13551:Anderson, Michael; Anderson, Susan Leigh (2011). 13139: 12552: 12499: 12141:"OpenAI Releases GPT-3, The Largest Model So Far" 12071: 11874: 11315: 10895: 9810: 9103:"Reshaping Business With Artificial Intelligence" 8895: 8730:. Washington, DC: Congressional Research Service. 8345:"Computer Wins on 'Jeopardy!': Trivial, It's Not" 8053: 7738: 7736: 7652: 7406: 7366: 7348: 7216: 7123: 7082: 7050: 7026: 6916: 6876: 6846: 6808: 6544: 6457: 6354: 6116: 5997: 5987: 5870: 5801: 5799: 5797: 5784: 5759: 5724: 5506: 5476: 4854:proved to be inefficient for capturing knowledge. 4831: 4804: 4376:) may provide another moral basis for AI rights. 3413: 1848:Programming languages for artificial intelligence 24911: 23909:Leverhulme Centre for the Future of Intelligence 18342:Schulz, Hannes; Behnke, Sven (1 November 2012). 17986:, "A Murder Mystery Puzzle: The literary puzzle 17159:Robotics: The Marriage of Computers and Machines 16104: 16065:, p. 51(3) Industrial Law Journal 511–559, 15085:. Vol. 2. Pergamon Press. pp. 359–366. 14570:Ford, Martin; Colvin, Geoff (6 September 2015). 13550: 12083: 11182: 10889: 10812:"How Not to Be Stupid About AI, With Yann LeCun" 9825: 9267: 8404:Brown, Noam; Sandholm, Tuomas (30 August 2019). 8105: 7966:. MIT Sloan Teaching & Learning Technologies 7633: 7613: 7006: 6336: 5658: 5571: 5569: 4795: 4793: 2829: 2699:Environmental impacts of artificial intelligence 2474: 2357:, coordination and deconfliction of distributed 1834:GPT models can process different types of data ( 1604:There are many kinds of classifiers in use. The 1264:Distributed search processes can coordinate via 983:Modern deep learning techniques for NLP include 679: 17091:Affective Computing and Intelligent Interaction 16572:"Microsoft's Bill Gates insists AI is a threat" 15416:"The Challenge of Being Human in the Age of AI" 15160: 14306: 13620: 12838:"Experts Don't Think Robots Should Have Rights" 12169: 11697: 11695: 11311: 11307: 8593:openai.com, May 31, 2023. Retrieved 2024-08-07. 8282:Grant, Eugene F.; Lardner, Rex (25 July 1952). 7108: 7060: 6886: 5614: 5543: 5541: 4686: – Software to detect AI-generated content 3765:and ongoing pressure from the U.S. Congress to 3549:social values, justice, and the public interest 3058: 2778:YouTube § Moderation and offensive content 2709:Electricity 2024, Analysis and Forecast to 2026 2202:, which could be trained to play chess, Go, or 972:" (due to the common sense knowledge problem). 759: 23904:Institute for Ethics and Emerging Technologies 17937:, Princeton University Press, 2023, 333 pp.), 17660:International Journal of Public Administration 16952:The Shape of Automation for Men and Management 15197: 14837: 14418: 13957:– via Victoria University of Wellington. 13290: 13262:Computational Intelligence: A Logical Approach 13115:; Knight, Kevin; Nair, Shivashankar B (2010). 12785:"What leaders need to know about robot rights" 12453: 11237: 11142:Floridi, Luciano; Cowls, Josh (23 June 2019). 9966: 9012: 8863:Griffith, Erin; Metz, Cade (27 January 2023). 7733: 7639:Gradient calculation in computational graphs, 6912: 6521: 5835: 5794: 5418: 4722: – Algorithm exhibiting emergent behavior 4612:(1986) are less prominent in popular culture. 4064: 3806:. However, beginning with the collapse of the 1312:such as "and", "or", "not" and "implies") and 1015:test, and many other real-world applications. 913: 24606: 24141: 24088:Superintelligence: Paths, Dangers, Strategies 24068:Open letter on artificial intelligence (2015) 23724: 23012: 22584: 21588:Note: This template roughly follows the 2012 21564: 20640: 20318: 19443: 18769: 18661: 16391:NRC (United States National Research Council) 16241: 16198: 14997: 14660: 13791:Superintelligence: Paths, Dangers, Strategies 13219: 13075: 12955: 12931: 12896: 12676: 12657: 12651: 12579: 12533: 12465: 12409: 12246: 12126: 12093: 12040: 12020: 12008: 11992: 11902: 11870: 11854: 11818: 11762: 11750: 11726: 11682: 11617: 10777: 10699: 10582: 10554: 10514: 10227: 10215: 10200: 10090: 9995: 9958: 9946: 9894: 9867: 9309: 9297: 9249: 9047: 8815:. Executive Department, State of California. 8724:Artificial Intelligence and National Security 8403: 8037:"7 AI Programming Languages You Need to Know" 7855: 7830: 7813: 7777: 7754: 7746: 7727: 7711: 7695: 7672: 7648: 7623: 7603: 7563: 7535: 7491: 7474: 7442: 7398: 7358: 7342: 7322: 7314: 7306: 7298: 7280: 7260: 7240: 7208: 7189: 7147: 7115: 7102: 7074: 7046: 7022: 6994: 6964: 6952: 6938: 6932: 6904: 6868: 6840: 6828: 6800: 6721: 6697: 6685: 6673: 6657: 6629: 6602: 6573: 6561: 6536: 6517: 6477: 6473: 6453: 6437: 6433: 6410: 6402: 6398: 6346: 6330: 6314: 6298: 6282: 6274: 6261: 6248: 6232: 6212: 6196: 6156: 6108: 6061: 6020: 5979: 5946: 5898: 5862: 5813: 5776: 5747: 5743: 5715: 5672: 5640: 5600: 5566: 5560: 5519: 5500: 5470: 5387: 4827: 4822: 4820: 4800: 4790: 4773: – Computer composed of organic material 4089: 3610:Global Partnership on Artificial Intelligence 3467:for developing provably beneficial machines. 3199: 2030:). The deployment of AI may be overseen by a 1631: 1450:Probabilistic methods for uncertain reasoning 1261:only the fittest to survive each generation. 857:There are several kinds of machine learning. 744:(what we know about what other people know); 408: 24156:Subfields of and cyberneticians involved in 20654: 20332: 18341: 18030:, 20 November 2023, pp. 54–59. "If by ' 17935:Free Agents: How Evolution Gave Us Free Will 17526: 17434:"AI is entering an era of corporate control" 16991: 15561: 14013: 13984: 13301:(2nd ed.). Cambridge University Press. 12881: 11692: 11141: 10725: 10502: 10266: 9918: 9527:"Where the battle to dominate AI may be won" 9019:(3rd ed.). Cambridge University Press. 8862: 8281: 7207:Stochastic methods for uncertain reasoning: 6967:"Optimization Algorithms in Neural Networks" 6606: 5886: 5839: 5538: 5494: 5087:Max Planck Institute for Intelligent Systems 4504:" as far back as 1863, and expanded upon by 2631:" file. In 2023, leading authors (including 2608:. Since 2016, some privacy experts, such as 1668:Learning algorithms for neural networks use 1577:Classifiers and statistical learning methods 1250:are commonly used to train neural networks. 18638:Articles related to Artificial intelligence 16839: 16789: 16760: 16352:"Artificial Intelligence Prepares for 2001" 16282: 16173: 15340: 15135: 14624:Technological Forecasting and Social Change 14621: 14249:Foundations and Trends in Signal Processing 14046:"Facing up to the problem of consciousness" 13647: 13625:. Cheltenham, UK: Edward Elgar Publishing. 13473: 12985: 12401: 11465: 11244:International Journal of Ethics and Systems 10835:Arguments that AI is not an imminent risk: 10751: 10458: 10390: 10362: 10267:Buckley, Chris; Mozur, Paul (22 May 2019). 9417: 7911: 7899: 7882: 7870: 7762: 7497: 7182: 6761: 5489: 4728: – Gender biases in digital technology 4242:does not know whether a machine can have a 3206:Workplace impact of artificial intelligence 2991:, in which there are a large amount of non- 2648: 1838:) such as images, videos, sound, and text. 1711:before the network can identify an object. 968:unless restricted to small domains called " 707: 659:in the future, prompting discussions about 24613: 24599: 24148: 24134: 23731: 23717: 23019: 23005: 22979: 22591: 22577: 21571: 21557: 20647: 20633: 20325: 20311: 19450: 19436: 18776: 18762: 18668: 18654: 18383:Serenko, Alexander; Michael Dohan (2011). 18177: 17495:"Chatbots Have Entered the Uncanny Valley" 17115: 17020: 16199:Müller, Vincent C.; Bostrom, Nick (2014). 15688:Artificial Intelligence: a paper symposium 15535:"The changing science of machine learning" 14893:Grant, Nico; Hill, Kashmir (22 May 2023). 14569: 13412:(2nd ed.), Natick, MA: A. K. Peters, 13230:Artificial Intelligence: A Modern Approach 13086:Artificial Intelligence: A Modern Approach 12211:, Under "The Argument from Consciousness". 12036: 11630: 11628: 11626: 10803: 10347: 9775: 9503:"Big tech and the pursuit of AI dominance" 9051:Artificial Intelligence: A Modern Approach 8926: 8889: 8602: 7133: 6965:Singh Chauhan, Nagesh (18 December 2020). 6382: 4817: 4779: – Erroneous material generated by AI 4582:, the murderous computer in charge of the 4224:Machine consciousness, sentience, and mind 4173: 3927:became a serious field of academic study. 3115:Convention on Certain Conventional Weapons 2154:, by a significant margin. In March 2016, 1793:reinforcement learning from human feedback 1137: 415: 401: 22598: 20106: 20069:Relationship between religion and science 19457: 18174:, vol. 330, no. 6 (June 2024), pp. 80–81. 18082: 17958: 17881: 17775: 17718: 17299: 16806: 16631: 16569: 16540: 16401: 16307: 16129:Computation: Finite and Infinite Machines 16109:. 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Retrieved 2024-08-07. 8608: 8258: 8180: 8123: 8079: 7984: 7924: 7751:Goodfellow, Bengio & Courville (2016) 7092: 6144: 6131:places this under "uncertain reasoning"). 5676: 5592: 5548: 5523: 4863:"Rational agent" is general term used in 4684:Artificial intelligence content detection 3853:", including neural network research, by 2612:, have begun to view privacy in terms of 2364:In November 2023, US Vice President 1687:the signal passes in only one direction. 30:"AI" redirects here. For other uses, see 23874:Centre for the Study of Existential Risk 20581:No free lunch in search and optimization 18206: 18038:, especially smutty ones." (p. 59.) 17639: 17349: 17130: 16958: 15990: 15965: 15953: 15812:Madrigal, Alexis C. (27 February 2015). 15811: 15508: 15440: 15242: 14764:. Cambridge, Mass.: MIT Press. pp. 14594: 14368: 14351: 14040: 13987:IEEE Computational Intelligence Magazine 13961: 13919: 13621:Barfield, Woodrow; Pagallo, Ugo (2018). 13596: 13521: 13425: 13189:Artificial Intelligence: A New Synthesis 13040: 13028: 13016: 12951: 12904: 12591: 12541: 12404:, p. 116) Historical significance: 12270: 12065: 12057: 11890: 11774: 11634: 11477: 11412: 11060: 10844: 10783: 10474: 10024: 9763: 9285: 9237: 8856: 8315: 8147:Jumper, J; Evans, R; Pritzel, A (2021). 8008: 7996: 7627: 7607: 7587: 7573: 7567: 7539: 7454: 7422: 7382: 6641: 6172: 5831: 5719: 5688: 5652: 5608: 5599:, pp. 161–162, 197–203, 211, 240), 5575:Funding initiatives in the early 1980s: 5485: 4698: – Automation of business processes 4622:in many stories, most notably with the " 4527: 4359: 4328:Computationalism is the position in the 4200: 4009: 3725:The field of AI research was founded at 3590: 3390:In 2023, many leading AI experts issued 2653:The commercial AI scene is dominated by 2535: 2382: 1718: 1635: 1557: 1453: 1304:. Formal logic comes in two main forms: 1212: 1072: 1038:is the ability to analyze visual input. 711: 36:Artificial intelligence (disambiguation) 23914:Machine Intelligence Research Institute 22686:Carbon nanotube field-effect transistor 22644:Applications of artificial intelligence 18533:. Brussels: European Commission. 2020. 18211:. New York: Farrar, Straus and Giroux. 17517: 17492: 17431: 17406: 17381: 17324: 17116:Taylor, Josh; Hern, Alex (2 May 2023). 16740: 16695: 16663: 16606: 16594: 16413: 16346: 16270: 16135: 16131:, Englewood Cliffs, N.J.: Prentice-Hall 16029: 15957:(2007), "From Here to Human-Level AI", 15836: 15532: 15390: 15096:The Stanford Encyclopedia of Philosophy 14905: 14782: 14755: 14662:"From not working to neural networking" 14525: 14490: 14394: 14331: 14307:DiFeliciantonio, Chase (3 April 2023). 14282: 14231: 13798: 13784: 13382: 13336:Introduction to Artificial Intelligence 13181: 12947: 12756: 12752: 12750: 12727: 12723: 12721: 12719: 12684: 12603: 12567: 12529: 12525: 12493: 12481: 12457: 12449: 12425: 12376: 12296:"What Is Artificial Intelligence (AI)?" 12181: 12004: 11981: 11938: 11914: 11886: 11878: 11806: 11790: 11738: 11718: 11686: 11678: 11623: 11453: 11401:Altman, Brockman & Sutskever (2023) 11345: 11034: 11015: 10963: 10925: 10913: 10693: 10607: 10558: 10550: 10538: 10526: 10485: 10470: 10243: 10138: 9859: 9843: 9786: 9784: 9592: 9452: 9405: 9333: 9048:Russell, Stuart; Norvig, Peter (2020). 8746: 8721:Congressional Research Service (2019). 8716: 8714: 8712: 8623: 8561: 8341: 8054:Davenport, T; Kalakota, R (June 2019). 8034: 7964:"AI Writing and Content Creation Tools" 7802:Ciresan, Meier & Schmidhuber (2012) 7676: 7656: 7450: 7410: 7370: 7220: 7127: 7086: 7054: 7030: 6880: 6812: 6772: 6753: 6733: 6661: 6617: 6585: 6358: 6184: 6152: 6148: 6120: 6028: 5991: 5958:Representing categories and relations: 5935:Bertini, Del Bimbo & Torniai (2006) 5922: 5874: 5788: 5763: 5711: 5680: 5636: 5596: 5556: 5552: 5481: 5111:' definition, and includes things like 4839: 4812: 4777:Hallucination (artificial intelligence) 4767: – Form of artificial intelligence 4144:attempts to bridge the two approaches. 3281:First, AI does not require human-like " 3176:. It lowers the cost and difficulty of 2968: 2901:is a commercial program widely used by 1898:Applications of artificial intelligence 1113: 995:(a deep learning architecture using an 14: 24912: 24728:Electrical and electronics engineering 24713:Developmental and reproductive biology 22835:Differential technological development 22288:Knowledge representation and reasoning 18783: 18190:from the original on 12 February 2016. 17241: 17208: 17088: 16905: 16851: 16720: 16491: 16123: 15903: 15666:Building Large Knowledge-Based Systems 15038: 14981:Artificial Intelligence: The Very Idea 14960: 14948:from the original on 25 September 2021 14930: 14684: 14239: 14179: 14014:Cellan-Jones, Rory (2 December 2014). 13949:from the original on 19 September 2008 13931: 13884: 13836: 13823: 13052: 12976: 12672: 12668: 12639: 12627: 12537: 12433: 12429: 12282: 12208: 12196: 12110: 11953: 11802: 11710: 11376: 11319: 11126:"AI Ethics and Governance in Practice" 10989: 10836: 10731: 10705: 10648: 10599: 10570: 10432: 10317: 10254: 10036: 9790: 9753:from the original on 22 February 2024. 9710:Hiller, Jennifer (20 September 2024). 9709: 9690: 9671: 9514:from the original on 29 December 2023. 9113:from the original on 13 February 2024. 9013:Poole, David; Mackworth, Alan (2023). 8742: 8740: 8484: 8377: 8221:. Cambridge University. 17 April 2024. 7789: 7681:Hornik, Stinchcombe & White (1989) 6757: 6370: 5911:Kuperman, Reichley & Bailey (2006) 5412: 4633:, and thus to suffer. This appears in 4532:The word "robot" itself was coined by 4142:neuro-symbolic artificial intelligence 2844:Machine learning applications will be 2037: 1864:software had replaced previously used 1068: 454:that develops and studies methods and 24594: 24129: 23712: 23426:Simultaneous localization and mapping 23000: 22572: 22313:Philosophy of artificial intelligence 21552: 20628: 20306: 19431: 19377:Philosophy of artificial intelligence 18757: 18649: 18636: 18540:from the original on 20 February 2020 17929:, "The Fate of Free Will" (review of 17890: 17860: 17603:from the original on 4 September 2013 17456: 17361: 17188: 16971: 16949: 16501:, Perennial Modern Classics, Harper, 16316: 16237:from the original on 15 January 2016. 15861: 15695:Lipartito, Kenneth (6 January 2011), 15378:from the original on 28 February 2019 15089: 14783:Goldman, Sharon (14 September 2022). 14730: 14706:Geist, Edward Moore (9 August 2015). 14705: 14672:from the original on 31 December 2016 14550: 14454: 14194:from the original on 23 November 2016 13763:from the original on 20 December 2019 13265:. New York: Oxford University Press. 12980: 12920: 12861: 12835: 12696: 12615: 12469: 12258: 12138: 12032: 11786: 11701:Turing's original publication of the 11592:. gov.uk. 21 May 2024. Archived from 11489: 11079: 10840: 10757: 10603: 10174: 10126: 9728: 9630: 9537:from the original on 13 January 2024. 9465:from the original on 10 January 2024. 8986: 8908:from the original on 17 November 2023 8822:from the original on 21 February 2024 8406:"Superhuman AI for multiplayer poker" 8316:Anderson, Mark Robert (11 May 2017). 7936: 7012: 5844:Kahneman, Slovic & Tversky (1982) 5730: 5462: 5460: 5458: 4416:Superintelligence and the singularity 4230:Philosophy of artificial intelligence 3972:Philosophy of artificial intelligence 3911:(including curated datasets, such as 3579:Regulation of artificial intelligence 3569:reason, and autonomous capabilities. 2546:Artificial intelligence and copyright 2067:. This is particularly important for 2044:Artificial intelligence in healthcare 1882:general-purpose programming languages 1486:. These tools include models such as 1360:). Proofs can be structured as proof 1153: 665:safety and benefits of the technology 22805:Three-dimensional integrated circuit 21632:Energy consumption (Green computing) 21578: 21485:Generative adversarial network (GAN) 20576:Interactive evolutionary computation 20368:Interactive evolutionary computation 20363:Human-based evolutionary computation 20358:Evolutionary multimodal optimization 18603: 18512:from the original on 15 October 2019 18489:, Noam Shazeer, Niki Parmar et al. " 17891:Frank, Michael (22 September 2023). 17745:from the original on 19 October 2013 17706: 17155: 16708:from the original on 30 October 2015 16652: 16640:from the original on 8 December 2019 16582:from the original on 29 January 2015 16570:Rawlinson, Kevin (29 January 2015). 16186:from the original on 12 January 2018 16093:from the original on 31 January 2021 15979:from the original on 4 December 2022 15849:from the original on 14 January 2018 15824:from the original on 4 February 2016 15795: 15744:from the original on 14 January 2018 15731: 15648:from the original on 30 October 2015 15453:from the original on 19 October 2021 15441:Kobielus, James (27 November 2019). 15428:from the original on 4 November 2021 15398:from the original on 17 October 2014 15365: 15138:"Robots and Artificial Intelligence" 15114: 15059:from the original on 30 October 2015 14802: 14743:from the original on 30 October 2015 14718:from the original on 30 October 2015 14219:from the original on 12 January 2019 14028:from the original on 30 October 2015 13462:AI & ML in Fusion, video lecture 13315:from the original on 7 December 2017 12912: 12801: 12747: 12716: 12505: 12077: 11707:Computing machinery and intelligence 11639:. Oxford, England: Clarendon Press. 11548:from the original on 1 November 2023 11302:Regulation of AI to mitigate risks: 11189:Medicine, Health Care and Philosophy 11016:Brodsky, Sascha (19 December 2023). 10990:Heaven, Will Douglas (12 May 2023). 10901: 10809: 10406: 10386: 10328:51(3) Industrial Law Journal 511–559 9863: 9819: 9781: 9652: 9547: 9524: 9490:from the original on 5 January 2024. 9453:Hammond, George (27 December 2023). 8877:from the original on 9 December 2023 8709: 8617: 7570:, p. 187) (k-nearest neighbor) 6749: 5648: 5268:approaches to AI were championed by 4885:Computing Machinery and Intelligence 4836:Poole, Mackworth & Goebel (1998) 4809:Poole, Mackworth & Goebel (1998) 4783: 4658:Do Androids Dream of Electric Sheep? 4074:networks"). This approach is mostly 3716:Computing Machinery and Intelligence 2231:are used. In contrast, LLMs such as 2194:developed increasingly generalistic 1880:were used in early AI research, but 1852:Hardware for artificial intelligence 1806:Current models and services include 1764:used for benchmark testing, such as 1707:, where a local set of neurons must 892:for all of these types of learning. 772:, the agent has a specific goal. In 22924:Future-oriented technology analysis 22664:Progress in artificial intelligence 22318:Distributed artificial intelligence 21590:ACM Computing Classification System 18615:Stanford Encyclopedia of Philosophy 18606:"Logic and Artificial Intelligence" 18596:Internet Encyclopedia of Philosophy 18413:from the original on 4 October 2013 18300:, 20 November 2023, pp. 20–26. 17694:from the original on 18 August 2020 17640:Williams, Rhiannon (28 June 2023), 17407:Vincent, James (15 November 2022). 17131:Thompson, Derek (23 January 2014). 16696:Sainato, Michael (19 August 2015). 16632:Robitzski, Dan (5 September 2018). 16452:from the original on 3 October 2018 16389: 16372:from the original on 17 August 2020 16174:Morgenstern, Michael (9 May 2015). 15868:, Dartmouth College, archived from 15727:from the original on 9 October 2022 15635: 15591:Laskowski, Nicole (November 2023). 14876: 14206: 14110:: Machine learning and human values 13891:European Journal of Risk Regulation 13880:from the original on 9 August 2007. 13824:Brooks, Rodney (10 November 2014). 13155:(5th ed.). Benjamin/Cummings. 12400:Physical symbol system hypothesis: 12061: 11842: 11246:. ahead-of-print (ahead-of-print). 10848: 10784:McMorrow, Ryan (19 December 2023). 10612: 10375:Arntz, Gregory & Zierahn (2016) 9831: 9371: 9273: 8737: 7447:Poole, Mackworth & Goebel (1998 7403:Poole, Mackworth & Goebel (1998 7363:Poole, Mackworth & Goebel (1998 7245:Poole, Mackworth & Goebel (1998 7213:Poole, Mackworth & Goebel (1998 7120:Poole, Mackworth & Goebel (1998 7079:Poole, Mackworth & Goebel (1998 6909:Poole, Mackworth & Goebel (1998 6895:or informed searches (e.g., greedy 6873:Poole, Mackworth & Goebel (1998 6805:Poole, Mackworth & Goebel (1998 6541:Poole, Mackworth & Goebel (1998 6351:Poole, Mackworth & Goebel (1998 6113:Poole, Mackworth & Goebel (1998 6066:Poole, Mackworth & Goebel (1998 6045:Poole, Mackworth & Goebel (1998 6025:Poole, Mackworth & Goebel (1998 5984:Poole, Mackworth & Goebel (1998 5867:Poole, Mackworth & Goebel (1998 5781:Poole, Mackworth & Goebel (1998 5756:Poole, Mackworth & Goebel (1998 5684: 5644: 5604: 5527: 4735:Glossary of artificial intelligence 4726:Female gendering of AI technologies 4147: 3930:In the late teens and early 2020s, 3681:Timeline of artificial intelligence 3652:In November 2023, the first global 3524:tests projects in four main areas: 3259: 3045:generative pre-trained transformers 2963:Association for Computing Machinery 2491:AI applications for evacuation and 1777:Generative pre-trained transformers 1438:, including logic programming with 24: 24056:Statement on AI risk of extinction 21823:Integrated development environment 20614:Evolutionary Computation (journal) 18502:"Robots could demand legal rights" 18018:for such a purpose." 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Hoboken: Pearson. 12759:"AI Should Be Terrified of Humans" 12728:Thomson, Jonny (31 October 2022). 12151:from the original on 4 August 2020 12056:AI widely used in the late 1990s: 11061:Marshall, Matt (29 January 2024). 11035:Edwards, Benj (22 February 2024). 10630:from the original on 28 March 2023 10395:Arntz, Gregory & Zierahn (2016 9691:Halper, Evan (20 September 2024). 8952: 8773: 8657:eleuther.ai. 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Specialized 1628:are also used as classifiers. 1464:conditional probability tables 800:inverse reinforcement learning 580:, perception, and support for 13: 1: 24925:Computational fields of study 22951:Technology in science fiction 22101:Multimedia information system 22086:Geographic information system 22076:Enterprise information system 21665:Computer systems organization 21480:Variational autoencoder (VAE) 21440:Long short-term memory (LSTM) 20707:Computational learning theory 20482:Bacterial Colony Optimization 19234:Hard problem of consciousness 18310:aced a test but showed that 17709:"ChatGPT Is Already Obsolete" 17672:10.1080/01900692.2018.1498103 16864:Behavioral and Brain Sciences 16278:, vol. 16, pp. 9–17 16274:(1995), "Eyes on the Prize", 15308:10.1126/science.185.4157.1124 15175:10.1080/21582041.2018.1563803 14526:Edwards, Benj (17 May 2023). 13945:. Christchurch, New Zealand. 13871:10.1016/S0921-8890(05)80025-9 13555:. 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Various AI models, such as 2830:Algorithmic bias and fairness 2475:Other industry-specific tasks 1701:Convolutional neural networks 1129: 1108:multimodal sentiment analysis 1018: 896:Computational learning theory 680:Reasoning and problem-solving 434:), in its broadest sense, is 23884:Future of Humanity Institute 23026: 22460:Computational social science 22048:Theoretical computer science 21861:Software development process 21637:Electronic design automation 21622:Very Large Scale Integration 21460:Convolutional neural network 17940:The New York Review of Books 17707:Wong, Matteo (19 May 2023), 17578:10.1126/science.291.5504.599 17062:Stanford University (2023). 16954:, New York: Harper & Row 16857:"Minds, Brains and Programs" 16817:10.1016/j.neunet.2014.09.003 16533:10.1016/j.inffus.2017.02.003 16382:Presidential Address to the 16256:10.1016/j.imavis.2007.08.013 16147:. 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Artificial Intelligence 4433:reprogram and improve itself 4316:Computational theory of mind 4207:Weak artificial intelligence 3124:AI tools make it easier for 3059:Bad actors and weaponized AI 2741:announced an agreement with 2312:to define mathematic tasks. 2162:in a match with Go champion 2142:, defeated the two greatest 2106:Game artificial intelligence 1375:are labelled by premises or 925:. Specific problems include 760:Planning and decision-making 7: 24101:Artificial Intelligence Act 24095:Do You Trust This Computer? 23436:Vision-guided robot systems 22283:Natural language processing 22071:Information storage systems 21455:Multilayer perceptron (MLP) 20477:Particle swarm optimization 20421:Gene expression programming 19811:Hypothetico-deductive model 19786:Deductive-nomological model 19771:Constructivist epistemology 18348:KI – Künstliche Intelligenz 18000:natural-language processing 17782:The Advent of the Algorithm 17280:Nature Machine Intelligence 17162:. 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(2004). 11358:Stanford University (2023) 11252:10.1108/IJOES-05-2023-0107 11201:10.1007/s11019-020-09948-1 10649:Pittis, Don (4 May 2023). 10091:Russell & Norvig (2021 9996:Russell & Norvig (2021 9959:Russell & Norvig (2021 9947:Russell & Norvig (2021 9919:Larson & Angwin (2016) 9868:Russell & Norvig (2021 9548:Metz, Cade (5 July 2023). 9479:"The Future of AI Is GOMA" 9352:Cornell University Library 9205:Automation in Construction 9178:10.1007/s10694-021-01157-3 8541:10.1038/s41586-021-04357-7 8251:10.1038/s41589-024-01580-x 8173:10.1038/s41586-021-03819-2 8125:10.3389/fsens.2023.1294721 7950:"Explained: Generative AI" 7778:Russell & Norvig (2021 7747:Russell & Norvig (2021 7728:Russell & Norvig (2021 7712:Russell & Norvig (2021 7696:Russell & Norvig (2021 7673:Russell & Norvig (2021 7649:Russell & Norvig (2021 7624:Russell & Norvig (2021 7604:Russell & Norvig (2021 7564:Russell & Norvig (2021 7536:Russell & Norvig (2021 7492:Russell & Norvig (2021 7475:Russell & Norvig (2021 7443:Russell & Norvig (2021 7399:Russell & Norvig (2021 7359:Russell & Norvig (2021 7343:Russell & Norvig (2021 7323:Russell & Norvig (2021 7315:Russell & Norvig (2021 7307:Russell & Norvig (2021 7299:Russell & Norvig (2021 7281:Russell & Norvig (2021 7261:Russell & Norvig (2021 7241:Russell & Norvig (2021 7209:Russell & Norvig (2021 7194:Scientific American (1999) 7190:Russell & Norvig (2021 7148:Russell & Norvig (2021 7116:Russell & Norvig (2021 7103:Russell & Norvig (2021 7075:Russell & Norvig (2021 7047:Russell & Norvig (2021 7023:Russell & Norvig (2021 6995:Russell & Norvig (2021 6953:Russell & Norvig (2021 6933:Russell & Norvig (2021 6905:Russell & Norvig (2021 6869:Russell & Norvig (2021 6829:Russell & Norvig (2021 6801:Russell & Norvig (2021 6658:Russell & Norvig (2021 6607:Cambria & White (2014) 6603:Russell & Norvig (2021 6562:Russell & Norvig (2021 6537:Russell & Norvig (2021 6518:Russell & Norvig (2021 6474:Russell & Norvig (2021 6454:Russell & Norvig (2021 6438:Russell & Norvig (2021 6434:Russell & Norvig (2021 6411:Russell & Norvig (2021 6403:Russell & Norvig (2021 6399:Russell & Norvig (2021 6347:Russell & Norvig (2021 6331:Russell & Norvig (2021 6315:Russell & Norvig (2021 6299:Russell & Norvig (2021 6283:Russell & Norvig (2021 6275:Russell & Norvig (2021 6262:Russell & Norvig (2021 6249:Russell & Norvig (2021 6233:Russell & Norvig (2021 6213:Russell & Norvig (2021 6157:Russell & Norvig (2021 6109:Russell & Norvig (2021 6062:Russell & Norvig (2021 6021:Russell & Norvig (2021 5980:Russell & Norvig (2021 5887:Smoliar & Zhang (1994) 5863:Russell & Norvig (2021 5840:Wason & Shapiro (1966) 5814:Russell & Norvig (2021 5777:Russell & Norvig (2021 5748:Russell & Norvig (2021 5744:Russell & Norvig (2021 5716:Russell & Norvig (2021 5673:Russell & Norvig (2021 5641:Russell & Norvig (2021 5601:Russell & Norvig (2021 5561:Russell & Norvig (2021 5520:Russell & Norvig (2021 5501:Russell & Norvig (2021 5471:Russell & Norvig (2021 4759:Robotic process automation 4741:Intelligence amplification 4708:Computational intelligence 4557:in these works began with 4521: 4313: 4297:is easy to explain, human 4274: 4227: 4204: 4177: 4151: 4090:Symbolic AI and its limits 3980: 3969: 3942:, beat the world champion 3785:artificial neural networks 3678: 3672: 3668: 3576: 3417: 3263: 3210:Technological unemployment 3203: 3200:Technological unemployment 3186:facial recognition systems 3062: 2972: 2833: 2775: 2696: 2539: 2511: 2376: 2338: 2318: 2103: 2041: 1895: 1845: 1656:, which loosely model the 1632:Artificial neural networks 1173:Simple exhaustive searches 1097:human–computer interaction 1089:feeling, emotion, and mood 890:artificial neural networks 602:artificial neural networks 460:perceive their environment 171:Hybrid intelligent systems 93:Recursive self-improvement 75: 29: 24633: 24290: 24164: 24109: 24048: 23927: 23854:Alignment Research Center 23846: 23838:Technological singularity 23788:Effective accelerationism 23750: 23674: 23644:Workplace robotics safety 23626: 23520: 23444: 23407: 23362: 23260: 23104: 23093: 23034: 22974: 22939:Technological singularity 22899:Technological convergence 22817: 22613: 22606: 22528: 22465:Computational engineering 22440:Computational mathematics 22417: 22364: 22326: 22273: 22235: 22197: 22139: 22056: 22002: 21964: 21909: 21846: 21779: 21743: 21700: 21664: 21597: 21586: 21498: 21412: 21356: 21285: 21218: 21090: 20990: 20983: 20937: 20901: 20864:Artificial neural network 20844: 20720: 20687:Automatic differentiation 20660: 20604: 20523: 20490: 20449: 20376: 20340: 20265: 20097: 19999: 19929: 19872:Semantic view of theories 19791:Epistemological anarchism 19743: 19728:dependent and independent 19465: 19397: 19364: 19191: 19061: 18956:Gottfried Wilhelm Leibniz 18946:David Lewis (philosopher) 18791: 18683: 18643: 18591:"Artificial Intelligence" 18491:Attention is all you need 18404:10.1016/j.joi.2011.06.002 18360:10.1007/s13218-012-0198-z 17984:Hughes-Castleberry, Kenna 17728:Global Catastrophic Risks 17518:Wallach, Wendell (2010). 16915:. New York: Basic Books. 16876:10.1017/S0140525X00005756 16673:. United States: Viking. 16435:10.1109/tamd.2009.2039057 16397:. National Academy Press. 16296:Communications of the ACM 16044:10.1017/S0269888905000408 16015:10.1007/s10676-007-9138-2 15554:10.1007/s10994-011-5242-y 14555:. New York: Grove Press. 14461:Darwin among the Machines 14240:Deng, L.; Yu, D. (2014). 14155:10.1109/cvpr.2012.6248110 13939:. Letters to the Editor. 13885:Buiten, Miriam C (2019). 13582:10.1109/tamd.2009.2021702 13536:10.1007/s00146-007-0094-5 12893:technological singularity 11618:Russell & Norvig 2021 11161:10.1162/99608f92.8cd550d1 10515:Russell & Norvig 2021 10391:Frey & Osborne (2017) 9418:Alter & Harris (2023) 9054:(4th ed.). Pearson. 8810:"Executive Order N-12-23" 8681:7 Best AI for Math Tools. 8072:10.7861/futurehosp.6-2-94 7708:Recurrent neural networks 7645:automatic differentiation 7319:Dynamic Bayesian networks 7273:Markov decision processes 6225:Automated decision making 5490:Beal & Winston (2009) 5072:) and Sam Corbett-Davis ( 5068:), Cynthia Chouldechova ( 5064:), Sendhil Mullainathan ( 4914:conditionally independent 4502:Darwin among the Machines 4410: 3901:graphics processing units 3861:successfully showed that 3800:fifth generation computer 3455:Other approaches include 3295:paperclip factory manager 3289:argued that if one gives 3126:authoritarian governments 3083:authoritarian governments 2507: 2445: 2136:question answering system 2048:The application of AI in 1888:have become predominant. 1858:graphics processing units 1689:Recurrent neural networks 1538:dynamic Bayesian networks 1488:Markov decision processes 1442:, are designed to handle 1234:mathematical optimization 991:encoding their meaning), 966:word-sense disambiguation 774:automated decision-making 594:mathematical optimization 24380:Charles Geoffrey Vickers 24267:Second-order cybernetics 23889:Future of Life Institute 23808:Instrumental convergence 22711:Holographic data storage 22475:Computational healthcare 22470:Differentiable computing 22389:Graphics processing unit 21808:Domain-specific language 21677:Computational complexity 20692:Neuromorphic engineering 20655:Differentiable computing 20406:Evolutionary programming 20353:Evolutionary data mining 20334:Evolutionary computation 19614:Intertheoretic reduction 19603:Ignoramus et ignorabimus 19580:Functional contextualism 17536:. In Foss, B. M. (ed.). 17368:Analytics India Magazine 17228:10.1093/mind/LIX.236.433 16176:"Automation and anxiety" 15024:10.1109/msp.2012.2205597 14862:10.1609/aimag.v38i3.2741 14551:Fearn, Nicholas (2007). 14491:Edelson, Edward (1991). 14085:10.1017/CBO9780511975837 13999:10.1109/MCI.2014.2307227 13654:IEEE Intelligent Systems 13334:Ertel, Wolfgang (2017). 12402:Newell & Simon (1976 12145:Analytics India Magazine 11974:Lungarella et al. (2003) 11789:, p. 96) quoted in 10348:Ford & Colvin (2015) 9776:Taylor & Hern (2023) 7554:learning models such as 7467:Bayesian decision theory 7257:Information value theory 6991:Evolutionary computation 6295:Information value theory 5855:Knowledge representation 5577:Fifth Generation Project 5358:thinking (as opposed to 5276:and went by many names: 4304:know what red looks like 4234:Artificial consciousness 4027:Aeronautical engineering 3718:', which introduced the 3583:Regulation of algorithms 3065:Lethal autonomous weapon 2979:Algorithmic transparency 2952:anti-discrimination laws 2649:Dominance by tech giants 2158:won 4 out of 5 games of 2099: 2032:Chief automation officer 1563:Expectation–maximization 1484:information value theory 1302:knowledge representation 1287: 1255:evolutionary computation 900:computational complexity 837:, or it can be learned. 804:Information value theory 721:Knowledge representation 708:Knowledge representation 670: 645:transformer architecture 566:knowledge representation 458:that enable machines to 295:Artificial consciousness 27:Intelligence of machines 24920:Artificial intelligence 24658:Artificial intelligence 24242:Engineering cybernetics 24172:Artificial intelligence 23744:artificial intelligence 23492:Human–robot interaction 22904:Technological evolution 22877:Exploratory engineering 22706:3D optical data storage 22639:Artificial intelligence 22450:Computational chemistry 22384:Photograph manipulation 22275:Artificial intelligence 22091:Decision support system 21465:Residual neural network 20881:Artificial Intelligence 20536:Artificial intelligence 20462:Ant colony optimization 20099:Philosophers of science 19877:Scientific essentialism 19826:Model-dependent realism 19761:Constructive empiricism 19654:Evidence-based practice 19084:Eliminative materialism 18688:Artificial intelligence 18623:Artificial Intelligence 18579:Artificial intelligence 18392:Journal of Informetrics 17918:New York Times Magazine 17828:Oxford University Press 17493:Waddell, Kaveh (2018). 17247:. Paris: UNESCO. 2021. 16775:10.1023/A:1013298507114 16607:Roberts, Jacob (2016). 16324:The Wall Street Journal 16220:10.1145/2639475.2639478 15959:Artificial Intelligence 15515:The Singularity is Near 15421:The Wall Street Journal 15249:Thinking, Fast and Slow 15220:10.1126/science.aaa8415 14687:Science Fiction Studies 14404:. New York: MIT Press. 14401:What Computers Can't Do 14313:San Francisco Chronicle 14289:Consciousness Explained 14207:CNA (12 January 2019). 13117:Artificial Intelligence 12899:, pp. 1004–1005), 12520:, the historic debate: 12446:Dreyfus' critique of AI 11805:, p. 2) quoted in 11304:Berryhill et al. (2019) 9907:Grant & Hill (2023) 8747:Slyusar, Vadym (2019). 8430:10.1126/science.aay2400 8239:Nature Chemical Biology 7560:support vector machines 6436:, §19.2) (Definition), 6311:Markov decision process 6273:Uncertain preferences: 6101:closed world assumption 6015:(including solving the 5810:combinatorial explosion 5752:constraint satisfaction 5409:CNN.com (July 26, 2006) 4655:, as well as the novel 4606:(1951) and Bishop from 4174:Soft vs. hard computing 3432:Artificial moral agents 3107:kill an innocent person 2757:Inflation Reduction Act 2589:and a violation of the 2399:, often in response to 1866:central processing unit 1585:are functions that use 1278:ant colony optimization 1138:Search and optimization 898:can assess learners by 815:Markov decision process 604:, and methods based on 428:Artificial intelligence 166:Evolutionary algorithms 56:Artificial intelligence 18:Artificial Intelligence 24888:Structural engineering 24828:Mechanical engineering 24801:Western and South Asia 24565:Walter Bradford Cannon 24455:Ludwig von Bertalanffy 24310:Alfred Radcliffe-Brown 24257:Management cybernetics 24182:Biomedical cybernetics 24177:Biological cybernetics 23813:Intelligence explosion 22914:Technology forecasting 22909:Technological paradigm 22882:Proactionary principle 22800:Software-defined radio 22515:Educational technology 22346:Reinforcement learning 22096:Process control system 21994:Computational geometry 21984:Algorithmic efficiency 21979:Analysis of algorithms 21627:Systems on Chip (SoCs) 20531:Artificial development 20401:Differential evolution 20348:Evolutionary algorithm 20182:Alfred North Whitehead 20172:Charles Sanders Peirce 19336:Propositional attitude 19331:Problem of other minds 19239:Hypostatic abstraction 18314:cannot be measured by 18041:Johnston, John (2008) 17530:; Shapiro, D. (1966). 16414:Oudeyer, P-Y. (2010). 15664:; Guha, R. V. (1989). 15090:Horst, Steven (2005). 14464:. Allan Lane Science. 14139:. pp. 3642–3649. 13799:Bostrom, Nick (2015). 13602:McKinsey & Company 12889:Intelligence explosion 12170:DiFeliciantonio (2023) 11966:Developmental robotics 11570:. Reuters. 21 May 2024 8245:(5). Nature: 634–645. 7600:Naive Bayes classifier 7409:, pp. ~363–379), 6450:Reinforcement learning 6145:Lenat & Guha (1989 5877:, chpt. 17.1–17.4, 18) 5534:McCarthy et al. (1955) 5282:Developmental robotics 4620:Three Laws of Robotics 4588:spaceship, as well as 4543: 4441:intelligence explosion 4403:, which could lead to 4295:information processing 4015: 3995:Synthetic intelligence 3600: 3566:UK AI Safety Institute 3150:Recommendation systems 2961:(ACM FAccT 2022), the 2388: 2196:reinforcement learning 2086:structure of a protein 2075:development which use 1916:recommendation systems 1771: 1723: 1693:Long short term memory 1649: 1622:naive Bayes classifier 1618:support vector machine 1573: 1466: 1462:, with the associated 1226: 1081: 964:, had difficulty with 939:information extraction 878:reinforcement learning 717: 555:not labeled AI anymore 483:recommendation systems 67: 24753:Environmental science 24638:Aerospace engineering 24525:Anthony Stafford Beer 24360:Ernst von Glasersfeld 23768:AI capability control 23598:Starship Technologies 22840:Disruptive innovation 22600:Emerging technologies 22485:Electronic publishing 22455:Computational biology 22445:Computational physics 22341:Unsupervised learning 22255:Distributed computing 22131:Information retrieval 22038:Mathematical analysis 22028:Mathematical software 21911:Theory of computation 21876:Software construction 21866:Requirements analysis 21744:Software organization 21672:Computer architecture 21642:Hardware acceleration 21607:Printed circuit board 21420:Neural Turing machine 21008:Human image synthesis 20566:Fitness approximation 20551:Evolutionary robotics 20492:Metaheuristic methods 20281:Philosophy portal 20032:Hard and soft science 20027:Faith and rationality 19896:Scientific skepticism 19676:Scientific Revolution 19459:Philosophy of science 19407:Philosophers category 19311:Mental representation 19074:Biological naturalism 18961:Maurice Merleau-Ponty 18936:Frank Cameron Jackson 17719:Yudkowsky, E (2008), 17647:MIT Technology Review 17055:IRE Convention Record 16965:MIT Technology Review 16950:Simon, H. A. (1965), 16498:The Language Instinct 16309:10.1145/360018.360022 16059:McGaughey, E (2022), 15533:Langley, Pat (2011). 14880:(13 September 2022). 14428:. Oxford: Blackwell. 14292:. The Penguin Press. 14180:Clark, Jack (2015b). 14108:The Alignment Problem 13457:AI & ML in Fusion 13145:Stubblefield, William 12683:, pp. 443–445), 12468:, pp. 981–982), 12464:, pp. 211–239), 12460:, pp. 120–132), 12332:carnegieendowment.org 12301:Google Cloud Platform 12064:, pp. 216–222), 12007:, pp. 214–215), 11877:, pp. 227–331), 11873:, pp. 23, 292), 10996:MIT Technology Review 10002:, pp. 40, 80–81) 9973:, pp. 39–40, 65) 9856:Berdahl et al. (2023) 9601:. New York, New York. 9025:10.1017/9781009258227 7655:, pp. 467–474), 7449:, pp. 424–433), 7413:, chpt. 19.4 & 7) 7405:, pp. 361–381), 7365:, pp. 361–381), 7215:, pp. 345–395), 7176:10.1145/872734.806939 7081:, pp. 268–275), 7069:and features such as 6911:, pp. 132–147), 6875:, pp. 113–132), 6807:, pp. 113–163), 6520:, pp. 672–674), 6413:, pp. 846–860) ( 6405:, pp. 738–740) ( 6395:Unsupervised learning 6357:, pp. 385–542), 6353:, pp. 397–438), 6161:qualification problem 6151:, pp. 113–114), 6119:, pp. 335–363), 6027:, pp. 281–298), 5990:, pp. 248–258), 5986:, pp. 174–177), 5982:, §10.2 & 10.5), 5873:, pp. 227–243), 5859:knowledge engineering 5787:, pp. 333–381), 5783:, pp. 345–395), 5775:Uncertain reasoning: 5762:, chpt. 3, 4, 6, 8), 5758:, chpt. 2, 3, 7, 9), 5687:, pp. 214–216), 5683:, pp. 209–210), 5679:, pp. 430–435), 5647:, pp. 212–213), 5639:, pp. 115–117), 5607:, pp. 210–211), 5595:, pp. 426–441), 5551:, pp. 243–252), 5526:, pp. 111–136), 5293:Matteo Wong wrote in 5066:University of Chicago 4753:Organoid intelligence 4576:2001: A Space Odyssey 4531: 4405:large-scale suffering 4360:AI welfare and rights 4299:subjective experience 4201:Narrow vs. general AI 4013: 3909:large amounts of data 3857:and others. In 1990, 3692:theory of computation 3594: 3522:Alan Turing Institute 3152:can precisely target 2856:people (as it can in 2703:In January 2024, the 2540:Further information: 2536:Privacy and copyright 2386: 2198:models, such as with 2180:imperfect-information 2166:, becoming the first 1874:programming languages 1781:large language models 1722: 1639: 1561: 1457: 1387:from the premises or 1216: 1187:or never completes. " 1076: 952:Early work, based on 943:information retrieval 859:Unsupervised learning 754:knowledge acquisition 725:knowledge engineering 715: 616:. AI also draws upon 541:play and analysis in 66: 24950:Intelligence by type 24555:Valentin Braitenberg 24435:Jay Wright Forrester 23859:Center for AI Safety 23548:Energid Technologies 22887:Technological change 22830:Collingridge dilemma 22627:Ambient intelligence 22245:Concurrent computing 22217:Ubiquitous computing 22189:Application security 22184:Information security 22013:Discrete mathematics 21989:Randomized algorithm 21941:Computability theory 21919:Model of computation 21891:Software maintenance 21886:Software engineering 21848:Software development 21798:Programming language 21793:Programming paradigm 21710:Network architecture 21511:Computer programming 21490:Graph neural network 21065:Text-to-video models 21043:Text-to-image models 20891:Large language model 20876:Scientific computing 20682:Statistical manifold 20677:Information geometry 20007:Criticism of science 19882:Scientific formalism 19766:Constructive realism 19671:Scientific pluralism 19644:Problem of induction 19089:Emergent materialism 18733:McCarthy 91 function 18604:Thomason, Richmond. 18508:. 21 December 2006. 17611:– via msu.edu. 17156:Thro, Ellen (1993). 16071:10.2139/ssrn.3044448 15913:, Simon and Schuster 15807:on 29 November 2014. 15732:Lohr, Steve (2017). 15710:10.2139/ssrn.1736283 13832:on 12 November 2014. 11677:, pp. 51–107), 11661:"Google books ngram" 10312:Urbina et al. (2022) 8112:Frontiers in Sensors 7790:Deng & Yu (2014) 7401:, sect. 13.3–13.5), 7211:, chpt. 12–18, 20), 7122:, pp. ~46–52), 7118:, sects. 9.3, 9.4), 6879:, pp. 79–121), 6857:breadth first search 6758:Tao & Tan (2005) 6710:Challa et al. (2011) 6543:, pp. 91–104), 6478:The Economist (2016) 6093:non-monotonic logics 5555:, pp. 52–107), 5306:Jack Clark wrote in 5133:Sometimes called a " 4988:John Joseph Hopfield 4702:Case-based reasoning 3952:large language model 3746:general intelligence 3160:for maximum effect. 2989:deep neural networks 2983:Right to explanation 2969:Lack of transparency 2743:Constellation Energy 2679:cloud infrastructure 2606:differential privacy 2465:game-playing systems 2391:In the early 2020s, 2174:. Then, in 2017, it 1980:Microsoft Translator 1936:targeted advertising 1750:image classification 1549:hidden Markov models 1436:Non-monotonic logics 1424:symbolic programming 1181:astronomical numbers 1114:General intelligence 1106:and, more recently, 1091:. For example, some 1047:image classification 1030:, sonar, radar, and 732:), and other areas. 632:, and other fields. 586:General intelligence 108:General game playing 24580:William Grey Walter 24520:Sergei P. Kurdyumov 24480:N. Katherine Hayles 24262:Medical cybernetics 24222:Conversation theory 24074:Our Final Invention 23639:Powered exoskeleton 22944:Technology scouting 22919:Accelerating change 22649:Machine translation 22520:Document management 22510:Operations research 22435:Enterprise software 22351:Multi-task learning 22336:Supervised learning 22058:Information systems 21881:Software deployment 21838:Software repository 21692:Real-time computing 20857:In-context learning 20697:Pattern recognition 20510:Gaussian adaptation 20416:Genetic programming 20074:Rhetoric of science 20012:Descriptive science 19756:Confirmation holism 19649:Scientific evidence 19609:Inductive reasoning 19538:Demarcation problem 19286:Language of thought 19036:Ludwig Wittgenstein 18866:Patricia Churchland 18723:McCarthy evaluation 18629:, 8 December 2005). 18452:10.1038/nature16961 18444:2016Natur.529..484S 18321:Scientific American 18252:10.1038/nature14236 18244:2015Natur.518..529M 18200:Scientific American 18184:plugandpray-film.de 18178:Maschafilm (2010). 18171:Scientific American 18134:10.1038/nature14539 18126:2015Natur.521..436L 18067:2021Natur.596..583J 17995:Scientific American 17852:AI machine-learning 17736:2008gcr..book..303Y 17623:. 21 October 1999. 17621:Scientific American 17474:1993vise.nasa...11V 16841:Schmidhuber, Jürgen 16656:The Guardian Weekly 15910:The Society of Mind 15484:10.1197/jamia.M2055 15414:(1 November 2021). 15300:1974Sci...185.1124T 15212:2015Sci...349..255J 15045:The Washington Post 15016:2012ISPM...29...82H 13926:Scientific American 13662:10.1109/MIS.2009.75 13467:2 July 2023 at the 13354:Ciaramella, Alberto 13193:. Morgan Kaufmann. 13007:, pp. 340–400. 12687:, pp. 269–271) 12532:, pp. 10–11), 12518:Neats vs. scruffies 12436:, pp. 190–191) 12428:, pp. 15–16), 12391:, pp. 112–117. 12068:, pp. 189–201) 12047:, pp. 486–487) 12043:, pp. 24–26), 11978:Asada et al. (2009) 11929:, pp. 454–462. 11893:, pp. 155–183) 11845:, pp. 212–213. 11725:, pp. 70–71), 11681:, pp. 27–32), 11493:The Guardian Weekly 10503:Cellan-Jones (2014) 10489:The Guardian Weekly 10334:27 May 2023 at the 10218:, pp. 987–990. 10165:, pp. 108–112. 10153:, pp. 105–108. 9949:, pp. 993–994) 9945:, pp. 67–70); 9747:Pew Research Center 9716:Wall Street Journal 9678:Wall Street Journal 9659:Wall Street Journal 9312:, pp. 991–992. 8587:Uesato, J. et al.: 8533:2022Natur.602..223W 8422:2019Sci...365..885B 8207:. 20 December 2023. 8165:2021Natur.596..583J 7792:, pp. 199–200. 7505:Ciaramella, Alberto 7303:Hidden Markov model 7247:, pp. 381–394) 7163:ACM SIGPLAN Notices 7126:, pp. 62–73), 7085:, pp. 50–62), 7053:, pp. 45–50), 7043:Propositional logic 7029:, pp. 35–77), 6919:, pp. 133–150) 6853:Uninformed searches 6785:Poria et al. (2017) 6746:Affective computing 6724:, pp. 931–938. 6700:, pp. 899–901. 6688:, pp. 895–899. 6676:, pp. 849–850. 6632:, pp. 875–878. 6576:, pp. 856–858. 6564:, pp. 849–850) 6547:, pp. 591–632) 6460:, pp. 442–449) 6430:Supervised learning 6187:, pp. 204–208. 6068:, pp. 275–277) 6047:, pp. 335–337) 5691:, pp. 301–318) 5655:, pp. 189–201) 5643:, pp. 21–22), 5633:Mansfield Amendment 5611:, pp. 235–248) 5530:, pp. 200–201) 4944:Warren S. McCulloch 4714:Digital immortality 4631:the ability to feel 4154:Neats and scruffies 3918:In 2016, issues of 3835:pattern recognition 3763:Sir James Lighthill 3622:Daniel Huttenlocher 3555:Asilomar Conference 3452:symposium in 2005. 3399:Juergen Schmidhuber 3392:the joint statement 3053:dictionary learning 2803:conspiracy theories 2791:recommender systems 2737:In September 2024, 2731:Wall Street Journal 2542:Information privacy 2469:industrial robotics 2461:autonomous vehicles 2426:sparked a trend of 2414:generators such as 2351:autonomous vehicles 2347:command and control 2182:games, such as the 2090:Parkinson's disease 2038:Health and medicine 1960:autonomous vehicles 1856:In the late 2010s, 1591:supervised learning 1440:negation as failure 1346:Deductive reasoning 1310:logical connectives 1306:propositional logic 1167:means-ends analysis 1085:Affective computing 1069:Social intelligence 1041:The field includes 935:machine translation 863:Supervised learning 661:regulatory policies 610:operations research 515:autonomous vehicles 260:Machine translation 176:Systems integration 113:Knowledge reasoning 50:Part of a series on 32:AI (disambiguation) 24560:William Ross Ashby 24485:Natalia Bekhtereva 24460:Maleyka Abbaszadeh 24400:Heinz von Foerster 24325:Buckminster Fuller 24252:Information theory 24202:Catastrophe theory 23608:Universal Robotics 23583:Intuitive Surgical 23573:Harvest Automation 23538:Barrett Technology 23320:Robotic spacecraft 23166:Audio-Animatronics 22961:Technology roadmap 22674:Speech recognition 22659:Mobile translation 22632:Internet of things 22303:Search methodology 22250:Parallel computing 22207:Interaction design 22116:Computing platform 22043:Numerical analysis 22033:Information theory 21818:Software framework 21781:Software notations 21720:Network components 21617:Integrated circuit 21450:Echo state network 21338:Jürgen Schmidhuber 21033:Facial recognition 21028:Speech recognition 20938:Software libraries 20457:Swarm intelligence 20450:Related techniques 20426:Evolution strategy 20396:Cultural algorithm 20293:Science portal 20222:Carl Gustav Hempel 20177:Wilhelm Windelband 20064:Questionable cause 19887:Scientific realism 19708:Underdetermination 19543:Empirical evidence 19533:Creative synthesis 19114:Neurophenomenology 18785:Philosophy of mind 18738:Situation calculus 18728:McCarthy Formalism 18708:Garbage collection 18698:Dartmouth workshop 17785:. Harcourt Books. 17050:Later published as 16521:Information Fusion 15759:Connection Science 15738:The New York Times 15668:. Addison-Wesley. 14932:Harari, Yuval Noah 14899:The New York Times 14495:The Nervous System 14261:10.1561/2000000039 13904:10.1017/err.2019.8 13480:The New York Times 13410:Machines Who Think 13221:Russell, Stuart J. 13077:Russell, Stuart J. 12919:'s "singularity": 12096:, pp. 14, 27) 12011:, pp. 24, 26) 11970:Weng et al. (2001) 11729:, pp. 2, 984) 11685:, pp. 8–17), 11518:on 1 November 2023 11466:Kasperowicz (2023) 11435:. 5 September 2024 10865:, pp. 67, 73. 10459:Morgenstern (2015) 10363:IGM Chicago (2017) 10273:The New York Times 9631:Davenport, Carly. 9554:The New York Times 8870:The New York Times 8631:The New York Times 8466:. 23 December 2020 8350:The New York Times 7952:. 9 November 2023. 7912:Schmidhuber (2022) 7900:Schmidhuber (2022) 7883:Schmidhuber (2022) 7871:Schmidhuber (2022) 7763:Schmidhuber (2015) 7556:K-nearest neighbor 7395:Bayesian inference 7373:, chpt. 19.3–19.4) 6929:Adversarial search 6865:state space search 6861:depth-first search 6825:State space search 6762:Scassellati (2002) 6245:Classical planning 6209:Automated planning 6123:, ~18.3.3) (Poole 6005:Situation calculus 5964:description logics 5516:Dartmouth workshop 5405:2008-02-19 at the 5062:Cornell University 4960:Roger David Joseph 4720:Emergent algorithm 4578:(both 1968), with 4569:Arthur C. Clarke's 4544: 4330:philosophy of mind 4240:philosophy of mind 4190:genetic algorithms 4132:. Critics such as 4016: 3991:Dartmouth workshop 3700:information theory 3601: 3232:Carl Benedikt Frey 3029:Multitask learning 2887:On June 28, 2015, 2657:companies such as 2571:speech recognition 2453:virtual assistants 2389: 2355:target acquisition 2130:exhibition match, 2073:tissue engineering 1988:facial recognition 1948:virtual assistants 1742:speech recognition 1724: 1709:identify an "edge" 1654:artificial neurons 1650: 1610:K-nearest neighbor 1574: 1514:Bayesian inference 1467: 1272:(inspired by bird 1266:swarm intelligence 1227: 1195:Adversarial search 1159:State space search 1154:State space search 1144:state space search 1124:human intelligence 1104:sentiment analysis 1093:virtual assistants 1082: 1063:robotic perception 1055:object recognition 1051:facial recognition 1043:speech recognition 1024:Machine perception 974:Margaret Masterman 958:generative grammar 947:question answering 927:speech recognition 793:classical planning 770:automated planning 718: 475:web search engines 471:applications of AI 469:Some high-profile 68: 24907: 24906: 24901: 24900: 24883:Scientific naming 24873:Quantum computing 24703:Computer hardware 24698:Clinical research 24693:Civil engineering 24588: 24587: 24510:Ranulph Glanville 24425:Jakob von Uexküll 24405:Humberto Maturana 24365:Francis Heylighen 24123: 24122: 24040:Eliezer Yudkowsky 24015:Stuart J. Russell 23833:Superintelligence 23706: 23705: 23649:Robotic tech vest 23578:Honeybee Robotics 23394:Electric unicycle 23347:remotely-operated 22994: 22993: 22813: 22812: 22783:Optical computing 22566: 22565: 22495:Electronic voting 22425:Quantum Computing 22418:Applied computing 22404:Image compression 22174:Hardware security 22164:Security services 22121:Digital marketing 21901:Open-source model 21813:Modeling language 21725:Network scheduler 21546: 21545: 21308:Stephen Grossberg 21281: 21280: 20622: 20621: 20596:Program synthesis 20571:Genetic operators 20561:Fitness landscape 20515:Memetic algorithm 20500:Firefly algorithm 20411:Genetic algorithm 20300: 20299: 20142: 20141: 20054:Normative science 19911:Uniformitarianism 19666:Scientific method 19560:Explanatory power 19425: 19424: 19321:Mind–body problem 19219:Cognitive closure 19183:Substance dualism 18801:G. E. M. Anscombe 18751: 18750: 18438:(7587): 484–489. 18238:(7540): 529–533. 18218:978-0-3742-5783-5 18120:(7553): 436–444. 18061:(7873): 583–589. 18022:Immerwahr, Daniel 18008:ancient languages 17931:Kevin J. Mitchell 17850:writes: "Current 17792:978-0-1560-1391-8 17572:(5504): 599–600. 17480:on 1 January 2007 17254:978-9-2310-0450-6 17169:978-0-8160-2628-9 17108:978-3-5402-9621-8 17006:10.1109/93.311653 16922:978-0-4650-4521-1 16763:Autonomous Robots 16680:978-0-5255-5861-3 16659:. pp. 42–43. 16619:on 19 August 2018 16508:978-0-0613-3646-1 16484:978-3-5402-3733-4 16154:978-0-6745-7616-2 16116:978-1-4614-6940-7 15941:on 26 August 2007 15927:Rochester, Nathan 15872:on 8 October 2008 15675:978-0-2015-1752-1 15525:978-0-6700-3384-3 15518:. Penguin Books. 15317:978-0-5212-8414-1 15259:978-1-4299-6935-2 15206:(6245): 255–260. 14990:978-0-2620-8153-5 14775:978-1-4356-4787-9 14595:Fox News (2023). 14562:978-0-8021-1839-4 14506:978-0-7910-0464-7 14471:978-0-7382-0030-9 14435:978-0-0290-8060-3 14411:978-0-0601-1082-6 14387:978-0-4650-6570-7 14299:978-0-7139-9037-9 14164:978-1-4673-1228-8 14119:978-0-3938-6833-3 14094:978-0-5218-7628-5 13632:978-1-7864-3904-8 13440:978-0-6723-0412-5 13406:McCorduck, Pamela 13367:978-8-8947-8760-3 13345:978-3-3195-8486-7 13329:Other textbooks: 13308:978-1-1071-9539-4 13272:978-0-1951-0270-3 13200:978-1-5586-0467-4 13162:978-0-8053-4780-7 13126:978-0-0700-8770-5 13096:978-0-1346-1099-3 12967:AI as evolution: 12679:, pp. 985), 12422:Moravec's paradox 11777:, pp. 86–86. 11741:, pp. 47–49. 11717:, pp. 6–9), 11544:(Press release). 11496:. pp. 10–12. 11433:Council of Europe 10626:. 25 March 2023. 10492:. pp. 34–39. 10077:, pp. 88–91. 9574:. 24 January 2024 9510:. 26 March 2023. 9139:978-0-1282-4073-1 9061:978-0-1346-1099-3 9034:978-1-0092-5819-7 8527:(7896): 223–228. 8416:(6456): 885–890. 8159:(7873): 583–589. 7622:Neural networks: 7518:978-8-8947-8760-3 7471:decision networks 7435:Bayesian learning 7355:Bayesian networks 7277:decision networks 7237:decision analysis 7130:, chpt. 4.2, 7.2) 7099:Logical inference 7067:First-order logic 6797:Search algorithms 6476:, pp. 281), 6470:Transfer learning 6383:Solomonoff (1956) 6147:, Introduction), 6081:Default reasoning 5960:Semantic networks 5563:, pp. 19–21) 5421:Business Horizons 5039:In statistics, a 4972:Alexey Ivakhnenko 4784:Explanatory notes 4573:Stanley Kubrick's 4536:in his 1921 play 4508:in his 1998 book 4427:If research into 4422:superintelligence 4335:mind–body problem 4217:superintelligence 4110:Moravec's paradox 3987:Intelligent agent 3925:alignment problem 3804:academic research 3731:Dartmouth College 3627:Council of Europe 3595:The first global 3461:Stuart J. Russell 3442:Eliezer Yudkowsky 3315:Yuval Noah Harari 3304:superintelligence 3254:Joseph Weizenbaum 3190:mass surveillance 3136:allow widespread 3134:voice recognition 2761:Palisades Nuclear 2747:Three Mile Island 2602:de-identification 2579:temporary workers 2397:generative models 2301:from eleuther or 2186:-playing program 1972:self-driving cars 1810:(formerly Bard), 1530:decision networks 1506:Bayesian networks 1492:decision networks 1480:decision analysis 1444:default reasoning 1412:logic programming 1393:first-order logic 1379:. In the case of 1352:a new statement ( 1331:" and "There are 962:semantic networks 904:sample complexity 882:Transfer learning 746:default reasoning 657:long-term effects 473:include advanced 448:field of research 425: 424: 161:Bayesian networks 88:Intelligent agent 40:Intelligent agent 16:(Redirected from 24957: 24708:Computer science 24615: 24608: 24601: 24592: 24591: 24575:Warren McCulloch 24550:Valentin Turchin 24500:Pyotr Grigorenko 24445:John N. Warfield 24370:Francisco Varela 24330:Charles François 24300:Alexander Lerner 24277:Sociocybernetics 24197:Neurocybernetics 24150: 24143: 24136: 24127: 24126: 24115: 24114: 24062:Human Compatible 24035:Roman Yampolskiy 23783:Consequentialism 23740:Existential risk 23733: 23726: 23719: 23710: 23709: 23694: 23693: 23682: 23681: 23666:Fictional robots 23634:Critique of work 23283:Unmanned vehicle 23099: 23021: 23014: 23007: 22998: 22997: 22982: 22981: 22929:Horizon scanning 22845:Ephemeralization 22761:Racetrack memory 22696:Extended reality 22691:Cybermethodology 22611: 22610: 22593: 22586: 22579: 22570: 22569: 22556: 22555: 22546: 22545: 22536: 22535: 22356:Cross-validation 22328:Machine learning 22212:Social computing 22179:Network security 21974:Algorithm design 21896:Programming team 21856:Control variable 21833:Software library 21771:Software quality 21766:Operating system 21715:Network protocol 21580:Computer science 21573: 21566: 21559: 21550: 21549: 21536:Machine learning 21526: 21525: 21506: 21261:Action selection 21251:Self-driving car 21058:Stable Diffusion 21023:Speech synthesis 20988: 20987: 20852:Machine learning 20728:Gradient descent 20649: 20642: 20635: 20626: 20625: 20586:Machine learning 20556:Fitness function 20546:Digital organism 20327: 20320: 20313: 20304: 20303: 20291: 20290: 20279: 20278: 20277: 20252:Bas van Fraassen 20207:Hans Reichenbach 20187:Bertrand Russell 20104: 20103: 19930:Philosophy of... 19713:Unity of science 19506:Commensurability 19452: 19445: 19438: 19429: 19428: 19173:Representational 19168:Property dualism 19161:Type physicalism 19126:New mysterianism 19094:Epiphenomenalism 18916:Martin Heidegger 18778: 18771: 18764: 18755: 18754: 18670: 18663: 18656: 18647: 18646: 18634: 18633: 18619: 18610:Zalta, Edward N. 18600: 18565: 18564: 18549: 18547: 18545: 18539: 18532: 18521: 18519: 18517: 18483: 18481: 18479: 18422: 18420: 18418: 18412: 18389: 18379: 18283: 18281: 18279: 18222: 18191: 18165: 18163: 18161: 18104: 18086: 17980: 17978: 17976: 17965:The Times Online 17920:(July 18, 2023) 17913: 17907: 17905: 17887: 17885: 17816: 17814: 17812: 17777:Berlinski, David 17753: 17752: 17750: 17744: 17725: 17715: 17703: 17701: 17699: 17650: 17636: 17634: 17632: 17612: 17610: 17608: 17602: 17563: 17553: 17551: 17549: 17535: 17523: 17514: 17512: 17510: 17489: 17487: 17485: 17476:. 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Archived from 13820: 13818: 13816: 13805:TED (conference) 13795: 13781: 13772: 13770: 13768: 13762: 13755: 13743: 13725: 13707: 13682: 13673: 13650:Winston, Patrick 13644: 13617: 13615: 13613: 13593: 13564: 13556: 13547: 13524:AI & Society 13518: 13516: 13514: 13482: 13444: 13422: 13401: 13371: 13360:(1st ed.). 13349: 13338:(2nd ed.). 13324: 13322: 13320: 13288: 13286: 13284: 13243: 13216: 13214: 13212: 13192: 13178: 13176: 13174: 13154: 13130: 13108: 13056: 13050: 13044: 13038: 13032: 13026: 13020: 13014: 13008: 13005:McCorduck (2004) 13002: 12996: 12989: 12983: 12975:, p. 401), 12965: 12959: 12941: 12935: 12929: 12923: 12901:Omohundro (2008) 12885: 12879: 12878: 12876: 12874: 12859: 12853: 12852: 12850: 12848: 12833: 12827: 12826: 12824: 12822: 12799: 12793: 12792: 12780: 12774: 12773: 12771: 12769: 12754: 12745: 12744: 12742: 12740: 12725: 12714: 12713: 12711: 12709: 12694: 12688: 12661: 12655: 12649: 12643: 12637: 12631: 12625: 12619: 12613: 12607: 12601: 12595: 12589: 12583: 12577: 12571: 12565: 12556: 12550: 12544: 12528:, p. 168), 12515: 12509: 12503: 12497: 12491: 12485: 12479: 12473: 12443: 12437: 12419: 12413: 12408:, p. 153), 12398: 12392: 12389:Haugeland (1985) 12386: 12380: 12374: 12368: 12367: 12365: 12363: 12349: 12343: 12342: 12340: 12338: 12324: 12318: 12317: 12315: 12313: 12292: 12286: 12280: 12274: 12268: 12262: 12256: 12250: 12244: 12238: 12237: 12235: 12233: 12227:The Conversation 12218: 12212: 12206: 12200: 12194: 12185: 12179: 12173: 12167: 12161: 12160: 12158: 12156: 12136: 12130: 12120: 12114: 12108: 12097: 12087: 12081: 12075: 12069: 12060:, p. 265), 12054: 12048: 12030: 12024: 12018: 12012: 12002: 11996: 11990: 11984: 11963: 11957: 11951: 11942: 11936: 11930: 11927:McCorduck (2004) 11924: 11918: 11912: 11906: 11900: 11894: 11864: 11858: 11852: 11846: 11840: 11834: 11831:Lighthill (1973) 11828: 11822: 11816: 11810: 11800: 11794: 11784: 11778: 11772: 11766: 11760: 11754: 11748: 11742: 11736: 11730: 11699: 11690: 11671: 11665: 11664: 11657: 11651: 11650: 11632: 11621: 11615: 11606: 11605: 11603: 11601: 11586: 11580: 11579: 11577: 11575: 11564: 11558: 11557: 11555: 11553: 11534: 11528: 11527: 11525: 11523: 11504: 11498: 11497: 11487: 11481: 11475: 11469: 11463: 11457: 11451: 11445: 11444: 11442: 11440: 11425: 11419: 11418: 11410: 11404: 11398: 11392: 11389:Kissinger (2021) 11386: 11380: 11374: 11361: 11355: 11349: 11343: 11334: 11328: 11322: 11300: 11294: 11293: 11291: 11289: 11278: 11272: 11271: 11235: 11229: 11228: 11180: 11174: 11173: 11163: 11139: 11133: 11132: 11130: 11121: 11115: 11114: 11112: 11103: 11097: 11096: 11094: 11092: 11077: 11071: 11070: 11058: 11052: 11051: 11049: 11047: 11032: 11026: 11025: 11013: 11007: 11006: 11004: 11002: 10987: 10981: 10980: 10978: 10976: 10961: 10955: 10954: 10952: 10950: 10944:Business Insider 10935: 10929: 10923: 10917: 10911: 10905: 10899: 10893: 10887: 10878: 10875:Yudkowsky (2008) 10872: 10866: 10863:Christian (2020) 10860: 10851: 10833: 10827: 10826: 10824: 10822: 10807: 10801: 10800: 10798: 10796: 10781: 10775: 10774: 10772: 10770: 10755: 10749: 10748: 10746: 10744: 10729: 10723: 10722: 10720: 10718: 10703: 10697: 10691: 10685: 10684: 10682: 10680: 10665: 10659: 10658: 10646: 10640: 10639: 10637: 10635: 10616: 10610: 10596:Rawlinson (2015) 10592: 10586: 10580: 10574: 10568: 10562: 10548: 10542: 10536: 10530: 10524: 10518: 10512: 10506: 10500: 10494: 10493: 10483: 10477: 10468: 10462: 10456: 10450: 10449: 10447: 10445: 10430: 10424: 10423: 10421: 10419: 10404: 10398: 10384: 10378: 10372: 10366: 10360: 10354: 10352:McGaughey (2022) 10345: 10339: 10324: 10315: 10309: 10303: 10302: 10300: 10298: 10283: 10277: 10276: 10264: 10258: 10252: 10246: 10240:Robitzski (2018) 10237: 10231: 10225: 10219: 10213: 10204: 10198: 10192: 10191: 10189: 10187: 10172: 10166: 10163:Christian (2020) 10160: 10154: 10151:Christian (2020) 10148: 10142: 10136: 10130: 10124: 10118: 10115:Christian (2020) 10112: 10106: 10103:Christian (2020) 10100: 10094: 10084: 10078: 10075:Christian (2020) 10072: 10066: 10063:Christian (2020) 10060: 10054: 10053: 10046: 10040: 10034: 10028: 10022: 10016: 10009: 10003: 9998:, p. 994); 9993: 9987: 9980: 9974: 9961:, p. 995); 9956: 9950: 9940: 9934: 9933:, p. 67–70. 9931:Christian (2020) 9928: 9922: 9916: 9910: 9904: 9898: 9892: 9883: 9880:Christian (2020) 9877: 9871: 9853: 9847: 9841: 9835: 9829: 9823: 9817: 9808: 9807: 9805: 9803: 9788: 9779: 9773: 9767: 9761: 9755: 9754: 9738: 9732: 9726: 9720: 9719: 9707: 9701: 9700: 9688: 9682: 9681: 9669: 9663: 9662: 9650: 9644: 9643: 9637: 9628: 9622: 9621: 9609: 9603: 9602: 9590: 9584: 9583: 9581: 9579: 9564: 9558: 9557: 9545: 9539: 9538: 9522: 9516: 9515: 9505: 9498: 9492: 9491: 9481: 9473: 9467: 9466: 9450: 9444: 9443: 9435: 9427: 9421: 9415: 9409: 9403: 9397: 9396: 9394: 9392: 9369: 9363: 9362: 9360: 9358: 9346:Kopel, Matthew. 9343: 9337: 9331: 9325: 9322:Christian (2020) 9319: 9313: 9307: 9301: 9295: 9289: 9283: 9277: 9271: 9265: 9262:Laskowski (2023) 9259: 9253: 9247: 9241: 9235: 9229: 9228: 9196: 9190: 9189: 9172:(6): 3179–3185. 9157: 9151: 9149: 9148: 9146: 9121: 9115: 9114: 9098: 9092: 9091: 9089: 9087: 9080:McKinsey Digital 9072: 9066: 9065: 9045: 9039: 9038: 9010: 9004: 9003: 9001: 8999: 8984: 8978: 8977: 8975: 8973: 8950: 8944: 8943: 8941: 8939: 8924: 8918: 8917: 8915: 8913: 8893: 8887: 8886: 8884: 8882: 8860: 8854: 8853: 8851: 8838: 8832: 8831: 8829: 8827: 8821: 8814: 8805: 8799: 8798: 8796: 8794: 8771: 8765: 8764: 8744: 8735: 8731: 8729: 8718: 8707: 8700: 8694: 8691: 8685: 8678:Alex McFarland: 8676: 8670: 8664: 8658: 8649: 8643: 8642: 8640: 8638: 8621: 8615: 8614: 8612: 8600: 8594: 8585: 8579: 8578: 8576: 8574: 8559: 8553: 8552: 8516: 8510: 8509: 8507: 8505: 8482: 8476: 8475: 8473: 8471: 8456: 8450: 8449: 8401: 8395: 8394: 8392: 8390: 8375: 8369: 8368: 8366: 8364: 8347: 8339: 8333: 8332: 8330: 8328: 8322:The Conversation 8313: 8307: 8306: 8304: 8302: 8279: 8273: 8272: 8262: 8229: 8223: 8222: 8215: 8209: 8208: 8201: 8195: 8194: 8184: 8144: 8138: 8137: 8127: 8103: 8094: 8093: 8083: 8060:Future Healthc J 8051: 8045: 8044: 8032: 8026: 8025: 8023: 8021: 8006: 8000: 7994: 7988: 7985:Marmouyet (2023) 7982: 7976: 7975: 7973: 7971: 7960: 7954: 7953: 7946: 7940: 7934: 7928: 7921: 7915: 7909: 7903: 7897: 7886: 7880: 7874: 7868: 7859: 7853: 7834: 7828: 7817: 7811: 7805: 7799: 7793: 7787: 7781: 7771: 7765: 7740: 7731: 7721: 7715: 7705: 7699: 7689: 7683: 7666: 7660: 7637: 7631: 7620: 7611: 7597: 7591: 7585: 7579: 7549: 7543: 7529: 7523: 7522: 7501: 7495: 7484: 7478: 7464: 7458: 7432: 7426: 7420: 7414: 7392: 7386: 7380: 7374: 7352: 7346: 7339:mechanism design 7332: 7326: 7295: 7284: 7270: 7264: 7254: 7248: 7243:, chpt. 16–18), 7230: 7224: 7205: 7196: 7186: 7180: 7179: 7157: 7151: 7137: 7131: 7112: 7106: 7096: 7090: 7064: 7058: 7040: 7034: 7016: 7010: 7004: 6998: 6988: 6982: 6981: 6979: 6977: 6962: 6956: 6942: 6936: 6926: 6920: 6890: 6884: 6850: 6844: 6838: 6832: 6822: 6816: 6794: 6788: 6782: 6776: 6770: 6764: 6743: 6737: 6731: 6725: 6719: 6713: 6707: 6701: 6695: 6689: 6683: 6677: 6671: 6665: 6651: 6645: 6639: 6633: 6627: 6621: 6615: 6609: 6595: 6589: 6583: 6577: 6571: 6565: 6554: 6548: 6539:, chpt. 23–24), 6530: 6524: 6511: 6505: 6504: 6502: 6500: 6486: 6480: 6467: 6461: 6447: 6441: 6427: 6418: 6407:cluster analysis 6392: 6386: 6380: 6374: 6368: 6362: 6349:, chpt. 19–22), 6340: 6334: 6324: 6318: 6308: 6302: 6301:, Section 16.6). 6292: 6286: 6277:, Section 16.7) 6271: 6265: 6264:, Section 11.5). 6258: 6252: 6251:, Section 11.2). 6242: 6236: 6222: 6216: 6206: 6200: 6194: 6188: 6182: 6176: 6170: 6164: 6141: 6132: 6078: 6069: 6054: 6048: 6038: 6032: 6001: 5995: 5956: 5950: 5944: 5938: 5932: 5926: 5920: 5914: 5908: 5902: 5896: 5890: 5884: 5878: 5852: 5846: 5828: 5817: 5803: 5792: 5779:, chpt. 12–18), 5773: 5767: 5740: 5734: 5728: 5722: 5701: 5692: 5665: 5656: 5629:Lighthill report 5621: 5612: 5573: 5564: 5545: 5536: 5513: 5504: 5498: 5492: 5464: 5453: 5452: 5416: 5410: 5397: 5391: 5385: 5363: 5343: 5337: 5333: 5327: 5321: 5315: 5304: 5298: 5291: 5285: 5263: 5257: 5247: 5241: 5202: 5196: 5186: 5180: 5170: 5164: 5153: 5147: 5144: 5138: 5131: 5125: 5122: 5116: 5105: 5099: 5096: 5090: 5083: 5077: 5054: 5048: 5037: 5031: 5025: 5019: 5012:Seppo Linnainmaa 5004:Arthur E. Bryson 4996:Arthur E. Bryson 4968:Oliver Selfridge 4964:Frank Rosenblatt 4940: 4934: 4931:latent variables 4927: 4921: 4916:of one another. 4910: 4904: 4898: 4892: 4878: 4872: 4861: 4855: 4848: 4842: 4824: 4815: 4797: 4771:Wetware computer 4731: 4680: 4470:, cyberneticist 4393:moral blind spot 4148:Neat vs. scruffy 4130:algorithmic bias 4036: 3907:) and access to 3897:faster computers 3739:logical theorems 3654:AI Safety Summit 3597:AI Safety Summit 3501:Stable Diffusion 3465:three principles 3436:Human Compatible 3260:Existential risk 3182:advanced spyware 3142:Machine learning 3019:established the 2836:Algorithmic bias 2722:Research Paper, 2637:Jonathan Franzen 2598:data aggregation 2591:right to privacy 2424:Stable Diffusion 2058:Hippocratic Oath 2054:medical research 1984:Google Translate 1932:internet traffic 1870:machine learning 1762:curated datasets 1731:image processing 1705:image processing 1587:pattern matching 1500:mechanism design 1460:Bayesian network 1406:, and therefore 1248:gradient descent 1240:Gradient descent 1219:gradient descent 1217:Illustration of 931:speech synthesis 852:Machine learning 819:transition model 782:expected utility 503:Google Assistant 499:via human speech 452:computer science 444:computer systems 417: 410: 403: 324:Existential risk 146:Machine learning 47: 46: 21: 24965: 24964: 24960: 24959: 24958: 24956: 24955: 24954: 24945:Formal sciences 24910: 24909: 24908: 24903: 24902: 24897: 24796:Hebrew toponyms 24791:Arabic toponyms 24629: 24619: 24589: 24584: 24540:Talcott Parsons 24530:Stuart Kauffman 24430:Jason Jixuan Hu 24415:Igor Aleksander 24395:Gregory Bateson 24390:Gordon S. Brown 24375:Frederic Vester 24355:Erich von Holst 24315:Allenna Leonard 24305:Alexey Lyapunov 24286: 24232:Decision theory 24160: 24154: 24124: 24119: 24105: 24044: 24000:Steve Omohundro 23980:Geoffrey Hinton 23970:Stephen Hawking 23955:Paul Christiano 23935:Scott Alexander 23923: 23894:Google DeepMind 23842: 23828:Suffering risks 23746: 23737: 23707: 23702: 23670: 23622: 23543:Boston Dynamics 23528:Amazon Robotics 23516: 23440: 23431:Visual odometry 23421:Motion planning 23403: 23358: 23278:Continuum robot 23261:Classifications 23256: 23119:Anthropomorphic 23100: 23091: 23087:AI competitions 23030: 23025: 22995: 22990: 22970: 22809: 22620: 22617: 22616:Information and 22602: 22597: 22567: 22562: 22553: 22524: 22505:Word processing 22413: 22399:Virtual reality 22360: 22322: 22293:Computer vision 22269: 22265:Multiprocessing 22231: 22193: 22159:Security hacker 22135: 22111:Digital library 22052: 22003:Mathematics of 21998: 21960: 21936:Automata theory 21931:Formal language 21905: 21871:Software design 21842: 21775: 21761:Virtual machine 21739: 21735:Network service 21696: 21687:Embedded system 21660: 21593: 21582: 21577: 21547: 21542: 21494: 21408: 21374:Google DeepMind 21352: 21318:Geoffrey Hinton 21277: 21214: 21140:Project Debater 21086: 20984:Implementations 20979: 20933: 20897: 20840: 20782:Backpropagation 20716: 20702:Tensor calculus 20656: 20653: 20623: 20618: 20600: 20541:Artificial life 20519: 20486: 20445: 20372: 20336: 20331: 20301: 20296: 20285: 20275: 20273: 20261: 20242:Paul Feyerabend 20202:Michael Polanyi 20138: 20124:Galileo Galilei 20093: 20079:Science studies 19995: 19925: 19916:Verificationism 19821:Instrumentalism 19806:Foundationalism 19781:Conventionalism 19739: 19575:Feminist method 19461: 19456: 19426: 19421: 19393: 19360: 19306:Mental property 19199:Abstract object 19187: 19057: 19011:Wilfrid Sellars 18886:Donald Davidson 18871:Paul Churchland 18831:George Berkeley 18787: 18782: 18752: 18747: 18693:Circumscription 18679: 18674: 18639: 18589: 18586: 18585: 18584: 18566: 18562: 18557: 18552: 18543: 18541: 18537: 18530: 18515: 18513: 18500: 18487:Vaswani, Ashish 18477: 18475: 18416: 18414: 18410: 18387: 18344:"Deep Learning" 18335:Foreign Affairs 18277: 18275: 18219: 18159: 18157: 18110:"Deep learning" 17974: 17972: 17903: 17901: 17839:Foreign Affairs 17834:Cukier, Kenneth 17824:Mind As Machine 17820:Boden, Margaret 17810: 17808: 17793: 17766:Autor, David H. 17761: 17759:Further reading 17756: 17748: 17746: 17742: 17723: 17697: 17695: 17630: 17628: 17606: 17604: 17600: 17561: 17547: 17545: 17508: 17506: 17483: 17481: 17447: 17445: 17422: 17420: 17397: 17395: 17372: 17370: 17340: 17338: 17264: 17262: 17255: 17199: 17197: 17179: 17177: 17170: 17146: 17144: 17109: 17079: 17077: 17073: 17066: 17052: 17051: 17043: 17041: 17037: 17030: 17022:Solomonoff, Ray 16994:IEEE MultiMedia 16982: 16980: 16940: 16938: 16923: 16896: 16894: 16890: 16859: 16795:Neural Networks 16791:Schmidhuber, J. 16751: 16749: 16731: 16729: 16711: 16709: 16681: 16665:Russell, Stuart 16643: 16641: 16622: 16620: 16585: 16583: 16560: 16558: 16509: 16485: 16455: 16453: 16449: 16418: 16375: 16373: 16369: 16354: 16337: 16335: 16234: 16203: 16189: 16187: 16164: 16162: 16155: 16117: 16096: 16094: 15982: 15980: 15944: 15942: 15931:Shannon, Claude 15894: 15892: 15875: 15873: 15852: 15850: 15827: 15825: 15747: 15745: 15724: 15701: 15676: 15651: 15649: 15601: 15599: 15581: 15579: 15566:(23 May 2016). 15526: 15456: 15454: 15447:InformationWeek 15431: 15429: 15401: 15399: 15381: 15379: 15356: 15354: 15318: 15269: 15267: 15260: 15151: 15149: 15126: 15124: 15105: 15103: 15083:Neural Networks 15078: 15062: 15060: 14991: 14977:Haugeland, John 14951: 14949: 14921: 14919: 14829: 14827: 14793: 14791: 14776: 14746: 14744: 14721: 14719: 14675: 14673: 14612: 14610: 14606: 14599: 14597:"Fox News Poll" 14585: 14583: 14563: 14541: 14539: 14516: 14514: 14507: 14481: 14479: 14472: 14445: 14443: 14436: 14420:Dreyfus, Hubert 14412: 14396:Dreyfus, Hubert 14388: 14370:Domingos, Pedro 14364:on 27 June 2022 14342: 14340: 14322: 14320: 14300: 14284:Dennett, Daniel 14273: 14271: 14267: 14244: 14222: 14220: 14197: 14195: 14165: 14120: 14095: 14065: 14063: 14042:Chalmers, David 14031: 14029: 13952: 13950: 13877: 13862:10.1.1.588.7539 13844: 13814: 13812: 13766: 13764: 13760: 13753: 13633: 13611: 13609: 13512: 13510: 13497:(22 May 2023). 13495:Sutskever, Ilya 13469:Wayback Machine 13452: 13447: 13441: 13427:Newquist, H. P. 13420: 13398: 13384:Crevier, Daniel 13378: 13368: 13352: 13346: 13333: 13327: 13318: 13316: 13309: 13293:Mackworth, Alan 13289:Later edition: 13282: 13280: 13273: 13253:Mackworth, Alan 13241: 13210: 13208: 13201: 13172: 13170: 13163: 13127: 13111: 13097: 13065: 13060: 13059: 13051: 13047: 13041:McCauley (2007) 13039: 13035: 13029:Anderson (2008) 13027: 13023: 13017:Buttazzo (2001) 13015: 13011: 13003: 12999: 12995:, pp. 4–5) 12993:McCorduck (2004 12990: 12986: 12973:McCorduck (2004 12966: 12962: 12958:, p. 1005) 12952:Kurzweil (2005) 12942: 12938: 12934:, p. 1005. 12930: 12926: 12915: 12907: 12905:Kurzweil (2005) 12886: 12882: 12872: 12870: 12860: 12856: 12846: 12844: 12834: 12830: 12820: 12818: 12800: 12796: 12782: 12781: 12777: 12767: 12765: 12755: 12748: 12738: 12736: 12726: 12717: 12707: 12705: 12695: 12691: 12681:McCorduck (2004 12662: 12658: 12654:, p. 9817. 12650: 12646: 12638: 12634: 12626: 12622: 12614: 12610: 12602: 12598: 12592:Chalmers (1995) 12590: 12586: 12578: 12574: 12566: 12559: 12551: 12547: 12542:Domingos (2015) 12522:McCorduck (2004 12516: 12512: 12504: 12500: 12492: 12488: 12480: 12476: 12462:McCorduck (2004 12444: 12440: 12432:, p. 29), 12420: 12416: 12406:McCorduck (2004 12399: 12395: 12387: 12383: 12375: 12371: 12361: 12359: 12351: 12350: 12346: 12336: 12334: 12326: 12325: 12321: 12311: 12309: 12294: 12293: 12289: 12281: 12277: 12271:McCarthy (1999) 12269: 12265: 12257: 12253: 12245: 12241: 12231: 12229: 12219: 12215: 12207: 12203: 12195: 12188: 12180: 12176: 12168: 12164: 12154: 12152: 12137: 12133: 12121: 12117: 12109: 12100: 12088: 12084: 12076: 12072: 12055: 12051: 12045:McCorduck (2004 12031: 12027: 12019: 12015: 12003: 11999: 11991: 11987: 11964: 11960: 11952: 11945: 11937: 11933: 11925: 11921: 11913: 11909: 11901: 11897: 11883:McCorduck (2004 11881:, chpt. 17.4), 11865: 11861: 11853: 11849: 11841: 11837: 11829: 11825: 11817: 11813: 11801: 11797: 11785: 11781: 11775:Newquist (1994) 11773: 11769: 11761: 11757: 11749: 11745: 11737: 11733: 11723:McCorduck (2004 11721:, p. 24), 11715:Haugeland (1985 11700: 11693: 11675:McCorduck (2004 11672: 11668: 11659: 11658: 11654: 11647: 11633: 11624: 11616: 11609: 11599: 11597: 11588: 11587: 11583: 11573: 11571: 11566: 11565: 11561: 11551: 11549: 11536: 11535: 11531: 11521: 11519: 11506: 11505: 11501: 11488: 11484: 11478:Fox News (2023) 11476: 11472: 11464: 11460: 11452: 11448: 11438: 11436: 11427: 11426: 11422: 11411: 11407: 11399: 11395: 11387: 11383: 11375: 11364: 11356: 11352: 11344: 11337: 11329: 11325: 11301: 11297: 11287: 11285: 11280: 11279: 11275: 11236: 11232: 11181: 11177: 11140: 11136: 11128: 11122: 11118: 11110: 11104: 11100: 11090: 11088: 11078: 11074: 11059: 11055: 11045: 11043: 11033: 11029: 11014: 11010: 11000: 10998: 10988: 10984: 10974: 10972: 10962: 10958: 10948: 10946: 10936: 10932: 10924: 10920: 10912: 10908: 10900: 10896: 10888: 10881: 10873: 10869: 10861: 10854: 10845:Madrigal (2015) 10834: 10830: 10820: 10818: 10808: 10804: 10794: 10792: 10790:Financial Times 10782: 10778: 10768: 10766: 10756: 10752: 10742: 10740: 10730: 10726: 10716: 10714: 10704: 10700: 10692: 10688: 10678: 10676: 10667: 10666: 10662: 10647: 10643: 10633: 10631: 10618: 10617: 10613: 10593: 10589: 10581: 10577: 10569: 10565: 10549: 10545: 10537: 10533: 10525: 10521: 10517:, p. 1001. 10513: 10509: 10501: 10497: 10484: 10480: 10475:Thompson (2014) 10469: 10465: 10457: 10453: 10443: 10441: 10431: 10427: 10417: 10415: 10405: 10401: 10385: 10381: 10373: 10369: 10361: 10357: 10346: 10342: 10336:Wayback Machine 10325: 10318: 10310: 10306: 10296: 10294: 10285: 10284: 10280: 10265: 10261: 10253: 10249: 10238: 10234: 10226: 10222: 10214: 10207: 10199: 10195: 10185: 10183: 10173: 10169: 10161: 10157: 10149: 10145: 10137: 10133: 10125: 10121: 10113: 10109: 10101: 10097: 10089:, p. 83); 10087:Christian (2020 10085: 10081: 10073: 10069: 10061: 10057: 10052:. 16 June 2023. 10048: 10047: 10043: 10035: 10031: 10025:Dockrill (2022) 10023: 10019: 10013:Christian (2020 10010: 10006: 10000:Christian (2020 9994: 9990: 9984:Christian (2020 9981: 9977: 9971:Christian (2020 9965:, p. 36); 9963:Lipartito (2011 9957: 9953: 9943:Christian (2020 9941: 9937: 9929: 9925: 9917: 9913: 9905: 9901: 9893: 9886: 9878: 9874: 9862:, p. 17); 9854: 9850: 9842: 9838: 9830: 9826: 9818: 9811: 9801: 9799: 9789: 9782: 9774: 9770: 9764:Williams (2023) 9762: 9758: 9739: 9735: 9727: 9723: 9708: 9704: 9697:Washington Post 9689: 9685: 9670: 9666: 9651: 9647: 9635: 9629: 9625: 9618:Washington Post 9610: 9606: 9591: 9587: 9577: 9575: 9566: 9565: 9561: 9546: 9542: 9523: 9519: 9500: 9499: 9495: 9475: 9474: 9470: 9451: 9447: 9433: 9429: 9428: 9424: 9416: 9412: 9404: 9400: 9390: 9388: 9372:Burgess, Matt. 9370: 9366: 9356: 9354: 9344: 9340: 9332: 9328: 9320: 9316: 9308: 9304: 9296: 9292: 9286:Valinsky (2019) 9284: 9280: 9272: 9268: 9260: 9256: 9248: 9244: 9238:Simonite (2016) 9236: 9232: 9197: 9193: 9166:Fire Technology 9158: 9154: 9144: 9142: 9140: 9122: 9118: 9099: 9095: 9085: 9083: 9074: 9073: 9069: 9062: 9046: 9042: 9035: 9011: 9007: 8997: 8995: 8985: 8981: 8971: 8969: 8951: 8947: 8937: 8935: 8925: 8921: 8911: 8909: 8894: 8890: 8880: 8878: 8861: 8857: 8839: 8835: 8825: 8823: 8819: 8812: 8806: 8802: 8792: 8790: 8772: 8768: 8745: 8738: 8727: 8719: 8710: 8701: 8697: 8692: 8688: 8677: 8673: 8665: 8661: 8650: 8646: 8636: 8634: 8622: 8618: 8601: 8597: 8586: 8582: 8572: 8570: 8560: 8556: 8517: 8513: 8503: 8501: 8483: 8479: 8469: 8467: 8464:Google DeepMind 8458: 8457: 8453: 8402: 8398: 8388: 8386: 8376: 8372: 8362: 8360: 8340: 8336: 8326: 8324: 8314: 8310: 8300: 8298: 8280: 8276: 8230: 8226: 8217: 8216: 8212: 8203: 8202: 8198: 8145: 8141: 8104: 8097: 8052: 8048: 8033: 8029: 8019: 8017: 8007: 8003: 7997:Kobielus (2019) 7995: 7991: 7983: 7979: 7969: 7967: 7962: 7961: 7957: 7948: 7947: 7943: 7935: 7931: 7925:Christian (2020 7922: 7918: 7910: 7906: 7898: 7889: 7881: 7877: 7869: 7862: 7854: 7837: 7829: 7820: 7812: 7808: 7800: 7796: 7788: 7784: 7772: 7768: 7741: 7734: 7722: 7718: 7706: 7702: 7690: 7686: 7667: 7663: 7651:, sect. 21.2), 7641:backpropagation 7638: 7634: 7621: 7614: 7606:, sect. 12.6), 7598: 7594: 7588:Domingos (2015) 7586: 7582: 7566:, sect. 19.7), 7552:Non-parameteric 7550: 7546: 7538:, sect. 19.3), 7530: 7526: 7519: 7502: 7498: 7485: 7481: 7465: 7461: 7433: 7429: 7423:Domingos (2015) 7421: 7417: 7393: 7389: 7383:Domingos (2015) 7381: 7377: 7353: 7349: 7333: 7329: 7296: 7287: 7271: 7267: 7255: 7251: 7233:decision theory 7231: 7227: 7206: 7199: 7187: 7183: 7158: 7154: 7138: 7134: 7113: 7109: 7097: 7093: 7065: 7061: 7041: 7037: 7025:, chpts. 6–9), 7017: 7013: 7005: 7001: 6989: 6985: 6975: 6973: 6963: 6959: 6943: 6939: 6927: 6923: 6891: 6887: 6851: 6847: 6839: 6835: 6823: 6819: 6803:, chpts. 3–5), 6795: 6791: 6783: 6779: 6771: 6767: 6744: 6740: 6732: 6728: 6720: 6716: 6708: 6704: 6696: 6692: 6684: 6680: 6672: 6668: 6654:Computer vision 6652: 6648: 6642:Bushwick (2023) 6640: 6636: 6628: 6624: 6616: 6612: 6596: 6592: 6584: 6580: 6572: 6568: 6556:Subproblems of 6555: 6551: 6531: 6527: 6512: 6508: 6498: 6496: 6488: 6487: 6483: 6468: 6464: 6448: 6444: 6428: 6421: 6393: 6389: 6381: 6377: 6369: 6365: 6341: 6337: 6325: 6321: 6309: 6305: 6293: 6289: 6285:, Section 22.6) 6272: 6268: 6259: 6255: 6243: 6239: 6235:, chpt. 16–18). 6229:Decision theory 6223: 6219: 6207: 6203: 6195: 6191: 6183: 6179: 6173:Newquist (1994) 6171: 6167: 6155:, p. 13), 6142: 6135: 6097:circumscription 6079: 6072: 6055: 6051: 6041:Causal calculus 6039: 6035: 6013:fluent calculus 6002: 5998: 5957: 5953: 5949:, pp. 272. 5945: 5941: 5933: 5929: 5921: 5917: 5909: 5905: 5897: 5893: 5885: 5881: 5853: 5849: 5832:Kahneman (2011) 5829: 5820: 5804: 5795: 5774: 5770: 5741: 5737: 5729: 5725: 5720:McKinsey (2018) 5718:, p. 26), 5702: 5695: 5677:McCorduck (2004 5675:, p. 24), 5666: 5659: 5622: 5615: 5603:, p. 23), 5593:McCorduck (2004 5574: 5567: 5549:McCorduck (2004 5546: 5539: 5531: 5524:McCorduck (2004 5522:, p. 18), 5514: 5507: 5499: 5495: 5486:McCarthy (2007) 5479: 5474: 5465: 5456: 5417: 5413: 5407:Wayback Machine 5398: 5394: 5390:, pp. 1–4. 5386: 5377: 5372: 5367: 5366: 5344: 5340: 5334: 5330: 5322: 5318: 5305: 5301: 5292: 5288: 5264: 5260: 5248: 5244: 5203: 5199: 5187: 5183: 5171: 5167: 5154: 5150: 5145: 5141: 5132: 5128: 5123: 5119: 5106: 5102: 5097: 5093: 5084: 5080: 5070:Carnegie Mellon 5055: 5051: 5038: 5034: 5028:Geoffrey Hinton 5026: 5022: 4992:Henry J. Kelley 4984:Shun-Ichi Amari 4941: 4937: 4928: 4924: 4911: 4907: 4899: 4895: 4879: 4875: 4862: 4858: 4849: 4845: 4825: 4818: 4798: 4791: 4786: 4729: 4678: 4671: 4618:introduced the 4548:science fiction 4526: 4520: 4488:Robert Ettinger 4474:, and inventor 4466:Robot designer 4464: 4418: 4413: 4401:factory farming 4362: 4326: 4314:Main articles: 4312: 4283: 4275:Main articles: 4273: 4236: 4228:Main articles: 4226: 4213: 4205:Main articles: 4203: 4182: 4176: 4168:neural networks 4156: 4150: 4092: 4067: 4034: 3997: 3979: 3974: 3968: 3938:, developed by 3905:cloud computing 3855:Geoffrey Hinton 3684: 3677: 3671: 3663:AI Seoul Summit 3614:Henry Kissinger 3589: 3577:Main articles: 3575: 3517: 3473: 3457:Wendell Wallach 3438: 3418:Main articles: 3416: 3381:Geoffrey Hinton 3350:Stephen Hawking 3272:Stephen Hawking 3268: 3262: 3212: 3204:Main articles: 3202: 3178:digital warfare 3075: 3063:Main articles: 3061: 2985: 2971: 2932:recommendations 2880:. The field of 2842: 2834:Main articles: 2832: 2824:Geoffrey Hinton 2789:and others use 2780: 2774: 2745:to re-open the 2707:(IEA) released 2701: 2695: 2651: 2618:Brian Christian 2548: 2538: 2533: 2516: 2510: 2477: 2448: 2381: 2375: 2343: 2337: 2321: 2295:Google DeepMind 2225: 2176:defeated Ke Jie 2108: 2102: 2094:alpha-synuclein 2046: 2040: 1900: 1894: 1854: 1846:Main articles: 1844: 1774: 1754:backpropagation 1738:computer vision 1717: 1674:backpropagation 1634: 1626:Neural networks 1579: 1476:decision theory 1452: 1420:Turing complete 1366:inference rules 1314:predicate logic 1290: 1211: 1156: 1140: 1132: 1118:A machine with 1116: 1071: 1059:object tracking 1036:Computer vision 1032:tactile sensors 1021: 916: 849: 823:reward function 762: 710: 682: 673: 497:); interacting 442:, particularly 421: 392: 391: 382: 374: 373: 349: 339: 338: 310:Control problem 290: 280: 279: 191: 181: 180: 141: 133: 132: 103:Computer vision 78: 43: 28: 23: 22: 15: 12: 11: 5: 24963: 24953: 24952: 24947: 24942: 24937: 24932: 24927: 24922: 24905: 24904: 24899: 24898: 24896: 24895: 24890: 24885: 24880: 24875: 24870: 24865: 24860: 24855: 24850: 24848:Nanotechnology 24845: 24840: 24835: 24830: 24825: 24820: 24818:Machine vision 24815: 24810: 24805: 24804: 24803: 24798: 24793: 24788: 24783: 24775: 24774: 24773: 24768: 24760: 24755: 24750: 24745: 24744: 24743: 24738: 24730: 24725: 24720: 24715: 24710: 24705: 24700: 24695: 24690: 24685: 24680: 24675: 24670: 24665: 24660: 24655: 24650: 24645: 24640: 24634: 24631: 24630: 24621:Glossaries of 24618: 24617: 24610: 24603: 24595: 24586: 24585: 24583: 24582: 24577: 24572: 24567: 24562: 24557: 24552: 24547: 24542: 24537: 24535:Stuart Umpleby 24532: 24527: 24522: 24517: 24512: 24507: 24502: 24497: 24495:Norbert Wiener 24492: 24490:Niklas Luhmann 24487: 24482: 24477: 24472: 24467: 24465:Manfred Clynes 24462: 24457: 24452: 24447: 24442: 24440:Jennifer Wilby 24437: 24432: 24427: 24422: 24417: 24412: 24410:I. A. Richards 24407: 24402: 24397: 24392: 24387: 24382: 24377: 24372: 24367: 24362: 24357: 24352: 24347: 24345:Claude Bernard 24342: 24340:Margaret Boden 24337: 24335:Genevieve Bell 24332: 24327: 24322: 24320:Anthony Wilden 24317: 24312: 24307: 24302: 24296: 24294: 24292:Cyberneticians 24288: 24287: 24285: 24284: 24279: 24274: 24272:Cybersemiotics 24269: 24264: 24259: 24254: 24249: 24244: 24239: 24234: 24229: 24224: 24219: 24217:Control theory 24214: 24209: 24204: 24199: 24194: 24189: 24184: 24179: 24174: 24168: 24166: 24162: 24161: 24153: 24152: 24145: 24138: 24130: 24121: 24120: 24110: 24107: 24106: 24104: 24103: 24098: 24091: 24084: 24077: 24070: 24065: 24058: 24052: 24050: 24046: 24045: 24043: 24042: 24037: 24032: 24027: 24022: 24017: 24012: 24007: 24002: 23997: 23992: 23987: 23982: 23977: 23972: 23967: 23962: 23957: 23952: 23947: 23942: 23937: 23931: 23929: 23925: 23924: 23922: 23921: 23916: 23911: 23906: 23901: 23896: 23891: 23886: 23881: 23876: 23871: 23866: 23861: 23856: 23850: 23848: 23844: 23843: 23841: 23840: 23835: 23830: 23825: 23823:Machine ethics 23820: 23815: 23810: 23805: 23800: 23795: 23790: 23785: 23780: 23775: 23770: 23765: 23760: 23754: 23752: 23748: 23747: 23736: 23735: 23728: 23721: 23713: 23704: 23703: 23701: 23700: 23688: 23675: 23672: 23671: 23669: 23668: 23663: 23661:Terrainability 23658: 23653: 23652: 23651: 23641: 23636: 23630: 23628: 23624: 23623: 23621: 23620: 23615: 23610: 23605: 23600: 23595: 23590: 23585: 23580: 23575: 23570: 23565: 23560: 23555: 23550: 23545: 23540: 23535: 23530: 23524: 23522: 23518: 23517: 23515: 23514: 23509: 23504: 23499: 23494: 23489: 23484: 23479: 23474: 23469: 23464: 23459: 23454: 23448: 23446: 23442: 23441: 23439: 23438: 23433: 23428: 23423: 23417: 23415: 23405: 23404: 23402: 23401: 23396: 23391: 23386: 23385: 23384: 23374: 23368: 23366: 23360: 23359: 23357: 23356: 23355: 23354: 23349: 23339: 23334: 23329: 23328: 23327: 23317: 23312: 23307: 23302: 23297: 23296: 23295: 23290: 23280: 23275: 23273:Cloud robotics 23270: 23264: 23262: 23258: 23257: 23255: 23254: 23249: 23244: 23239: 23234: 23229: 23224: 23219: 23214: 23209: 23204: 23199: 23194: 23189: 23188: 23187: 23177: 23172: 23171: 23170: 23169: 23168: 23153: 23148: 23143: 23142: 23141: 23136: 23131: 23126: 23116: 23110: 23108: 23102: 23101: 23094: 23092: 23090: 23089: 23084: 23079: 23074: 23069: 23064: 23059: 23054: 23049: 23044: 23038: 23036: 23032: 23031: 23024: 23023: 23016: 23009: 23001: 22992: 22991: 22989: 22988: 22975: 22972: 22971: 22969: 22968: 22963: 22958: 22953: 22948: 22947: 22946: 22941: 22936: 22931: 22926: 22921: 22911: 22906: 22901: 22896: 22895: 22894: 22884: 22879: 22874: 22873: 22872: 22867: 22862: 22857: 22847: 22842: 22837: 22832: 22827: 22821: 22819: 22815: 22814: 22811: 22810: 22808: 22807: 22802: 22797: 22796: 22795: 22785: 22780: 22779: 22778: 22773: 22768: 22763: 22758: 22753: 22748: 22743: 22738: 22733: 22728: 22720: 22715: 22714: 22713: 22708: 22698: 22693: 22688: 22683: 22678: 22677: 22676: 22671: 22666: 22661: 22656: 22654:Machine vision 22651: 22646: 22636: 22635: 22634: 22623: 22621: 22618:communications 22614: 22608: 22604: 22603: 22596: 22595: 22588: 22581: 22573: 22564: 22563: 22561: 22560: 22550: 22540: 22529: 22526: 22525: 22523: 22522: 22517: 22512: 22507: 22502: 22497: 22492: 22487: 22482: 22477: 22472: 22467: 22462: 22457: 22452: 22447: 22442: 22437: 22432: 22427: 22421: 22419: 22415: 22414: 22412: 22411: 22409:Solid modeling 22406: 22401: 22396: 22391: 22386: 22381: 22376: 22370: 22368: 22362: 22361: 22359: 22358: 22353: 22348: 22343: 22338: 22332: 22330: 22324: 22323: 22321: 22320: 22315: 22310: 22308:Control method 22305: 22300: 22295: 22290: 22285: 22279: 22277: 22271: 22270: 22268: 22267: 22262: 22260:Multithreading 22257: 22252: 22247: 22241: 22239: 22233: 22232: 22230: 22229: 22224: 22219: 22214: 22209: 22203: 22201: 22195: 22194: 22192: 22191: 22186: 22181: 22176: 22171: 22166: 22161: 22156: 22154:Formal methods 22151: 22145: 22143: 22137: 22136: 22134: 22133: 22128: 22126:World Wide Web 22123: 22118: 22113: 22108: 22103: 22098: 22093: 22088: 22083: 22078: 22073: 22068: 22062: 22060: 22054: 22053: 22051: 22050: 22045: 22040: 22035: 22030: 22025: 22020: 22015: 22009: 22007: 22000: 21999: 21997: 21996: 21991: 21986: 21981: 21976: 21970: 21968: 21962: 21961: 21959: 21958: 21953: 21948: 21943: 21938: 21933: 21928: 21927: 21926: 21915: 21913: 21907: 21906: 21904: 21903: 21898: 21893: 21888: 21883: 21878: 21873: 21868: 21863: 21858: 21852: 21850: 21844: 21843: 21841: 21840: 21835: 21830: 21825: 21820: 21815: 21810: 21805: 21800: 21795: 21789: 21787: 21777: 21776: 21774: 21773: 21768: 21763: 21758: 21753: 21747: 21745: 21741: 21740: 21738: 21737: 21732: 21727: 21722: 21717: 21712: 21706: 21704: 21698: 21697: 21695: 21694: 21689: 21684: 21679: 21674: 21668: 21666: 21662: 21661: 21659: 21658: 21649: 21644: 21639: 21634: 21629: 21624: 21619: 21614: 21609: 21603: 21601: 21595: 21594: 21587: 21584: 21583: 21576: 21575: 21568: 21561: 21553: 21544: 21543: 21541: 21540: 21539: 21538: 21533: 21520: 21519: 21518: 21513: 21499: 21496: 21495: 21493: 21492: 21487: 21482: 21477: 21472: 21467: 21462: 21457: 21452: 21447: 21442: 21437: 21432: 21427: 21422: 21416: 21414: 21410: 21409: 21407: 21406: 21401: 21396: 21391: 21386: 21381: 21376: 21371: 21366: 21360: 21358: 21354: 21353: 21351: 21350: 21348:Ilya Sutskever 21345: 21340: 21335: 21330: 21325: 21320: 21315: 21313:Demis Hassabis 21310: 21305: 21303:Ian Goodfellow 21300: 21295: 21289: 21287: 21283: 21282: 21279: 21278: 21276: 21275: 21270: 21269: 21268: 21258: 21253: 21248: 21243: 21238: 21233: 21228: 21222: 21220: 21216: 21215: 21213: 21212: 21207: 21202: 21197: 21192: 21187: 21182: 21177: 21172: 21167: 21162: 21157: 21152: 21147: 21142: 21137: 21132: 21131: 21130: 21120: 21115: 21110: 21105: 21100: 21094: 21092: 21088: 21087: 21085: 21084: 21079: 21078: 21077: 21072: 21062: 21061: 21060: 21055: 21050: 21040: 21035: 21030: 21025: 21020: 21015: 21010: 21005: 21000: 20994: 20992: 20985: 20981: 20980: 20978: 20977: 20972: 20967: 20962: 20957: 20952: 20947: 20941: 20939: 20935: 20934: 20932: 20931: 20926: 20921: 20916: 20911: 20905: 20903: 20899: 20898: 20896: 20895: 20894: 20893: 20886:Language model 20883: 20878: 20873: 20872: 20871: 20861: 20860: 20859: 20848: 20846: 20842: 20841: 20839: 20838: 20836:Autoregression 20833: 20828: 20827: 20826: 20816: 20814:Regularization 20811: 20810: 20809: 20804: 20799: 20789: 20784: 20779: 20777:Loss functions 20774: 20769: 20764: 20759: 20754: 20753: 20752: 20742: 20737: 20736: 20735: 20724: 20722: 20718: 20717: 20715: 20714: 20712:Inductive bias 20709: 20704: 20699: 20694: 20689: 20684: 20679: 20674: 20666: 20664: 20658: 20657: 20652: 20651: 20644: 20637: 20629: 20620: 20619: 20617: 20616: 20610: 20608: 20602: 20601: 20599: 20598: 20593: 20588: 20583: 20578: 20573: 20568: 20563: 20558: 20553: 20548: 20543: 20538: 20533: 20527: 20525: 20524:Related topics 20521: 20520: 20518: 20517: 20512: 20507: 20505:Harmony search 20502: 20496: 20494: 20488: 20487: 20485: 20484: 20479: 20474: 20469: 20467:Bees algorithm 20464: 20459: 20453: 20451: 20447: 20446: 20444: 20443: 20438: 20436:Neuroevolution 20433: 20428: 20423: 20418: 20413: 20408: 20403: 20398: 20393: 20388: 20382: 20380: 20374: 20373: 20371: 20370: 20365: 20360: 20355: 20350: 20344: 20342: 20338: 20337: 20330: 20329: 20322: 20315: 20307: 20298: 20297: 20295: 20283: 20271: 20266: 20263: 20262: 20260: 20259: 20254: 20249: 20244: 20239: 20234: 20229: 20227:W. V. O. Quine 20224: 20219: 20214: 20209: 20204: 20199: 20194: 20189: 20184: 20179: 20174: 20169: 20164: 20162:Rudolf Steiner 20159: 20154: 20152:Henri Poincaré 20149: 20143: 20140: 20139: 20137: 20136: 20131: 20126: 20121: 20116: 20110: 20108: 20101: 20095: 20094: 20092: 20091: 20086: 20081: 20076: 20071: 20066: 20061: 20056: 20051: 20050: 20049: 20039: 20034: 20029: 20024: 20022:Exact sciences 20019: 20014: 20009: 20003: 20001: 20000:Related topics 19997: 19996: 19994: 19993: 19992: 19991: 19986: 19981: 19976: 19971: 19966: 19959:Social science 19956: 19955: 19954: 19952:Space and time 19944: 19939: 19933: 19931: 19927: 19926: 19924: 19923: 19918: 19913: 19908: 19903: 19898: 19893: 19884: 19879: 19874: 19865: 19856: 19851: 19838: 19833: 19828: 19823: 19818: 19813: 19808: 19803: 19798: 19793: 19788: 19783: 19778: 19773: 19768: 19763: 19758: 19753: 19747: 19745: 19741: 19740: 19738: 19737: 19732: 19731: 19730: 19725: 19715: 19710: 19705: 19704: 19703: 19698: 19693: 19683: 19678: 19673: 19668: 19663: 19661:Scientific law 19658: 19657: 19656: 19646: 19641: 19636: 19631: 19626: 19621: 19616: 19611: 19606: 19599: 19598: 19597: 19592: 19582: 19577: 19572: 19570:Falsifiability 19567: 19562: 19557: 19556: 19555: 19545: 19540: 19535: 19530: 19529: 19528: 19518: 19513: 19508: 19503: 19502: 19501: 19499:Mill's Methods 19491: 19480: 19475: 19469: 19467: 19463: 19462: 19455: 19454: 19447: 19440: 19432: 19423: 19422: 19420: 19419: 19414: 19409: 19404: 19398: 19395: 19394: 19392: 19391: 19374: 19368: 19366: 19362: 19361: 19359: 19358: 19353: 19348: 19343: 19338: 19333: 19328: 19323: 19318: 19313: 19308: 19303: 19301:Mental process 19298: 19293: 19288: 19283: 19278: 19273: 19271:Intentionality 19268: 19267: 19266: 19261: 19251: 19246: 19241: 19236: 19231: 19226: 19221: 19216: 19211: 19206: 19201: 19195: 19193: 19189: 19188: 19186: 19185: 19180: 19175: 19170: 19165: 19164: 19163: 19153: 19148: 19143: 19138: 19133: 19128: 19123: 19121:Neutral monism 19118: 19117: 19116: 19106: 19104:Interactionism 19101: 19096: 19091: 19086: 19081: 19076: 19071: 19065: 19063: 19059: 19058: 19056: 19055: 19048: 19043: 19038: 19033: 19028: 19023: 19018: 19016:Baruch Spinoza 19013: 19008: 19003: 18998: 18993: 18988: 18983: 18978: 18973: 18968: 18963: 18958: 18953: 18948: 18943: 18938: 18933: 18928: 18926:Edmund Husserl 18923: 18918: 18913: 18908: 18903: 18898: 18896:René Descartes 18893: 18891:Daniel Dennett 18888: 18883: 18878: 18873: 18868: 18863: 18861:David Chalmers 18858: 18853: 18848: 18846:Franz Brentano 18843: 18838: 18833: 18828: 18826:Alexander Bain 18823: 18818: 18816:Thomas Aquinas 18813: 18808: 18803: 18797: 18795: 18789: 18788: 18781: 18780: 18773: 18766: 18758: 18749: 18748: 18746: 18745: 18743:Space fountain 18740: 18735: 18730: 18725: 18720: 18715: 18710: 18705: 18700: 18695: 18690: 18684: 18681: 18680: 18673: 18672: 18665: 18658: 18650: 18644: 18641: 18640: 18631: 18630: 18620: 18601: 18567: 18560: 18559: 18558: 18556: 18555:External links 18553: 18551: 18550: 18522: 18498: 18484: 18423: 18398:(4): 629–649. 18380: 18354:(4): 357–363. 18339: 18330: 18304:Roivainen, Eka 18301: 18297:The New Yorker 18289: 18223: 18217: 18204: 18192: 18175: 18166: 18105: 18046: 18039: 18027:The New Yorker 18019: 17989:Cain's Jawbone 17981: 17956: 17924: 17914: 17888: 17858: 17831: 17817: 17791: 17773: 17762: 17760: 17757: 17755: 17754: 17716: 17704: 17666:(7): 596–615. 17651: 17637: 17613: 17554: 17524: 17520:Moral Machines 17515: 17490: 17454: 17429: 17404: 17379: 17359: 17347: 17322: 17286:(3): 189–191. 17271: 17253: 17239: 17206: 17186: 17168: 17153: 17128: 17113: 17107: 17086: 17059: 17018: 16989: 16969: 16956: 16947: 16921: 16903: 16870:(3): 417–457. 16849: 16837: 16787: 16758: 16738: 16718: 16693: 16679: 16661: 16650: 16629: 16604: 16592: 16567: 16512: 16507: 16493:Pinker, Steven 16489: 16483: 16462: 16411: 16399: 16387: 16344: 16314: 16302:(3): 113–126. 16280: 16268: 16239: 16196: 16171: 16153: 16133: 16125:Minsky, Marvin 16121: 16115: 16102: 16056: 16027: 16006:10.1.1.85.8904 15999:(2): 153–164. 15988: 15967:McCarthy, John 15963: 15955:McCarthy, John 15951: 15923:Minsky, Marvin 15919:McCarthy, John 15915: 15905:Minsky, Marvin 15901: 15881: 15859: 15834: 15809: 15793: 15772:10.1.1.83.7615 15765:(4): 151–190. 15754: 15729: 15692: 15680: 15674: 15662:Lenat, Douglas 15658: 15633: 15608: 15588: 15562:Larson, Jeff; 15559: 15547:(3): 275–279. 15530: 15524: 15506: 15478:(4): 369–371. 15463: 15438: 15408: 15388: 15363: 15338: 15316: 15282:; Slovic, D.; 15276: 15258: 15240: 15195: 15169:(2): 170–184. 15158: 15142:igmchicago.org 15133: 15112: 15087: 15069: 15036: 14995: 14989: 14973: 14958: 14928: 14903: 14890: 14874: 14835: 14813: 14800: 14780: 14774: 14753: 14728: 14703: 14693:(3): 413–429. 14682: 14658: 14637:10.1.1.395.416 14619: 14592: 14567: 14561: 14548: 14523: 14505: 14488: 14470: 14452: 14434: 14416: 14410: 14392: 14386: 14366: 14349: 14329: 14304: 14298: 14280: 14255:(3–4): 1–199. 14237: 14229: 14204: 14177: 14163: 14132: 14118: 14099: 14093: 14072: 14058:(3): 200–219. 14038: 14011: 13982: 13959: 13933:Butler, Samuel 13929: 13917: 13882: 13838:Brooks, Rodney 13834: 13821: 13796: 13782: 13773: 13744: 13683: 13645: 13631: 13618: 13594: 13565: 13557: 13553:Machine Ethics 13548: 13530:(4): 477–493. 13519: 13491:Brockman, Greg 13483: 13471: 13459: 13453: 13451: 13448: 13446: 13445: 13439: 13423: 13418: 13402: 13396: 13379: 13377: 13374: 13373: 13372: 13366: 13350: 13344: 13326: 13325: 13307: 13291:Poole, David; 13271: 13245: 13239: 13217: 13199: 13179: 13161: 13136: 13132: 13131: 13125: 13109: 13095: 13064: 13061: 13058: 13057: 13045: 13033: 13021: 13009: 12997: 12984: 12969:Edward Fredkin 12960: 12948:Moravec (1988) 12936: 12924: 12880: 12854: 12828: 12794: 12775: 12746: 12715: 12689: 12675:. Discussion: 12656: 12644: 12632: 12620: 12608: 12604:Dennett (1991) 12596: 12584: 12582:, p. 986. 12572: 12568:Roberts (2016) 12557: 12545: 12510: 12498: 12494:Langley (2011) 12486: 12484:, p. 125. 12482:Crevier (1993) 12474: 12450:Dreyfus (1972) 12438: 12414: 12393: 12381: 12377:Nilsson (1983) 12369: 12344: 12319: 12287: 12275: 12263: 12251: 12239: 12213: 12201: 12186: 12182:Goswami (2023) 12174: 12162: 12131: 12115: 12098: 12082: 12070: 12066:Newquist (1994 12058:Kurzweil (2005 12049: 12025: 12013: 11997: 11985: 11982:Oudeyer (2010) 11958: 11943: 11939:Moravec (1988) 11931: 11919: 11915:Nilsson (1998) 11907: 11895: 11891:Newquist (1994 11867:Expert systems 11859: 11847: 11835: 11823: 11811: 11809:, p. 109) 11795: 11793:, p. 109) 11779: 11767: 11755: 11743: 11739:Crevier (1993) 11731: 11691: 11666: 11652: 11645: 11622: 11607: 11596:on 23 May 2024 11581: 11559: 11529: 11499: 11482: 11470: 11458: 11454:Edwards (2023) 11446: 11420: 11405: 11393: 11381: 11362: 11350: 11346:Vincent (2023) 11335: 11323: 11295: 11273: 11230: 11195:(3): 387–399. 11175: 11134: 11116: 11098: 11072: 11053: 11027: 11008: 10982: 10956: 10930: 10928:, p. 173. 10926:Russell (2019) 10918: 10914:Wallach (2010) 10906: 10894: 10879: 10867: 10852: 10828: 10802: 10776: 10750: 10724: 10698: 10694:Valance (2023) 10686: 10675:. 14 June 2024 10660: 10641: 10611: 10608:Sainato (2015) 10587: 10575: 10563: 10559:Bostrom (2015) 10551:Bostrom (2014) 10543: 10539:Russell (2019) 10531: 10527:Bostrom (2014) 10519: 10507: 10495: 10478: 10471:Mahdawi (2017) 10463: 10451: 10439:Game Developer 10425: 10399: 10379: 10367: 10355: 10340: 10316: 10304: 10289:. 3 May 2019. 10278: 10259: 10247: 10244:Sainato (2015) 10232: 10230:, p. 988. 10220: 10205: 10203:, p. 989. 10193: 10167: 10155: 10143: 10139:Rothman (2020) 10131: 10119: 10107: 10095: 10093:, p. 997) 10079: 10067: 10065:, p. 110. 10055: 10050:"Black Box AI" 10041: 10029: 10017: 10004: 9988: 9986:, p. 65). 9975: 9969:, p. 6); 9951: 9935: 9923: 9911: 9899: 9897:, p. 995. 9884: 9872: 9870:, p. 995) 9848: 9844:Goffrey (2008) 9836: 9824: 9809: 9780: 9768: 9756: 9733: 9721: 9702: 9683: 9664: 9645: 9623: 9604: 9585: 9559: 9540: 9517: 9493: 9468: 9445: 9422: 9410: 9406:Reisner (2023) 9398: 9364: 9338: 9334:Vincent (2022) 9326: 9314: 9302: 9300:, p. 991. 9290: 9278: 9266: 9254: 9252:, p. 987. 9242: 9230: 9191: 9152: 9138: 9116: 9093: 9082:. 24 July 2024 9067: 9060: 9040: 9033: 9005: 8979: 8945: 8919: 8902:Bloomberg News 8888: 8855: 8833: 8800: 8774:Knight, Will. 8766: 8736: 8708: 8695: 8686: 8671: 8659: 8644: 8616: 8595: 8580: 8554: 8511: 8477: 8451: 8396: 8370: 8334: 8308: 8288:The New Yorker 8274: 8224: 8210: 8196: 8139: 8095: 8046: 8027: 8001: 7989: 7977: 7955: 7941: 7929: 7916: 7904: 7887: 7875: 7860: 7858:, p. 785. 7835: 7818: 7816:, p. 751. 7806: 7794: 7782: 7766: 7732: 7716: 7700: 7684: 7677:Cybenko (1988) 7661: 7632: 7628:Domingos (2015 7612: 7610:, p. 152) 7608:Domingos (2015 7592: 7590:, p. 152. 7580: 7578: 7577: 7574:Domingos (2015 7568:Domingos (2015 7544: 7540:Domingos (2015 7532:Decision trees 7524: 7517: 7496: 7479: 7459: 7457:, p. 210) 7455:Domingos (2015 7427: 7425:, p. 210. 7415: 7387: 7375: 7347: 7327: 7317:, sect. 14.4) 7311:Kalman filters 7309:, sect. 14.3) 7285: 7265: 7249: 7225: 7197: 7181: 7170:(8): 109–115. 7152: 7132: 7107: 7091: 7059: 7035: 7033:, chpt. 13–16) 7011: 6999: 6997:, sect. 4.1.2) 6983: 6957: 6937: 6921: 6915:, sect. 3.6), 6907:, sect. 3.5), 6885: 6871:, sect. 3.4), 6845: 6833: 6817: 6815:, chpts. 7–12) 6789: 6777: 6773:Waddell (2018) 6765: 6754:Edelson (1991) 6738: 6734:MIT AIL (2014) 6726: 6714: 6702: 6690: 6678: 6666: 6646: 6634: 6622: 6618:Vincent (2019) 6610: 6590: 6586:Dickson (2022) 6578: 6566: 6549: 6525: 6506: 6481: 6462: 6442: 6419: 6415:word embedding 6387: 6375: 6363: 6335: 6319: 6303: 6287: 6266: 6253: 6237: 6217: 6201: 6199:, p. 528. 6189: 6185:Crevier (1993) 6177: 6175:, p. 296. 6165: 6133: 6070: 6049: 6033: 6009:event calculus 5996: 5951: 5939: 5927: 5923:McGarry (2005) 5915: 5903: 5891: 5879: 5847: 5818: 5793: 5768: 5746:, chpt. 3–5), 5735: 5723: 5712:Goldman (2022) 5693: 5689:Newquist (1994 5657: 5653:Newquist (1994 5613: 5609:Newquist (1994 5565: 5559:, p. 9), 5537: 5532:The proposal: 5505: 5493: 5482:Nilsson (1995) 5454: 5411: 5392: 5374: 5373: 5371: 5368: 5365: 5364: 5338: 5328: 5316: 5299: 5286: 5258: 5242: 5234:Terry Winograd 5230:Logic Theorist 5197: 5181: 5165: 5148: 5139: 5126: 5117: 5109:United Nations 5100: 5091: 5078: 5049: 5032: 5020: 5000:Stuart Dreyfus 4956:Karl Steinbuch 4935: 4922: 4905: 4893: 4889:Ray Solomonoff 4873: 4856: 4852:expert systems 4843: 4840:Nilsson (1998) 4816: 4813:Nilsson (1998) 4788: 4787: 4785: 4782: 4781: 4780: 4774: 4768: 4762: 4756: 4750: 4747:Mind uploading 4744: 4738: 4732: 4723: 4717: 4711: 4705: 4699: 4693: 4687: 4681: 4670: 4667: 4663:Philip K. Dick 4591:The Terminator 4522:Main article: 4519: 4516: 4494:Edward Fredkin 4463: 4460: 4456:S-shaped curve 4417: 4414: 4412: 4409: 4374:self-awareness 4366:AI is sentient 4361: 4358: 4311: 4308: 4286:David Chalmers 4281:Theory of mind 4272: 4269: 4225: 4222: 4202: 4199: 4180:Soft computing 4178:Main article: 4175: 4172: 4152:Main article: 4149: 4146: 4138:explainable AI 4114:Hubert Dreyfus 4091: 4088: 4066: 4063: 3978: 3975: 3970:Main article: 3967: 3964: 3819:mental objects 3796:expert systems 3673:Main article: 3670: 3667: 3658:Bletchley Park 3574: 3571: 3551: 3550: 3544: 3538: 3532: 3516: 3513: 3472: 3469: 3420:Machine ethics 3415: 3412: 3370:Demis Hassabis 3366:Stuart Russell 3343:misinformation 3299:Stuart Russell 3264:Main article: 3261: 3258: 3201: 3198: 3158:misinformation 3117:, however the 3111:United Nations 3060: 3057: 2975:Explainable AI 2970: 2967: 2878:discrimination 2831: 2828: 2811:filter bubbles 2805:, and extreme 2799:misinformation 2773: 2772:Misinformation 2770: 2694: 2691: 2671:Meta Platforms 2650: 2647: 2583:necessary evil 2537: 2534: 2532: 2531:Risks and harm 2529: 2520:Demis Hassabis 2512:Main article: 2509: 2506: 2486:foreign policy 2482:energy storage 2476: 2473: 2447: 2444: 2377:Main article: 2374: 2371: 2339:Main article: 2336: 2333: 2328:World Pensions 2320: 2317: 2287:Alpha Geometry 2278:trained data. 2264:hallucinations 2224: 2221: 2119:Garry Kasparov 2104:Main article: 2101: 2098: 2042:Main article: 2039: 2036: 2016:image labeling 1904:search engines 1896:Main article: 1893: 1890: 1843: 1840: 1797:hallucinations 1785:corpus of text 1773: 1770: 1716: 1713: 1633: 1630: 1614:Kernel methods 1578: 1575: 1553:Kalman filters 1451: 1448: 1289: 1286: 1246:. Variants of 1210: 1207: 1155: 1152: 1139: 1136: 1131: 1128: 1115: 1112: 1070: 1067: 1020: 1017: 985:word embedding 915: 912: 867:classification 848: 845: 766:rational agent 761: 758: 737:knowledge base 709: 706: 681: 678: 672: 669: 663:to ensure the 543:strategy games 423: 422: 420: 419: 412: 405: 397: 394: 393: 390: 389: 383: 380: 379: 376: 375: 372: 371: 366: 361: 356: 350: 345: 344: 341: 340: 337: 336: 331: 326: 321: 316: 307: 302: 297: 291: 286: 285: 282: 281: 278: 277: 272: 267: 262: 257: 256: 255: 245: 240: 235: 234: 233: 228: 223: 213: 208: 206:Earth sciences 203: 198: 196:Bioinformatics 192: 187: 186: 183: 182: 179: 178: 173: 168: 163: 158: 153: 148: 142: 139: 138: 135: 134: 131: 130: 125: 120: 115: 110: 105: 100: 95: 90: 85: 79: 74: 73: 70: 69: 59: 58: 52: 51: 26: 9: 6: 4: 3: 2: 24962: 24951: 24948: 24946: 24943: 24941: 24938: 24936: 24933: 24931: 24928: 24926: 24923: 24921: 24918: 24917: 24915: 24894: 24891: 24889: 24886: 24884: 24881: 24879: 24876: 24874: 24871: 24869: 24866: 24864: 24861: 24859: 24856: 24854: 24851: 24849: 24846: 24844: 24841: 24839: 24836: 24834: 24831: 24829: 24826: 24824: 24821: 24819: 24816: 24814: 24811: 24809: 24806: 24802: 24799: 24797: 24794: 24792: 24789: 24787: 24784: 24782: 24779: 24778: 24776: 24772: 24769: 24767: 24764: 24763: 24761: 24759: 24756: 24754: 24751: 24749: 24746: 24742: 24739: 24737: 24734: 24733: 24731: 24729: 24726: 24724: 24721: 24719: 24716: 24714: 24711: 24709: 24706: 24704: 24701: 24699: 24696: 24694: 24691: 24689: 24686: 24684: 24681: 24679: 24676: 24674: 24671: 24669: 24666: 24664: 24661: 24659: 24656: 24654: 24651: 24649: 24646: 24644: 24641: 24639: 24636: 24635: 24632: 24628: 24624: 24616: 24611: 24609: 24604: 24602: 24597: 24596: 24593: 24581: 24578: 24576: 24573: 24571: 24568: 24566: 24563: 24561: 24558: 24556: 24553: 24551: 24548: 24546: 24545:Ulla Mitzdorf 24543: 24541: 24538: 24536: 24533: 24531: 24528: 24526: 24523: 24521: 24518: 24516: 24515:Robert Trappl 24513: 24511: 24508: 24506: 24503: 24501: 24498: 24496: 24493: 24491: 24488: 24486: 24483: 24481: 24478: 24476: 24473: 24471: 24470:Margaret Mead 24468: 24466: 24463: 24461: 24458: 24456: 24453: 24451: 24450:Kevin Warwick 24448: 24446: 24443: 24441: 24438: 24436: 24433: 24431: 24428: 24426: 24423: 24421: 24420:Jacque Fresco 24418: 24416: 24413: 24411: 24408: 24406: 24403: 24401: 24398: 24396: 24393: 24391: 24388: 24386: 24383: 24381: 24378: 24376: 24373: 24371: 24368: 24366: 24363: 24361: 24358: 24356: 24353: 24351: 24348: 24346: 24343: 24341: 24338: 24336: 24333: 24331: 24328: 24326: 24323: 24321: 24318: 24316: 24313: 24311: 24308: 24306: 24303: 24301: 24298: 24297: 24295: 24293: 24289: 24283: 24280: 24278: 24275: 24273: 24270: 24268: 24265: 24263: 24260: 24258: 24255: 24253: 24250: 24248: 24245: 24243: 24240: 24238: 24235: 24233: 24230: 24228: 24225: 24223: 24220: 24218: 24215: 24213: 24212:Connectionism 24210: 24208: 24205: 24203: 24200: 24198: 24195: 24193: 24190: 24188: 24185: 24183: 24180: 24178: 24175: 24173: 24170: 24169: 24167: 24163: 24159: 24151: 24146: 24144: 24139: 24137: 24132: 24131: 24128: 24118: 24108: 24102: 24099: 24097: 24096: 24092: 24090: 24089: 24085: 24083: 24082: 24081:The Precipice 24078: 24076: 24075: 24071: 24069: 24066: 24064: 24063: 24059: 24057: 24054: 24053: 24051: 24047: 24041: 24038: 24036: 24033: 24031: 24030:Frank Wilczek 24028: 24026: 24023: 24021: 24018: 24016: 24013: 24011: 24008: 24006: 24003: 24001: 23998: 23996: 23993: 23991: 23988: 23986: 23983: 23981: 23978: 23976: 23975:Dan Hendrycks 23973: 23971: 23968: 23966: 23963: 23961: 23958: 23956: 23953: 23951: 23948: 23946: 23945:Yoshua Bengio 23943: 23941: 23938: 23936: 23933: 23932: 23930: 23926: 23920: 23917: 23915: 23912: 23910: 23907: 23905: 23902: 23900: 23897: 23895: 23892: 23890: 23887: 23885: 23882: 23880: 23877: 23875: 23872: 23870: 23867: 23865: 23862: 23860: 23857: 23855: 23852: 23851: 23849: 23847:Organizations 23845: 23839: 23836: 23834: 23831: 23829: 23826: 23824: 23821: 23819: 23816: 23814: 23811: 23809: 23806: 23804: 23801: 23799: 23796: 23794: 23791: 23789: 23786: 23784: 23781: 23779: 23776: 23774: 23771: 23769: 23766: 23764: 23761: 23759: 23756: 23755: 23753: 23749: 23745: 23741: 23734: 23729: 23727: 23722: 23720: 23715: 23714: 23711: 23699: 23698: 23689: 23687: 23686: 23677: 23676: 23673: 23667: 23664: 23662: 23659: 23657: 23654: 23650: 23647: 23646: 23645: 23642: 23640: 23637: 23635: 23632: 23631: 23629: 23625: 23619: 23616: 23614: 23613:Wolf Robotics 23611: 23609: 23606: 23604: 23601: 23599: 23596: 23594: 23591: 23589: 23586: 23584: 23581: 23579: 23576: 23574: 23571: 23569: 23568:Foster-Miller 23566: 23564: 23561: 23559: 23556: 23554: 23551: 23549: 23546: 23544: 23541: 23539: 23536: 23534: 23531: 23529: 23526: 23525: 23523: 23519: 23513: 23510: 23508: 23505: 23503: 23500: 23498: 23495: 23493: 23490: 23488: 23487:Developmental 23485: 23483: 23480: 23478: 23475: 23473: 23470: 23468: 23465: 23463: 23460: 23458: 23455: 23453: 23450: 23449: 23447: 23443: 23437: 23434: 23432: 23429: 23427: 23424: 23422: 23419: 23418: 23416: 23414: 23410: 23406: 23400: 23397: 23395: 23392: 23390: 23387: 23383: 23380: 23379: 23378: 23375: 23373: 23370: 23369: 23367: 23365: 23361: 23353: 23350: 23348: 23345: 23344: 23343: 23340: 23338: 23335: 23333: 23330: 23326: 23323: 23322: 23321: 23318: 23316: 23313: 23311: 23308: 23306: 23303: 23301: 23298: 23294: 23291: 23289: 23286: 23285: 23284: 23281: 23279: 23276: 23274: 23271: 23269: 23266: 23265: 23263: 23259: 23253: 23252:Soft robotics 23250: 23248: 23247:BEAM robotics 23245: 23243: 23240: 23238: 23235: 23233: 23230: 23228: 23225: 23223: 23220: 23218: 23215: 23213: 23210: 23208: 23205: 23203: 23202:Entertainment 23200: 23198: 23195: 23193: 23190: 23186: 23183: 23182: 23181: 23178: 23176: 23173: 23167: 23164: 23163: 23162: 23159: 23158: 23157: 23154: 23152: 23149: 23147: 23144: 23140: 23137: 23135: 23132: 23130: 23127: 23125: 23122: 23121: 23120: 23117: 23115: 23112: 23111: 23109: 23107: 23103: 23098: 23088: 23085: 23083: 23080: 23078: 23075: 23073: 23070: 23068: 23065: 23063: 23060: 23058: 23055: 23053: 23050: 23048: 23045: 23043: 23040: 23039: 23037: 23035:Main articles 23033: 23029: 23022: 23017: 23015: 23010: 23008: 23003: 23002: 22999: 22987: 22986: 22977: 22976: 22973: 22967: 22966:Transhumanism 22964: 22962: 22959: 22957: 22954: 22952: 22949: 22945: 22942: 22940: 22937: 22935: 22932: 22930: 22927: 22925: 22922: 22920: 22917: 22916: 22915: 22912: 22910: 22907: 22905: 22902: 22900: 22897: 22893: 22890: 22889: 22888: 22885: 22883: 22880: 22878: 22875: 22871: 22868: 22866: 22863: 22861: 22858: 22856: 22853: 22852: 22851: 22848: 22846: 22843: 22841: 22838: 22836: 22833: 22831: 22828: 22826: 22823: 22822: 22820: 22816: 22806: 22803: 22801: 22798: 22794: 22793:Chipless RFID 22791: 22790: 22789: 22786: 22784: 22781: 22777: 22774: 22772: 22769: 22767: 22764: 22762: 22759: 22757: 22754: 22752: 22749: 22747: 22744: 22742: 22739: 22737: 22734: 22732: 22729: 22727: 22724: 22723: 22721: 22719: 22716: 22712: 22709: 22707: 22704: 22703: 22702: 22699: 22697: 22694: 22692: 22689: 22687: 22684: 22682: 22679: 22675: 22672: 22670: 22667: 22665: 22662: 22660: 22657: 22655: 22652: 22650: 22647: 22645: 22642: 22641: 22640: 22637: 22633: 22630: 22629: 22628: 22625: 22624: 22622: 22619: 22612: 22609: 22605: 22601: 22594: 22589: 22587: 22582: 22580: 22575: 22574: 22571: 22559: 22551: 22549: 22541: 22539: 22531: 22530: 22527: 22521: 22518: 22516: 22513: 22511: 22508: 22506: 22503: 22501: 22498: 22496: 22493: 22491: 22488: 22486: 22483: 22481: 22478: 22476: 22473: 22471: 22468: 22466: 22463: 22461: 22458: 22456: 22453: 22451: 22448: 22446: 22443: 22441: 22438: 22436: 22433: 22431: 22428: 22426: 22423: 22422: 22420: 22416: 22410: 22407: 22405: 22402: 22400: 22397: 22395: 22394:Mixed reality 22392: 22390: 22387: 22385: 22382: 22380: 22377: 22375: 22372: 22371: 22369: 22367: 22363: 22357: 22354: 22352: 22349: 22347: 22344: 22342: 22339: 22337: 22334: 22333: 22331: 22329: 22325: 22319: 22316: 22314: 22311: 22309: 22306: 22304: 22301: 22299: 22296: 22294: 22291: 22289: 22286: 22284: 22281: 22280: 22278: 22276: 22272: 22266: 22263: 22261: 22258: 22256: 22253: 22251: 22248: 22246: 22243: 22242: 22240: 22238: 22234: 22228: 22227:Accessibility 22225: 22223: 22222:Visualization 22220: 22218: 22215: 22213: 22210: 22208: 22205: 22204: 22202: 22200: 22196: 22190: 22187: 22185: 22182: 22180: 22177: 22175: 22172: 22170: 22167: 22165: 22162: 22160: 22157: 22155: 22152: 22150: 22147: 22146: 22144: 22142: 22138: 22132: 22129: 22127: 22124: 22122: 22119: 22117: 22114: 22112: 22109: 22107: 22104: 22102: 22099: 22097: 22094: 22092: 22089: 22087: 22084: 22082: 22079: 22077: 22074: 22072: 22069: 22067: 22064: 22063: 22061: 22059: 22055: 22049: 22046: 22044: 22041: 22039: 22036: 22034: 22031: 22029: 22026: 22024: 22021: 22019: 22016: 22014: 22011: 22010: 22008: 22006: 22001: 21995: 21992: 21990: 21987: 21985: 21982: 21980: 21977: 21975: 21972: 21971: 21969: 21967: 21963: 21957: 21954: 21952: 21949: 21947: 21944: 21942: 21939: 21937: 21934: 21932: 21929: 21925: 21922: 21921: 21920: 21917: 21916: 21914: 21912: 21908: 21902: 21899: 21897: 21894: 21892: 21889: 21887: 21884: 21882: 21879: 21877: 21874: 21872: 21869: 21867: 21864: 21862: 21859: 21857: 21854: 21853: 21851: 21849: 21845: 21839: 21836: 21834: 21831: 21829: 21826: 21824: 21821: 21819: 21816: 21814: 21811: 21809: 21806: 21804: 21801: 21799: 21796: 21794: 21791: 21790: 21788: 21786: 21782: 21778: 21772: 21769: 21767: 21764: 21762: 21759: 21757: 21754: 21752: 21749: 21748: 21746: 21742: 21736: 21733: 21731: 21728: 21726: 21723: 21721: 21718: 21716: 21713: 21711: 21708: 21707: 21705: 21703: 21699: 21693: 21690: 21688: 21685: 21683: 21682:Dependability 21680: 21678: 21675: 21673: 21670: 21669: 21667: 21663: 21657: 21653: 21650: 21648: 21645: 21643: 21640: 21638: 21635: 21633: 21630: 21628: 21625: 21623: 21620: 21618: 21615: 21613: 21610: 21608: 21605: 21604: 21602: 21600: 21596: 21591: 21585: 21581: 21574: 21569: 21567: 21562: 21560: 21555: 21554: 21551: 21537: 21534: 21532: 21529: 21528: 21521: 21517: 21514: 21512: 21509: 21508: 21505: 21501: 21500: 21497: 21491: 21488: 21486: 21483: 21481: 21478: 21476: 21473: 21471: 21468: 21466: 21463: 21461: 21458: 21456: 21453: 21451: 21448: 21446: 21443: 21441: 21438: 21436: 21433: 21431: 21428: 21426: 21423: 21421: 21418: 21417: 21415: 21413:Architectures 21411: 21405: 21402: 21400: 21397: 21395: 21392: 21390: 21387: 21385: 21382: 21380: 21377: 21375: 21372: 21370: 21367: 21365: 21362: 21361: 21359: 21357:Organizations 21355: 21349: 21346: 21344: 21341: 21339: 21336: 21334: 21331: 21329: 21326: 21324: 21321: 21319: 21316: 21314: 21311: 21309: 21306: 21304: 21301: 21299: 21296: 21294: 21293:Yoshua Bengio 21291: 21290: 21288: 21284: 21274: 21273:Robot control 21271: 21267: 21264: 21263: 21262: 21259: 21257: 21254: 21252: 21249: 21247: 21244: 21242: 21239: 21237: 21234: 21232: 21229: 21227: 21224: 21223: 21221: 21217: 21211: 21208: 21206: 21203: 21201: 21198: 21196: 21193: 21191: 21190:Chinchilla AI 21188: 21186: 21183: 21181: 21178: 21176: 21173: 21171: 21168: 21166: 21163: 21161: 21158: 21156: 21153: 21151: 21148: 21146: 21143: 21141: 21138: 21136: 21133: 21129: 21126: 21125: 21124: 21121: 21119: 21116: 21114: 21111: 21109: 21106: 21104: 21101: 21099: 21096: 21095: 21093: 21089: 21083: 21080: 21076: 21073: 21071: 21068: 21067: 21066: 21063: 21059: 21056: 21054: 21051: 21049: 21046: 21045: 21044: 21041: 21039: 21036: 21034: 21031: 21029: 21026: 21024: 21021: 21019: 21016: 21014: 21011: 21009: 21006: 21004: 21001: 20999: 20996: 20995: 20993: 20989: 20986: 20982: 20976: 20973: 20971: 20968: 20966: 20963: 20961: 20958: 20956: 20953: 20951: 20948: 20946: 20943: 20942: 20940: 20936: 20930: 20927: 20925: 20922: 20920: 20917: 20915: 20912: 20910: 20907: 20906: 20904: 20900: 20892: 20889: 20888: 20887: 20884: 20882: 20879: 20877: 20874: 20870: 20869:Deep learning 20867: 20866: 20865: 20862: 20858: 20855: 20854: 20853: 20850: 20849: 20847: 20843: 20837: 20834: 20832: 20829: 20825: 20822: 20821: 20820: 20817: 20815: 20812: 20808: 20805: 20803: 20800: 20798: 20795: 20794: 20793: 20790: 20788: 20785: 20783: 20780: 20778: 20775: 20773: 20770: 20768: 20765: 20763: 20760: 20758: 20757:Hallucination 20755: 20751: 20748: 20747: 20746: 20743: 20741: 20738: 20734: 20731: 20730: 20729: 20726: 20725: 20723: 20719: 20713: 20710: 20708: 20705: 20703: 20700: 20698: 20695: 20693: 20690: 20688: 20685: 20683: 20680: 20678: 20675: 20673: 20672: 20668: 20667: 20665: 20663: 20659: 20650: 20645: 20643: 20638: 20636: 20631: 20630: 20627: 20615: 20612: 20611: 20609: 20607: 20603: 20597: 20594: 20592: 20589: 20587: 20584: 20582: 20579: 20577: 20574: 20572: 20569: 20567: 20564: 20562: 20559: 20557: 20554: 20552: 20549: 20547: 20544: 20542: 20539: 20537: 20534: 20532: 20529: 20528: 20526: 20522: 20516: 20513: 20511: 20508: 20506: 20503: 20501: 20498: 20497: 20495: 20493: 20489: 20483: 20480: 20478: 20475: 20473: 20472:Cuckoo search 20470: 20468: 20465: 20463: 20460: 20458: 20455: 20454: 20452: 20448: 20442: 20439: 20437: 20434: 20432: 20429: 20427: 20424: 20422: 20419: 20417: 20414: 20412: 20409: 20407: 20404: 20402: 20399: 20397: 20394: 20392: 20389: 20387: 20384: 20383: 20381: 20379: 20375: 20369: 20366: 20364: 20361: 20359: 20356: 20354: 20351: 20349: 20346: 20345: 20343: 20339: 20335: 20328: 20323: 20321: 20316: 20314: 20309: 20308: 20305: 20294: 20289: 20284: 20282: 20272: 20270: 20267: 20264: 20258: 20255: 20253: 20250: 20248: 20245: 20243: 20240: 20238: 20235: 20233: 20230: 20228: 20225: 20223: 20220: 20218: 20215: 20213: 20212:Rudolf Carnap 20210: 20208: 20205: 20203: 20200: 20198: 20195: 20193: 20190: 20188: 20185: 20183: 20180: 20178: 20175: 20173: 20170: 20168: 20165: 20163: 20160: 20158: 20155: 20153: 20150: 20148: 20147:Auguste Comte 20145: 20144: 20135: 20132: 20130: 20127: 20125: 20122: 20120: 20119:Francis Bacon 20117: 20115: 20112: 20111: 20109: 20105: 20102: 20100: 20096: 20090: 20087: 20085: 20082: 20080: 20077: 20075: 20072: 20070: 20067: 20065: 20062: 20060: 20057: 20055: 20052: 20048: 20047:Pseudoscience 20045: 20044: 20043: 20040: 20038: 20035: 20033: 20030: 20028: 20025: 20023: 20020: 20018: 20015: 20013: 20010: 20008: 20005: 20004: 20002: 19998: 19990: 19987: 19985: 19982: 19980: 19977: 19975: 19972: 19970: 19967: 19965: 19962: 19961: 19960: 19957: 19953: 19950: 19949: 19948: 19945: 19943: 19940: 19938: 19935: 19934: 19932: 19928: 19922: 19919: 19917: 19914: 19912: 19909: 19907: 19906:Structuralism 19904: 19902: 19899: 19897: 19894: 19892: 19888: 19885: 19883: 19880: 19878: 19875: 19873: 19869: 19868:Received view 19866: 19864: 19860: 19857: 19855: 19852: 19850: 19846: 19842: 19839: 19837: 19834: 19832: 19829: 19827: 19824: 19822: 19819: 19817: 19814: 19812: 19809: 19807: 19804: 19802: 19799: 19797: 19794: 19792: 19789: 19787: 19784: 19782: 19779: 19777: 19776:Contextualism 19774: 19772: 19769: 19767: 19764: 19762: 19759: 19757: 19754: 19752: 19749: 19748: 19746: 19742: 19736: 19733: 19729: 19726: 19724: 19721: 19720: 19719: 19716: 19714: 19711: 19709: 19706: 19702: 19699: 19697: 19694: 19692: 19689: 19688: 19687: 19684: 19682: 19679: 19677: 19674: 19672: 19669: 19667: 19664: 19662: 19659: 19655: 19652: 19651: 19650: 19647: 19645: 19642: 19640: 19637: 19635: 19632: 19630: 19627: 19625: 19622: 19620: 19617: 19615: 19612: 19610: 19607: 19605: 19604: 19600: 19596: 19593: 19591: 19588: 19587: 19586: 19583: 19581: 19578: 19576: 19573: 19571: 19568: 19566: 19563: 19561: 19558: 19554: 19551: 19550: 19549: 19546: 19544: 19541: 19539: 19536: 19534: 19531: 19527: 19524: 19523: 19522: 19519: 19517: 19514: 19512: 19509: 19507: 19504: 19500: 19497: 19496: 19495: 19492: 19490: 19489: 19485: 19481: 19479: 19476: 19474: 19471: 19470: 19468: 19464: 19460: 19453: 19448: 19446: 19441: 19439: 19434: 19433: 19430: 19418: 19415: 19413: 19410: 19408: 19405: 19403: 19400: 19399: 19396: 19390: 19386: 19382: 19378: 19375: 19373: 19370: 19369: 19367: 19363: 19357: 19354: 19352: 19351:Understanding 19349: 19347: 19344: 19342: 19339: 19337: 19334: 19332: 19329: 19327: 19324: 19322: 19319: 19317: 19314: 19312: 19309: 19307: 19304: 19302: 19299: 19297: 19294: 19292: 19289: 19287: 19284: 19282: 19279: 19277: 19276:Introspection 19274: 19272: 19269: 19265: 19262: 19260: 19257: 19256: 19255: 19252: 19250: 19247: 19245: 19242: 19240: 19237: 19235: 19232: 19230: 19229:Consciousness 19227: 19225: 19222: 19220: 19217: 19215: 19212: 19210: 19207: 19205: 19202: 19200: 19197: 19196: 19194: 19190: 19184: 19181: 19179: 19176: 19174: 19171: 19169: 19166: 19162: 19159: 19158: 19157: 19154: 19152: 19151:Phenomenology 19149: 19147: 19146:Phenomenalism 19144: 19142: 19139: 19137: 19136:Occasionalism 19134: 19132: 19129: 19127: 19124: 19122: 19119: 19115: 19112: 19111: 19110: 19109:Naïve realism 19107: 19105: 19102: 19100: 19099:Functionalism 19097: 19095: 19092: 19090: 19087: 19085: 19082: 19080: 19077: 19075: 19072: 19070: 19067: 19066: 19064: 19060: 19054: 19053: 19049: 19047: 19044: 19042: 19041:Stephen Yablo 19039: 19037: 19034: 19032: 19029: 19027: 19024: 19022: 19019: 19017: 19014: 19012: 19009: 19007: 19004: 19002: 18999: 18997: 18996:Richard Rorty 18994: 18992: 18991:Hilary Putnam 18989: 18987: 18984: 18982: 18979: 18977: 18974: 18972: 18969: 18967: 18966:Marvin Minsky 18964: 18962: 18959: 18957: 18954: 18952: 18949: 18947: 18944: 18942: 18941:Immanuel Kant 18939: 18937: 18934: 18932: 18931:William James 18929: 18927: 18924: 18922: 18919: 18917: 18914: 18912: 18909: 18907: 18904: 18902: 18899: 18897: 18894: 18892: 18889: 18887: 18884: 18882: 18879: 18877: 18874: 18872: 18869: 18867: 18864: 18862: 18859: 18857: 18854: 18852: 18849: 18847: 18844: 18842: 18839: 18837: 18836:Henri Bergson 18834: 18832: 18829: 18827: 18824: 18822: 18819: 18817: 18814: 18812: 18809: 18807: 18804: 18802: 18799: 18798: 18796: 18794: 18790: 18786: 18779: 18774: 18772: 18767: 18765: 18760: 18759: 18756: 18744: 18741: 18739: 18736: 18734: 18731: 18729: 18726: 18724: 18721: 18719: 18716: 18714: 18711: 18709: 18706: 18704: 18703:Frame problem 18701: 18699: 18696: 18694: 18691: 18689: 18686: 18685: 18682: 18678: 18677:John McCarthy 18671: 18666: 18664: 18659: 18657: 18652: 18651: 18648: 18642: 18635: 18628: 18624: 18621: 18617: 18616: 18611: 18607: 18602: 18598: 18597: 18592: 18588: 18587: 18582: 18581: 18580: 18574: 18570: 18536: 18529: 18528: 18523: 18511: 18507: 18503: 18499: 18496: 18492: 18488: 18485: 18473: 18469: 18465: 18461: 18457: 18453: 18449: 18445: 18441: 18437: 18433: 18429: 18424: 18409: 18405: 18401: 18397: 18393: 18386: 18381: 18377: 18373: 18369: 18365: 18361: 18357: 18353: 18349: 18345: 18340: 18337: 18336: 18331: 18327: 18323: 18322: 18317: 18313: 18309: 18305: 18302: 18299: 18298: 18293: 18290: 18287: 18273: 18269: 18265: 18261: 18257: 18253: 18249: 18245: 18241: 18237: 18233: 18229: 18224: 18220: 18214: 18210: 18205: 18202: 18201: 18196: 18193: 18189: 18185: 18181: 18176: 18173: 18172: 18167: 18155: 18151: 18147: 18143: 18139: 18135: 18131: 18127: 18123: 18119: 18115: 18111: 18106: 18102: 18098: 18094: 18090: 18085: 18080: 18076: 18072: 18068: 18064: 18060: 18056: 18052: 18047: 18044: 18040: 18037: 18033: 18029: 18028: 18023: 18020: 18017: 18016:training data 18013: 18012:civilizations 18009: 18005: 18001: 17997: 17996: 17991: 17990: 17985: 17982: 17970: 17966: 17962: 17957: 17954: 17950: 17946: 17942: 17941: 17936: 17932: 17928: 17927:Gleick, James 17925: 17923: 17919: 17915: 17912: 17900: 17899: 17894: 17889: 17884: 17879: 17875: 17871: 17867: 17863: 17859: 17856: 17853: 17849: 17848:Alex Pentland 17845: 17841: 17840: 17835: 17832: 17829: 17825: 17821: 17818: 17806: 17802: 17798: 17794: 17788: 17784: 17783: 17778: 17774: 17771: 17767: 17764: 17763: 17741: 17737: 17733: 17729: 17722: 17717: 17714: 17710: 17705: 17693: 17689: 17685: 17681: 17677: 17673: 17669: 17665: 17661: 17657: 17652: 17649: 17648: 17643: 17638: 17626: 17622: 17618: 17614: 17599: 17595: 17591: 17587: 17583: 17579: 17575: 17571: 17567: 17560: 17555: 17543: 17539: 17534: 17529: 17525: 17521: 17516: 17504: 17500: 17496: 17491: 17479: 17475: 17471: 17467: 17463: 17459: 17458:Vinge, Vernor 17455: 17443: 17439: 17435: 17430: 17418: 17414: 17410: 17405: 17393: 17389: 17385: 17380: 17369: 17365: 17360: 17357: 17353: 17348: 17336: 17332: 17328: 17323: 17319: 17315: 17311: 17307: 17302: 17297: 17293: 17289: 17285: 17281: 17277: 17272: 17260: 17256: 17250: 17246: 17245: 17240: 17237: 17233: 17229: 17225: 17221: 17217: 17216: 17211: 17207: 17196: 17192: 17187: 17175: 17171: 17165: 17161: 17160: 17154: 17142: 17138: 17134: 17129: 17125: 17124: 17119: 17114: 17110: 17104: 17100: 17096: 17092: 17087: 17072: 17065: 17060: 17056: 17036: 17029: 17028: 17023: 17019: 17015: 17011: 17007: 17003: 16999: 16995: 16990: 16979: 16975: 16970: 16966: 16962: 16957: 16953: 16948: 16936: 16932: 16928: 16924: 16918: 16914: 16913: 16908: 16904: 16889: 16885: 16881: 16877: 16873: 16869: 16865: 16858: 16854: 16850: 16846: 16842: 16838: 16834: 16830: 16826: 16822: 16818: 16814: 16809: 16804: 16800: 16796: 16792: 16788: 16784: 16780: 16776: 16772: 16768: 16764: 16759: 16748: 16744: 16739: 16728: 16724: 16719: 16707: 16703: 16699: 16694: 16690: 16686: 16682: 16676: 16672: 16671: 16666: 16662: 16658: 16657: 16651: 16639: 16635: 16630: 16618: 16614: 16613:Distillations 16610: 16605: 16602: 16598: 16593: 16581: 16577: 16573: 16568: 16556: 16552: 16548: 16543: 16538: 16534: 16530: 16526: 16522: 16518: 16513: 16510: 16504: 16500: 16499: 16494: 16490: 16486: 16480: 16476: 16472: 16468: 16463: 16448: 16444: 16440: 16436: 16432: 16428: 16424: 16417: 16412: 16408: 16404: 16400: 16396: 16392: 16388: 16385: 16368: 16364: 16360: 16353: 16349: 16348:Nilsson, Nils 16345: 16334: 16330: 16326: 16325: 16320: 16315: 16310: 16305: 16301: 16297: 16293: 16289: 16285: 16284:Newell, Allen 16281: 16277: 16273: 16272:Nilsson, Nils 16269: 16265: 16261: 16257: 16253: 16250:(1): 82–101. 16249: 16245: 16240: 16233: 16229: 16225: 16221: 16217: 16213: 16209: 16202: 16197: 16185: 16181: 16180:The Economist 16177: 16172: 16160: 16156: 16150: 16145: 16144: 16143:Mind Children 16138: 16137:Moravec, Hans 16134: 16130: 16126: 16122: 16118: 16112: 16108: 16103: 16092: 16088: 16084: 16080: 16076: 16072: 16068: 16064: 16063: 16057: 16053: 16049: 16045: 16041: 16037: 16033: 16028: 16024: 16020: 16016: 16012: 16007: 16002: 15998: 15994: 15989: 15978: 15974: 15973: 15968: 15964: 15961:, p. 171 15960: 15956: 15952: 15940: 15936: 15932: 15928: 15924: 15920: 15916: 15912: 15911: 15906: 15902: 15891: 15887: 15882: 15871: 15867: 15866: 15860: 15848: 15844: 15840: 15835: 15823: 15819: 15815: 15810: 15806: 15802: 15798: 15794: 15790: 15786: 15782: 15778: 15773: 15768: 15764: 15760: 15755: 15743: 15739: 15735: 15730: 15723: 15719: 15715: 15711: 15707: 15700: 15699: 15693: 15689: 15685: 15681: 15677: 15671: 15667: 15663: 15659: 15647: 15643: 15639: 15634: 15630: 15626: 15622: 15618: 15614: 15609: 15598: 15597:Enterprise AI 15594: 15589: 15577: 15573: 15569: 15565: 15564:Angwin, Julia 15560: 15555: 15550: 15546: 15542: 15541: 15536: 15531: 15527: 15521: 15517: 15516: 15511: 15510:Kurzweil, Ray 15507: 15503: 15499: 15494: 15489: 15485: 15481: 15477: 15473: 15469: 15464: 15452: 15448: 15444: 15439: 15427: 15423: 15422: 15417: 15413: 15409: 15397: 15393: 15389: 15377: 15373: 15369: 15364: 15352: 15348: 15344: 15339: 15335: 15331: 15327: 15323: 15319: 15313: 15309: 15305: 15301: 15297: 15293: 15289: 15285: 15284:Tversky, Amos 15281: 15277: 15265: 15261: 15255: 15252:. Macmillan. 15251: 15250: 15245: 15241: 15237: 15233: 15229: 15225: 15221: 15217: 15213: 15209: 15205: 15201: 15196: 15192: 15188: 15184: 15180: 15176: 15172: 15168: 15164: 15159: 15147: 15143: 15139: 15134: 15122: 15118: 15113: 15101: 15097: 15093: 15088: 15084: 15077: 15076: 15070: 15058: 15054: 15050: 15046: 15042: 15037: 15033: 15029: 15025: 15021: 15017: 15013: 15009: 15005: 15001: 14996: 14992: 14986: 14982: 14978: 14974: 14970: 14969: 14964: 14959: 14947: 14943: 14942: 14937: 14933: 14929: 14917: 14913: 14909: 14904: 14900: 14896: 14891: 14887: 14883: 14879: 14875: 14871: 14867: 14863: 14859: 14854: 14849: 14845: 14841: 14836: 14825: 14821: 14820: 14819:Deep Learning 14814: 14811: 14810: 14805: 14801: 14790: 14786: 14781: 14777: 14771: 14767: 14762: 14761: 14754: 14742: 14738: 14734: 14729: 14717: 14713: 14709: 14704: 14700: 14696: 14692: 14688: 14683: 14671: 14667: 14666:The Economist 14663: 14659: 14655: 14651: 14647: 14643: 14638: 14633: 14629: 14625: 14620: 14605: 14598: 14593: 14581: 14577: 14573: 14568: 14564: 14558: 14554: 14549: 14537: 14533: 14529: 14524: 14512: 14508: 14502: 14497: 14496: 14489: 14477: 14473: 14467: 14463: 14462: 14457: 14456:Dyson, George 14453: 14441: 14437: 14431: 14427: 14426: 14421: 14417: 14413: 14407: 14403: 14402: 14397: 14393: 14389: 14383: 14379: 14375: 14371: 14367: 14363: 14359: 14358:Science Alert 14355: 14350: 14339: 14335: 14330: 14318: 14314: 14310: 14305: 14301: 14295: 14291: 14290: 14285: 14281: 14266: 14262: 14258: 14254: 14250: 14243: 14238: 14234: 14230: 14218: 14214: 14210: 14205: 14193: 14189: 14188:Bloomberg.com 14184: 14178: 14174: 14170: 14166: 14160: 14156: 14152: 14147: 14142: 14138: 14133: 14129: 14125: 14121: 14115: 14111: 14109: 14104: 14100: 14096: 14090: 14086: 14082: 14078: 14073: 14061: 14057: 14053: 14052: 14047: 14043: 14039: 14027: 14023: 14022: 14017: 14012: 14008: 14004: 14000: 13996: 13992: 13988: 13983: 13979: 13975: 13971: 13967: 13966: 13960: 13948: 13944: 13943: 13938: 13934: 13930: 13927: 13923: 13918: 13914: 13910: 13905: 13900: 13896: 13892: 13888: 13883: 13876: 13872: 13868: 13863: 13858: 13855:(1–2): 3–15. 13854: 13850: 13843: 13839: 13835: 13831: 13827: 13822: 13810: 13806: 13802: 13797: 13793: 13792: 13787: 13786:Bostrom, Nick 13783: 13779: 13774: 13759: 13752: 13751: 13745: 13741: 13737: 13733: 13729: 13724: 13719: 13715: 13711: 13706: 13705:10.2196/42936 13701: 13697: 13693: 13689: 13684: 13681: 13677: 13672: 13667: 13663: 13659: 13655: 13651: 13646: 13642: 13638: 13634: 13628: 13624: 13619: 13607: 13603: 13599: 13595: 13591: 13587: 13583: 13579: 13575: 13571: 13566: 13563: 13558: 13554: 13549: 13545: 13541: 13537: 13533: 13529: 13525: 13520: 13508: 13504: 13500: 13496: 13492: 13488: 13484: 13481: 13477: 13472: 13470: 13466: 13463: 13460: 13458: 13455: 13454: 13450:Other sources 13442: 13436: 13432: 13428: 13424: 13421: 13419:1-5688-1205-1 13415: 13411: 13407: 13403: 13399: 13397:0-465-02997-3 13393: 13389: 13385: 13381: 13380: 13376:History of AI 13369: 13363: 13359: 13355: 13351: 13347: 13341: 13337: 13332: 13331: 13330: 13314: 13310: 13304: 13300: 13299: 13294: 13278: 13274: 13268: 13264: 13263: 13258: 13257:Goebel, Randy 13254: 13250: 13246: 13242: 13240:0-13-790395-2 13236: 13232: 13231: 13226: 13225:Norvig, Peter 13222: 13218: 13206: 13202: 13196: 13191: 13190: 13184: 13183:Nilsson, Nils 13180: 13168: 13164: 13158: 13153: 13152: 13146: 13142: 13141:Luger, George 13138: 13137: 13135: 13128: 13122: 13118: 13114: 13110: 13106: 13102: 13098: 13092: 13088: 13087: 13082: 13081:Norvig, Peter 13078: 13074: 13073: 13072: 13070: 13069:Open Syllabus 13054: 13053:Galvan (1997) 13049: 13042: 13037: 13030: 13025: 13018: 13013: 13006: 13001: 12994: 12988: 12982: 12978: 12977:Butler (1863) 12974: 12971:is quoted in 12970: 12964: 12957: 12953: 12949: 12945: 12944:Transhumanism 12940: 12933: 12928: 12922: 12918: 12914: 12910: 12906: 12902: 12898: 12894: 12890: 12884: 12869: 12865: 12858: 12843: 12839: 12832: 12817: 12813: 12809: 12805: 12798: 12790: 12786: 12779: 12764: 12760: 12753: 12751: 12735: 12731: 12724: 12722: 12720: 12704: 12703:The Spectator 12700: 12693: 12686: 12685:Crevier (1993 12682: 12678: 12674: 12673:Searle (1999) 12670: 12669:Searle (1980) 12666: 12660: 12653: 12648: 12641: 12640:Searle (1980) 12636: 12629: 12628:Searle (1999) 12624: 12617: 12612: 12605: 12600: 12593: 12588: 12581: 12576: 12569: 12564: 12562: 12554: 12549: 12543: 12539: 12538:Minsky (1986) 12535: 12531: 12530:Nilsson (1983 12527: 12526:Crevier (1993 12523: 12519: 12514: 12507: 12502: 12495: 12490: 12483: 12478: 12471: 12467: 12463: 12459: 12458:Crevier (1993 12455: 12451: 12447: 12442: 12435: 12431: 12427: 12426:Moravec (1988 12423: 12418: 12412:, p. 19) 12411: 12407: 12403: 12397: 12390: 12385: 12379:, p. 10. 12378: 12373: 12358: 12354: 12348: 12333: 12329: 12323: 12307: 12303: 12302: 12297: 12291: 12284: 12283:Minsky (1986) 12279: 12272: 12267: 12260: 12255: 12248: 12243: 12228: 12224: 12217: 12210: 12209:Turing (1950) 12205: 12198: 12197:Turing (1950) 12193: 12191: 12183: 12178: 12171: 12166: 12150: 12146: 12142: 12135: 12129:, p. 26) 12128: 12124: 12119: 12112: 12111:Clark (2015b) 12107: 12105: 12103: 12095: 12091: 12086: 12079: 12074: 12067: 12063: 12059: 12053: 12046: 12042: 12038: 12034: 12029: 12023:, p. 26. 12022: 12017: 12010: 12006: 12005:Crevier (1993 12001: 11995:, p. 25. 11994: 11989: 11983: 11979: 11975: 11971: 11967: 11962: 11955: 11954:Brooks (1990) 11950: 11948: 11940: 11935: 11928: 11923: 11916: 11911: 11905:, p. 24. 11904: 11899: 11892: 11888: 11887:Crevier (1993 11884: 11880: 11879:Nilsson (1998 11876: 11872: 11868: 11863: 11857:, p. 22. 11856: 11851: 11844: 11839: 11832: 11827: 11821:, p. 21. 11820: 11815: 11808: 11807:Crevier (1993 11804: 11799: 11792: 11791:Crevier (1993 11788: 11783: 11776: 11771: 11765:, p. 18. 11764: 11759: 11753:, p. 17. 11752: 11747: 11740: 11735: 11728: 11724: 11720: 11719:Crevier (1993 11716: 11712: 11711:Turing (1950) 11708: 11704: 11698: 11696: 11688: 11687:Moravec (1988 11684: 11680: 11679:Crevier (1993 11676: 11670: 11662: 11656: 11648: 11646:0-1982-5079-7 11642: 11638: 11631: 11629: 11627: 11619: 11614: 11612: 11595: 11591: 11585: 11569: 11563: 11547: 11543: 11539: 11533: 11517: 11513: 11509: 11503: 11495: 11494: 11486: 11479: 11474: 11467: 11462: 11455: 11450: 11434: 11430: 11424: 11416: 11409: 11402: 11397: 11390: 11385: 11378: 11377:UNESCO (2021) 11373: 11371: 11369: 11367: 11359: 11354: 11347: 11342: 11340: 11332: 11327: 11321: 11320:Buiten (2019) 11317: 11313: 11309: 11305: 11299: 11283: 11277: 11269: 11265: 11261: 11257: 11253: 11249: 11245: 11241: 11234: 11226: 11222: 11218: 11214: 11210: 11206: 11202: 11198: 11194: 11190: 11186: 11179: 11171: 11167: 11162: 11157: 11153: 11149: 11145: 11138: 11127: 11120: 11109: 11102: 11087: 11083: 11076: 11068: 11064: 11057: 11042: 11038: 11031: 11023: 11019: 11012: 10997: 10993: 10986: 10971: 10967: 10960: 10945: 10941: 10934: 10927: 10922: 10915: 10910: 10903: 10898: 10891: 10886: 10884: 10876: 10871: 10864: 10859: 10857: 10850: 10846: 10842: 10838: 10837:Brooks (2014) 10832: 10817: 10813: 10806: 10791: 10787: 10780: 10765: 10761: 10754: 10739: 10735: 10728: 10713: 10709: 10702: 10695: 10690: 10674: 10673:Bloomberg BNN 10670: 10664: 10656: 10652: 10645: 10629: 10625: 10621: 10615: 10609: 10605: 10601: 10600:Holley (2015) 10597: 10591: 10584: 10579: 10572: 10571:Harari (2023) 10567: 10560: 10556: 10552: 10547: 10540: 10535: 10528: 10523: 10516: 10511: 10504: 10499: 10491: 10490: 10482: 10476: 10472: 10467: 10460: 10455: 10440: 10436: 10429: 10414: 10413:Rest of World 10410: 10403: 10397:, p. 33) 10396: 10392: 10388: 10383: 10377:, p. 33. 10376: 10371: 10364: 10359: 10353: 10349: 10344: 10337: 10333: 10329: 10323: 10321: 10313: 10308: 10292: 10288: 10282: 10274: 10270: 10263: 10256: 10255:Harari (2018) 10251: 10245: 10241: 10236: 10229: 10224: 10217: 10212: 10210: 10202: 10197: 10182: 10178: 10171: 10164: 10159: 10152: 10147: 10140: 10135: 10128: 10123: 10117:, p. 83. 10116: 10111: 10105:, p. 91. 10104: 10099: 10092: 10088: 10083: 10076: 10071: 10064: 10059: 10051: 10045: 10038: 10037:Sample (2017) 10033: 10026: 10021: 10015:, p. 80) 10014: 10008: 10001: 9997: 9992: 9985: 9979: 9972: 9968: 9964: 9960: 9955: 9948: 9944: 9939: 9932: 9927: 9920: 9915: 9908: 9903: 9896: 9891: 9889: 9882:, p. 25. 9881: 9876: 9869: 9865: 9861: 9860:Goffrey (2008 9857: 9852: 9846:, p. 17. 9845: 9840: 9833: 9828: 9821: 9816: 9814: 9798: 9794: 9787: 9785: 9777: 9772: 9765: 9760: 9752: 9748: 9744: 9737: 9730: 9725: 9717: 9713: 9706: 9698: 9694: 9687: 9679: 9675: 9668: 9660: 9656: 9649: 9641: 9640:Goldman Sachs 9634: 9627: 9619: 9615: 9608: 9600: 9596: 9589: 9573: 9569: 9563: 9555: 9551: 9544: 9536: 9532: 9528: 9521: 9513: 9509: 9508:The Economist 9504: 9497: 9489: 9485: 9480: 9472: 9464: 9460: 9456: 9449: 9441: 9440: 9432: 9426: 9419: 9414: 9407: 9402: 9387: 9383: 9379: 9375: 9368: 9353: 9349: 9342: 9335: 9330: 9324:, p. 63. 9323: 9318: 9311: 9306: 9299: 9294: 9287: 9282: 9275: 9270: 9263: 9258: 9251: 9246: 9239: 9234: 9226: 9222: 9218: 9214: 9210: 9206: 9202: 9195: 9187: 9183: 9179: 9175: 9171: 9167: 9163: 9156: 9141: 9135: 9131: 9127: 9120: 9112: 9108: 9104: 9097: 9081: 9077: 9071: 9063: 9057: 9053: 9052: 9044: 9036: 9030: 9026: 9022: 9018: 9017: 9009: 8994: 8990: 8983: 8968: 8964: 8960: 8956: 8949: 8934: 8930: 8923: 8907: 8903: 8899: 8892: 8876: 8872: 8871: 8866: 8859: 8850: 8845: 8837: 8818: 8811: 8804: 8789: 8785: 8781: 8777: 8770: 8762: 8758: 8754: 8750: 8743: 8741: 8734: 8726: 8725: 8717: 8715: 8713: 8705: 8699: 8690: 8683: 8682: 8675: 8668: 8663: 8656: 8654: 8648: 8633: 8632: 8627: 8620: 8611: 8606: 8599: 8592: 8591: 8584: 8569: 8568:New Scientist 8565: 8558: 8550: 8546: 8542: 8538: 8534: 8530: 8526: 8522: 8515: 8500: 8496: 8492: 8488: 8481: 8465: 8461: 8455: 8447: 8443: 8439: 8435: 8431: 8427: 8423: 8419: 8415: 8411: 8407: 8400: 8385: 8381: 8374: 8359: 8355: 8351: 8346: 8338: 8323: 8319: 8312: 8297: 8293: 8289: 8285: 8278: 8270: 8266: 8261: 8256: 8252: 8248: 8244: 8240: 8236: 8233:April 2024). 8228: 8220: 8214: 8206: 8200: 8192: 8188: 8183: 8178: 8174: 8170: 8166: 8162: 8158: 8154: 8150: 8143: 8135: 8131: 8126: 8121: 8117: 8113: 8109: 8102: 8100: 8091: 8087: 8082: 8077: 8073: 8069: 8065: 8061: 8057: 8050: 8042: 8038: 8031: 8016: 8012: 8005: 7998: 7993: 7986: 7981: 7965: 7959: 7951: 7945: 7938: 7933: 7927:, p. 22) 7926: 7920: 7913: 7908: 7901: 7896: 7894: 7892: 7884: 7879: 7872: 7867: 7865: 7857: 7852: 7850: 7848: 7846: 7844: 7842: 7840: 7833:, p. 17. 7832: 7827: 7825: 7823: 7815: 7810: 7803: 7798: 7791: 7786: 7780:, sect. 21.3) 7779: 7775: 7770: 7764: 7760: 7758: 7752: 7749:, chpt. 21), 7748: 7744: 7743:Deep learning 7739: 7737: 7729: 7725: 7720: 7714:, sect. 21.6) 7713: 7709: 7704: 7698:, sect. 21.1) 7697: 7693: 7688: 7682: 7678: 7674: 7670: 7665: 7658: 7657:Nilsson (1998 7654: 7650: 7646: 7642: 7636: 7629: 7626:, chpt. 21), 7625: 7619: 7617: 7609: 7605: 7601: 7596: 7589: 7584: 7575: 7572: 7571: 7569: 7565: 7561: 7557: 7553: 7548: 7542:, p. 88) 7541: 7537: 7533: 7528: 7520: 7514: 7510: 7506: 7500: 7493: 7489: 7483: 7477:, sect. 16.5) 7476: 7472: 7469:and Bayesian 7468: 7463: 7456: 7453:, chpt. 20), 7452: 7451:Nilsson (1998 7448: 7445:, chpt. 20), 7444: 7440: 7436: 7431: 7424: 7419: 7412: 7411:Nilsson (1998 7408: 7404: 7400: 7396: 7391: 7384: 7379: 7372: 7371:Nilsson (1998 7368: 7364: 7360: 7356: 7351: 7344: 7340: 7336: 7331: 7325:, sect. 14.5) 7324: 7320: 7316: 7312: 7308: 7304: 7300: 7294: 7292: 7290: 7282: 7278: 7274: 7269: 7263:, sect. 16.6) 7262: 7258: 7253: 7246: 7242: 7238: 7234: 7229: 7222: 7221:Nilsson (1998 7218: 7214: 7210: 7204: 7202: 7195: 7191: 7188:Fuzzy logic: 7185: 7177: 7173: 7169: 7165: 7164: 7156: 7149: 7145: 7141: 7136: 7129: 7128:Nilsson (1998 7125: 7121: 7117: 7111: 7104: 7100: 7095: 7088: 7087:Nilsson (1998 7084: 7080: 7076: 7072: 7068: 7063: 7056: 7055:Nilsson (1998 7052: 7048: 7044: 7039: 7032: 7031:Nilsson (1998 7028: 7024: 7020: 7015: 7008: 7003: 6996: 6992: 6987: 6972: 6968: 6961: 6954: 6950: 6946: 6941: 6934: 6930: 6925: 6918: 6914: 6910: 6906: 6902: 6898: 6894: 6889: 6882: 6881:Nilsson (1998 6878: 6874: 6870: 6866: 6862: 6858: 6854: 6849: 6843:, sect. 11.2. 6842: 6837: 6830: 6826: 6821: 6814: 6813:Nilsson (1998 6810: 6806: 6802: 6798: 6793: 6786: 6781: 6774: 6769: 6763: 6759: 6755: 6751: 6747: 6742: 6735: 6730: 6723: 6718: 6711: 6706: 6699: 6694: 6687: 6682: 6675: 6670: 6663: 6662:Nilsson (1998 6660:, chpt. 25), 6659: 6655: 6650: 6643: 6638: 6631: 6626: 6619: 6614: 6608: 6605:, chpt. 24), 6604: 6600: 6594: 6587: 6582: 6575: 6570: 6563: 6559: 6553: 6546: 6542: 6538: 6534: 6529: 6523: 6519: 6515: 6510: 6495: 6491: 6485: 6479: 6475: 6471: 6466: 6459: 6456:, chpt. 22), 6455: 6451: 6446: 6439: 6435: 6431: 6426: 6424: 6416: 6412: 6408: 6404: 6400: 6396: 6391: 6384: 6379: 6372: 6371:Turing (1950) 6367: 6360: 6359:Nilsson (1998 6356: 6352: 6348: 6344: 6339: 6332: 6328: 6323: 6316: 6312: 6307: 6300: 6296: 6291: 6284: 6280: 6276: 6270: 6263: 6257: 6250: 6246: 6241: 6234: 6230: 6226: 6221: 6214: 6210: 6205: 6198: 6193: 6186: 6181: 6174: 6169: 6162: 6158: 6154: 6153:Moravec (1988 6150: 6149:Crevier (1993 6146: 6140: 6138: 6130: 6126: 6122: 6121:Nilsson (1998 6118: 6114: 6110: 6106: 6102: 6098: 6094: 6090: 6089:default logic 6086: 6085:Frame problem 6082: 6077: 6075: 6067: 6063: 6059: 6053: 6046: 6042: 6037: 6031:, chpt. 18.2) 6030: 6029:Nilsson (1998 6026: 6022: 6018: 6017:frame problem 6014: 6010: 6006: 6000: 5994:, chpt. 18.3) 5993: 5992:Nilsson (1998 5989: 5985: 5981: 5977: 5973: 5969: 5965: 5961: 5955: 5948: 5943: 5936: 5931: 5924: 5919: 5912: 5907: 5900: 5895: 5888: 5883: 5876: 5875:Nilsson (1998 5872: 5868: 5865:, chpt. 10), 5864: 5860: 5856: 5851: 5845: 5841: 5837: 5833: 5827: 5825: 5823: 5816:, p. 21) 5815: 5811: 5807: 5802: 5800: 5798: 5791:, chpt. 7–12) 5790: 5789:Nilsson (1998 5786: 5782: 5778: 5772: 5766:, chpt. 7–12) 5765: 5764:Nilsson (1998 5761: 5757: 5753: 5749: 5745: 5739: 5732: 5727: 5721: 5717: 5713: 5709: 5705: 5704:Deep learning 5700: 5698: 5690: 5686: 5682: 5681:Crevier (1993 5678: 5674: 5670: 5664: 5662: 5654: 5650: 5646: 5642: 5638: 5637:Crevier (1993 5634: 5630: 5626: 5620: 5618: 5610: 5606: 5602: 5598: 5597:Crevier (1993 5594: 5590: 5586: 5582: 5578: 5572: 5570: 5562: 5558: 5557:Moravec (1988 5554: 5553:Crevier (1993 5550: 5544: 5542: 5535: 5529: 5525: 5521: 5517: 5512: 5510: 5502: 5497: 5491: 5487: 5483: 5478: 5472: 5468: 5463: 5461: 5459: 5450: 5446: 5442: 5438: 5434: 5430: 5426: 5422: 5415: 5408: 5404: 5401: 5396: 5389: 5384: 5382: 5380: 5375: 5361: 5357: 5353: 5349: 5342: 5332: 5325: 5320: 5313: 5309: 5303: 5296: 5290: 5283: 5279: 5275: 5274:Rodney Brooks 5271: 5267: 5262: 5255: 5251: 5246: 5239: 5235: 5231: 5227: 5223: 5219: 5215: 5214:Daniel Bobrow 5211: 5207: 5206:Arthur Samuel 5201: 5194: 5190: 5185: 5178: 5174: 5169: 5162: 5158: 5152: 5143: 5136: 5135:robopocalypse 5130: 5121: 5114: 5110: 5104: 5095: 5088: 5082: 5075: 5071: 5067: 5063: 5059: 5058:Jon Kleinberg 5053: 5046: 5042: 5036: 5029: 5024: 5017: 5013: 5009: 5005: 5001: 4997: 4993: 4989: 4985: 4981: 4977: 4976:Valentin Lapa 4973: 4969: 4965: 4961: 4957: 4953: 4949: 4945: 4939: 4932: 4926: 4919: 4915: 4909: 4903: 4897: 4890: 4886: 4882: 4877: 4870: 4866: 4860: 4853: 4847: 4841: 4837: 4833: 4829: 4823: 4821: 4814: 4810: 4806: 4802: 4796: 4794: 4789: 4778: 4775: 4772: 4769: 4766: 4763: 4760: 4757: 4754: 4751: 4748: 4745: 4742: 4739: 4736: 4733: 4727: 4724: 4721: 4718: 4715: 4712: 4709: 4706: 4703: 4700: 4697: 4694: 4691: 4688: 4685: 4682: 4676: 4675:AI Convention 4673: 4672: 4666: 4664: 4660: 4659: 4654: 4653: 4648: 4647: 4642: 4641: 4636: 4632: 4627: 4625: 4621: 4617: 4613: 4611: 4610: 4605: 4604: 4599: 4598: 4593: 4592: 4587: 4586: 4585:Discovery One 4581: 4577: 4574: 4570: 4566: 4565: 4560: 4556: 4551: 4549: 4541: 4540: 4535: 4530: 4525: 4515: 4513: 4512: 4507: 4503: 4499: 4498:Samuel Butler 4495: 4491: 4489: 4485: 4484:Aldous Huxley 4481: 4477: 4473: 4472:Kevin Warwick 4469: 4462:Transhumanism 4459: 4457: 4452: 4450: 4446: 4442: 4438: 4434: 4430: 4425: 4423: 4408: 4406: 4402: 4398: 4395:analogous to 4394: 4389: 4387: 4381: 4379: 4375: 4371: 4367: 4357: 4355: 4351: 4346: 4344: 4343:Hilary Putnam 4340: 4336: 4331: 4325: 4321: 4317: 4307: 4305: 4300: 4296: 4292: 4287: 4282: 4278: 4271:Consciousness 4268: 4266: 4261: 4257: 4253: 4252:mental states 4249: 4248:consciousness 4245: 4241: 4235: 4231: 4221: 4218: 4212: 4208: 4198: 4195: 4191: 4187: 4181: 4171: 4169: 4165: 4161: 4155: 4145: 4143: 4139: 4135: 4131: 4127: 4122: 4119: 4115: 4111: 4106: 4104: 4100: 4096: 4087: 4085: 4081: 4077: 4072: 4062: 4060: 4054: 4050: 4047: 4046:Marvin Minsky 4042: 4040: 4039:John McCarthy 4037:" AI founder 4032: 4028: 4024: 4020: 4012: 4008: 4006: 4001: 3996: 3992: 3988: 3984: 3973: 3963: 3961: 3957: 3953: 3949: 3945: 3941: 3937: 3933: 3928: 3926: 3921: 3916: 3914: 3910: 3906: 3902: 3898: 3893: 3892:Deep learning 3889: 3887: 3883: 3879: 3875: 3871: 3866: 3864: 3860: 3856: 3852: 3851:connectionism 3848: 3844: 3840: 3839:Rodney Brooks 3836: 3832: 3828: 3824: 3820: 3817:to represent 3816: 3811: 3809: 3805: 3801: 3797: 3792: 3790: 3786: 3782: 3781: 3776: 3772: 3768: 3764: 3760: 3755: 3754:Marvin Minsky 3751: 3750:Herbert Simon 3747: 3742: 3740: 3736: 3732: 3728: 3723: 3721: 3717: 3713: 3709: 3705: 3701: 3697: 3693: 3689: 3682: 3676: 3666: 3664: 3659: 3655: 3650: 3647: 3643: 3639: 3634: 3632: 3628: 3623: 3619: 3615: 3611: 3607: 3598: 3593: 3588: 3584: 3580: 3570: 3567: 3562: 3558: 3556: 3548: 3545: 3542: 3539: 3536: 3533: 3530: 3527: 3526: 3525: 3523: 3512: 3510: 3506: 3502: 3498: 3494: 3490: 3486: 3482: 3478: 3468: 3466: 3462: 3458: 3453: 3451: 3445: 3443: 3437: 3433: 3429: 3425: 3421: 3411: 3409: 3405: 3400: 3395: 3393: 3388: 3386: 3382: 3379:In May 2023, 3377: 3375: 3371: 3367: 3363: 3362:Yoshua Bengio 3359: 3355: 3351: 3346: 3344: 3340: 3336: 3332: 3328: 3324: 3320: 3316: 3311: 3309: 3305: 3300: 3296: 3292: 3288: 3284: 3279: 3277: 3273: 3267: 3257: 3255: 3250: 3248: 3243: 3242: 3241:The Economist 3236: 3233: 3229: 3228:redistributed 3225: 3221: 3215: 3211: 3207: 3197: 3193: 3191: 3187: 3183: 3179: 3175: 3171: 3167: 3166:generative AI 3163: 3159: 3155: 3151: 3147: 3143: 3139: 3135: 3131: 3127: 3122: 3120: 3119:United States 3116: 3112: 3108: 3104: 3098: 3096: 3092: 3088: 3084: 3080: 3074: 3070: 3066: 3056: 3054: 3050: 3046: 3042: 3038: 3034: 3033:Deconvolution 3030: 3024: 3022: 3018: 3014: 3011: 3005: 3002: 2996: 2994: 2990: 2984: 2980: 2976: 2966: 2964: 2960: 2955: 2953: 2948: 2942: 2939: 2937: 2933: 2927: 2923: 2920: 2916: 2912: 2908: 2904: 2900: 2896: 2894: 2890: 2889:Google Photos 2885: 2883: 2879: 2875: 2871: 2867: 2863: 2859: 2855: 2851: 2850:training data 2847: 2841: 2837: 2827: 2825: 2820: 2819:generative AI 2815: 2812: 2808: 2804: 2800: 2796: 2792: 2788: 2784: 2779: 2769: 2767: 2762: 2758: 2753: 2748: 2744: 2740: 2735: 2732: 2729:In 2024, the 2727: 2725: 2721: 2720:Goldman Sachs 2716: 2712: 2710: 2706: 2700: 2690: 2688: 2684: 2680: 2676: 2672: 2668: 2664: 2660: 2659:Alphabet Inc. 2656: 2646: 2644: 2643: 2638: 2634: 2630: 2626: 2621: 2619: 2615: 2611: 2610:Cynthia Dwork 2607: 2603: 2599: 2594: 2592: 2588: 2584: 2580: 2576: 2572: 2567: 2563: 2561: 2557: 2553: 2547: 2543: 2528: 2525: 2521: 2515: 2505: 2501: 2497: 2494: 2489: 2487: 2483: 2472: 2470: 2466: 2462: 2458: 2454: 2443: 2441: 2437: 2433: 2429: 2425: 2421: 2417: 2413: 2412:text-to-image 2409: 2404: 2402: 2398: 2394: 2393:generative AI 2385: 2380: 2373:Generative AI 2370: 2367: 2366:Kamala Harris 2362: 2360: 2356: 2352: 2348: 2342: 2332: 2329: 2325: 2316: 2313: 2311: 2306: 2304: 2300: 2296: 2292: 2288: 2284: 2279: 2276: 2272: 2269: 2265: 2261: 2260: 2259:Mistral Large 2255: 2254: 2249: 2248: 2243: 2242: 2237: 2235: 2230: 2220: 2218: 2213: 2209: 2205: 2201: 2197: 2193: 2189: 2185: 2181: 2177: 2173: 2169: 2165: 2161: 2157: 2153: 2149: 2145: 2141: 2137: 2133: 2129: 2126: 2125: 2120: 2116: 2112: 2107: 2097: 2095: 2091: 2087: 2083: 2078: 2074: 2070: 2066: 2061: 2059: 2055: 2051: 2045: 2035: 2033: 2029: 2025: 2021: 2017: 2013: 2009: 2005: 2001: 1997: 1993: 1989: 1985: 1981: 1977: 1973: 1969: 1965: 1961: 1957: 1953: 1949: 1945: 1941: 1937: 1933: 1929: 1925: 1921: 1917: 1913: 1909: 1908:Google Search 1905: 1899: 1889: 1887: 1883: 1879: 1875: 1871: 1867: 1863: 1859: 1853: 1849: 1839: 1837: 1833: 1829: 1825: 1821: 1817: 1813: 1809: 1804: 1802: 1798: 1794: 1790: 1786: 1782: 1778: 1769: 1767: 1763: 1759: 1755: 1751: 1747: 1743: 1739: 1734: 1732: 1728: 1727:Deep learning 1721: 1715:Deep learning 1712: 1710: 1706: 1702: 1698: 1694: 1690: 1686: 1681: 1679: 1678:find patterns 1675: 1671: 1666: 1664: 1659: 1655: 1647: 1643: 1638: 1629: 1627: 1623: 1619: 1615: 1611: 1607: 1606:decision tree 1602: 1600: 1596: 1592: 1588: 1584: 1571: 1567: 1564: 1560: 1556: 1554: 1550: 1546: 1541: 1539: 1535: 1531: 1527: 1523: 1519: 1515: 1511: 1507: 1503: 1501: 1497: 1493: 1489: 1485: 1481: 1477: 1473: 1465: 1461: 1456: 1447: 1445: 1441: 1437: 1433: 1431: 1427: 1425: 1421: 1417: 1413: 1409: 1405: 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714: 705: 701: 699: 695: 691: 687: 677: 668: 666: 662: 658: 654: 650: 646: 642: 641:deep learning 638: 633: 631: 627: 623: 619: 615: 611: 607: 603: 599: 595: 591: 587: 583: 579: 575: 571: 567: 563: 558: 556: 552: 548: 544: 540: 536: 532: 529:tools (e.g., 528: 524: 520: 516: 512: 508: 504: 500: 496: 492: 488: 484: 480: 479:Google Search 476: 472: 467: 465: 461: 457: 453: 449: 445: 441: 438:exhibited by 437: 433: 429: 418: 413: 411: 406: 404: 399: 398: 396: 395: 388: 385: 384: 378: 377: 370: 367: 365: 362: 360: 357: 355: 352: 351: 348: 343: 342: 335: 332: 330: 327: 325: 322: 320: 317: 315: 311: 308: 306: 303: 301: 298: 296: 293: 292: 289: 284: 283: 276: 273: 271: 268: 266: 263: 261: 258: 254: 253:Mental health 251: 250: 249: 246: 244: 241: 239: 236: 232: 229: 227: 224: 222: 219: 218: 217: 216:Generative AI 214: 212: 209: 207: 204: 202: 199: 197: 194: 193: 190: 185: 184: 177: 174: 172: 169: 167: 164: 162: 159: 157: 156:Deep learning 154: 152: 149: 147: 144: 143: 137: 136: 129: 126: 124: 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19891:Anti-realism 19889: / 19870: / 19861: / 19847: / 19845:Reductionism 19843: / 19816:Inductionism 19796:Evolutionism 19601: 19488:a posteriori 19487: 19483: 19387: / 19383: / 19379: / 19296:Mental image 19291:Mental event 19258: 19254:Intelligence 19204:Chinese room 19050: 19001:Gilbert Ryle 18981:Derek Parfit 18971:Thomas Nagel 18901:Fred Dretske 18821:J. L. Austin 18793:Philosophers 18687: 18626: 18613: 18594: 18577: 18576: 18575:profile for 18572: 18542:. Retrieved 18526: 18514:. Retrieved 18505: 18495:transformers 18476:. Retrieved 18435: 18431: 18417:12 September 18415:. Retrieved 18395: 18391: 18351: 18347: 18333: 18319: 18312:intelligence 18306:, "AI's IQ: 18295: 18276:. Retrieved 18235: 18231: 18208: 18198: 18195:Marcus, Gary 18183: 18169: 18158:. Retrieved 18117: 18113: 18058: 18054: 18045:, MIT Press. 18042: 18025: 18014:to serve as 17993: 17987: 17973:. Retrieved 17964: 17938: 17934: 17917: 17909: 17902:. Retrieved 17898:The Diplomat 17896: 17873: 17870:Teknokultura 17869: 17862:Evans, Woody 17844:George Dyson 17837: 17823: 17809:. Retrieved 17781: 17769: 17749:24 September 17747:, retrieved 17727: 17713:The Atlantic 17712: 17696:. Retrieved 17663: 17659: 17645: 17629:. Retrieved 17620: 17605:. Retrieved 17569: 17565: 17546:. Retrieved 17537: 17528:Wason, P. C. 17519: 17507:. Retrieved 17499:The Atlantic 17498: 17482:. 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Retrieved 16362: 16358: 16336:. Retrieved 16322: 16299: 16295: 16288:Simon, H. A. 16275: 16247: 16243: 16211: 16207: 16188:. Retrieved 16179: 16163:. Retrieved 16142: 16128: 16106: 16095:, retrieved 16061: 16038:(1): 39–61. 16035: 16031: 15996: 15992: 15981:, retrieved 15971: 15958: 15943:. Retrieved 15939:the original 15909: 15893:. Retrieved 15889: 15874:, retrieved 15870:the original 15864: 15851:. Retrieved 15843:The Guardian 15842: 15826:. Retrieved 15817: 15805:the original 15800: 15762: 15758: 15746:. Retrieved 15737: 15697: 15687: 15665: 15650:. Retrieved 15641: 15612: 15600:. Retrieved 15596: 15580:. Retrieved 15571: 15544: 15538: 15514: 15475: 15471: 15455:. Retrieved 15446: 15430:. Retrieved 15419: 15400:. Retrieved 15380:. Retrieved 15372:The Atlantic 15371: 15355:. Retrieved 15346: 15291: 15287: 15268:. Retrieved 15248: 15203: 15199: 15166: 15162: 15150:. Retrieved 15141: 15125:. Retrieved 15104:. Retrieved 15095: 15082: 15074: 15061:. Retrieved 15044: 15010:(6): 82–97. 15007: 15003: 14980: 14966: 14952:23 September 14950:. Retrieved 14941:The Atlantic 14939: 14920:. Retrieved 14911: 14898: 14885: 14843: 14839: 14828:, retrieved 14824:the original 14818: 14808: 14792:. Retrieved 14788: 14759: 14745:. Retrieved 14737:The Guardian 14736: 14720:. Retrieved 14711: 14690: 14686: 14674:. Retrieved 14665: 14627: 14623: 14611:. Retrieved 14602:. Fox News. 14584:. Retrieved 14576:The Guardian 14575: 14552: 14540:. Retrieved 14532:Ars Technica 14531: 14515:. Retrieved 14494: 14480:. Retrieved 14460: 14444:. Retrieved 14424: 14400: 14373: 14362:the original 14357: 14341:. Retrieved 14337: 14321:. Retrieved 14312: 14288: 14272:. Retrieved 14252: 14248: 14221:. Retrieved 14212: 14196:. Retrieved 14187: 14136: 14106: 14076: 14064:. Retrieved 14055: 14049: 14030:. Retrieved 14019: 13993:(2): 48–57. 13990: 13986: 13972:(7): 24–30. 13969: 13963: 13951:. Retrieved 13940: 13925: 13897:(1): 41–59. 13894: 13890: 13852: 13848: 13830:the original 13813:. Retrieved 13790: 13777: 13765:. Retrieved 13749: 13695: 13691: 13671:1721.1/52357 13653: 13622: 13610:. Retrieved 13601: 13576:(1): 12–34. 13573: 13569: 13561: 13552: 13527: 13523: 13511:. Retrieved 13502: 13479: 13430: 13409: 13387: 13357: 13335: 13328: 13317:. Retrieved 13297: 13281:. Retrieved 13261: 13249:Poole, David 13229: 13209:. Retrieved 13188: 13171:. Retrieved 13150: 13133: 13116: 13113:Rich, Elaine 13084: 13066: 13063:AI textbooks 13048: 13036: 13024: 13012: 13000: 12991:AI in myth: 12987: 12981:Dyson (1998) 12963: 12939: 12927: 12921:Vinge (1993) 12917:Vernor Vinge 12883: 12871:. Retrieved 12867: 12857: 12845:. Retrieved 12841: 12831: 12819:. Retrieved 12808:The Guardian 12807: 12797: 12789:Fast Company 12788: 12778: 12766:. Retrieved 12762: 12737:. Retrieved 12733: 12706:. Retrieved 12702: 12692: 12665:Chinese room 12659: 12647: 12642:, p. 1. 12635: 12623: 12616:Horst (2005) 12611: 12599: 12587: 12575: 12548: 12513: 12501: 12489: 12477: 12441: 12434:Pinker (2007 12430:Minsky (1986 12417: 12396: 12384: 12372: 12360:. Retrieved 12356: 12347: 12335:. Retrieved 12331: 12322: 12310:. Retrieved 12299: 12290: 12278: 12266: 12259:Maker (2006) 12254: 12249:, p. 3. 12242: 12230:. Retrieved 12226: 12216: 12204: 12199:, p. 1. 12177: 12165: 12153:. Retrieved 12144: 12134: 12118: 12085: 12073: 12052: 12028: 12016: 12000: 11988: 11961: 11934: 11922: 11917:, p. 7. 11910: 11898: 11862: 11850: 11838: 11826: 11814: 11803:Minsky (1967 11798: 11782: 11770: 11758: 11746: 11734: 11689:, p. 3) 11669: 11655: 11636: 11620:, p. 9. 11598:. Retrieved 11594:the original 11584: 11572:. Retrieved 11562: 11550:. Retrieved 11541: 11532: 11520:. Retrieved 11516:the original 11511: 11502: 11491: 11485: 11473: 11461: 11449: 11439:17 September 11437:. Retrieved 11432: 11423: 11408: 11396: 11384: 11353: 11326: 11298: 11286:. Retrieved 11276: 11243: 11233: 11192: 11188: 11178: 11151: 11147: 11137: 11119: 11101: 11089:. Retrieved 11085: 11075: 11066: 11056: 11044:. Retrieved 11041:Ars Technica 11040: 11030: 11021: 11011: 10999:. Retrieved 10995: 10985: 10973:. Retrieved 10969: 10959: 10947:. Retrieved 10943: 10933: 10921: 10909: 10897: 10870: 10841:Geist (2015) 10831: 10819:. Retrieved 10815: 10805: 10793:. Retrieved 10789: 10779: 10767:. Retrieved 10763: 10753: 10741:. Retrieved 10737: 10727: 10715:. Retrieved 10712:The Guardian 10711: 10701: 10689: 10677:. Retrieved 10672: 10663: 10654: 10644: 10632:. Retrieved 10623: 10614: 10604:Gibbs (2014) 10590: 10578: 10566: 10546: 10534: 10522: 10510: 10498: 10487: 10481: 10466: 10454: 10442:. Retrieved 10438: 10428: 10416:. Retrieved 10412: 10402: 10382: 10370: 10358: 10343: 10307: 10297:14 September 10295:. Retrieved 10281: 10272: 10262: 10250: 10235: 10223: 10196: 10184:. Retrieved 10180: 10170: 10158: 10146: 10134: 10127:Verma (2021) 10122: 10110: 10098: 10082: 10070: 10058: 10044: 10032: 10020: 10007: 9991: 9978: 9954: 9938: 9926: 9914: 9902: 9875: 9851: 9839: 9827: 9800:. Retrieved 9796: 9771: 9759: 9746: 9736: 9729:Nicas (2018) 9724: 9718:. Dow Jones. 9715: 9705: 9696: 9686: 9680:. Dow Jones. 9677: 9667: 9661:. Dow Jones. 9658: 9648: 9639: 9626: 9617: 9607: 9598: 9588: 9576:. Retrieved 9571: 9562: 9553: 9543: 9531:CNN Business 9530: 9520: 9507: 9496: 9484:The Atlantic 9483: 9471: 9459:Ars Technica 9458: 9448: 9437: 9425: 9413: 9401: 9389:. Retrieved 9377: 9367: 9355:. Retrieved 9351: 9341: 9329: 9317: 9305: 9293: 9281: 9269: 9257: 9245: 9233: 9208: 9204: 9194: 9169: 9165: 9155: 9143:, retrieved 9129: 9119: 9106: 9096: 9084:. Retrieved 9079: 9070: 9049: 9043: 9015: 9008: 8996:. Retrieved 8992: 8982: 8970:. Retrieved 8959:The Guardian 8958: 8948: 8936:. Retrieved 8932: 8922: 8910:. Retrieved 8901: 8891: 8879:. Retrieved 8868: 8858: 8836: 8824:. Retrieved 8803: 8791:. Retrieved 8779: 8769: 8753:ResearchGate 8752: 8723: 8698: 8689: 8680: 8674: 8662: 8652: 8647: 8635:. Retrieved 8629: 8619: 8598: 8589: 8583: 8571:. Retrieved 8567: 8557: 8524: 8520: 8514: 8502:. Retrieved 8491:The Guardian 8490: 8480: 8468:. Retrieved 8463: 8454: 8413: 8409: 8399: 8387:. Retrieved 8383: 8373: 8361:. Retrieved 8349: 8337: 8325:. Retrieved 8321: 8311: 8299:. Retrieved 8287: 8277: 8242: 8238: 8227: 8213: 8199: 8156: 8152: 8142: 8115: 8111: 8066:(2): 94–98. 8063: 8059: 8049: 8040: 8030: 8018:. Retrieved 8014: 8004: 7992: 7980: 7968:. Retrieved 7958: 7944: 7937:Smith (2023) 7932: 7919: 7907: 7878: 7809: 7797: 7785: 7769: 7756: 7719: 7703: 7687: 7664: 7659:, chpt. 3.3) 7635: 7630:, Chapter 4) 7595: 7583: 7547: 7527: 7508: 7499: 7494:, chpt. 20), 7482: 7462: 7430: 7418: 7390: 7378: 7350: 7330: 7301:, chpt. 14) 7275:and dynamic 7268: 7252: 7228: 7184: 7167: 7161: 7155: 7135: 7110: 7094: 7077:, chpt. 7), 7062: 7049:, chpt. 6), 7038: 7014: 7002: 6986: 6974:. Retrieved 6970: 6960: 6949:optimization 6940: 6924: 6888: 6863:and general 6848: 6836: 6820: 6792: 6780: 6768: 6741: 6729: 6717: 6705: 6693: 6681: 6669: 6649: 6637: 6625: 6613: 6593: 6581: 6569: 6552: 6528: 6509: 6497:. Retrieved 6493: 6484: 6465: 6445: 6390: 6378: 6366: 6338: 6333:, chpt. 18). 6322: 6317:, chpt. 17). 6306: 6290: 6269: 6256: 6240: 6220: 6215:, chpt. 11). 6204: 6192: 6180: 6168: 6128: 6124: 6058:modal logics 6052: 6036: 5999: 5954: 5942: 5930: 5918: 5906: 5894: 5882: 5850: 5771: 5750:, chpt. 6) ( 5738: 5731:Toews (2023) 5726: 5706:revolution, 5496: 5424: 5420: 5414: 5395: 5359: 5355: 5341: 5331: 5324:Nils Nilsson 5319: 5302: 5295:The Atlantic 5289: 5270:Hans Moravec 5261: 5245: 5200: 5184: 5168: 5151: 5142: 5129: 5120: 5107:This is the 5103: 5094: 5081: 5052: 5035: 5023: 4980:Kaoru Nakano 4948:Walter Pitts 4938: 4925: 4908: 4896: 4876: 4859: 4846: 4656: 4650: 4644: 4643:, the films 4638: 4628: 4616:Isaac Asimov 4614: 4607: 4601: 4595: 4589: 4583: 4575: 4564:Frankenstein 4562: 4559:Mary Shelley 4552: 4545: 4537: 4509: 4506:George Dyson 4492: 4476:Ray Kurzweil 4468:Hans Moravec 4465: 4453: 4445:Vernor Vinge 4426: 4419: 4390: 4386:human rights 4382: 4378:Robot rights 4363: 4348:Philosopher 4347: 4327: 4324:Chinese room 4303: 4290: 4284: 4237: 4214: 4183: 4164:optimization 4157: 4134:Noam Chomsky 4126:sub-symbolic 4123: 4107: 4093: 4076:sub-symbolic 4068: 4055: 4051: 4043: 4017: 3998: 3929: 3917: 3890: 3867: 3812: 3808:Lisp Machine 3793: 3778: 3743: 3724: 3704:neurobiology 3685: 3656:was held in 3651: 3635: 3618:Eric Schmidt 3602: 3563: 3559: 3552: 3546: 3540: 3534: 3528: 3518: 3509:bioterrorism 3477:Hugging Face 3474: 3454: 3446: 3439: 3396: 3389: 3378: 3347: 3337:are made of 3312: 3290: 3287:Nick Bostrom 3280: 3269: 3251: 3239: 3237: 3224:productivity 3220:unemployment 3216: 3213: 3194: 3138:surveillance 3123: 3099: 3095:rogue states 3076: 3025: 3015: 3006: 2997: 2986: 2957:At its 2022 2956: 2943: 2940: 2935: 2931: 2928: 2924: 2915:Julia Angwin 2897: 2892: 2886: 2843: 2816: 2781: 2755:the 2022 US 2736: 2730: 2728: 2723: 2717: 2713: 2708: 2702: 2687:data centers 2652: 2640: 2633:John Grisham 2622: 2595: 2573:algorithms, 2568: 2564: 2556:surveillance 2549: 2517: 2502: 2498: 2490: 2478: 2449: 2436:Donald Trump 2432:Pope Francis 2405: 2390: 2363: 2344: 2326: 2322: 2314: 2307: 2302: 2298: 2290: 2286: 2283:Alpha Tensor 2282: 2280: 2257: 2251: 2245: 2241:Gemini Ultra 2239: 2232: 2226: 2212:Gran Turismo 2208:StarCraft II 2152:Ken Jennings 2143: 2122: 2111:Game playing 2109: 2062: 2047: 1918:(offered by 1901: 1892:Applications 1855: 1805: 1775: 1735: 1725: 1682: 1670:local search 1667: 1651: 1616:such as the 1603: 1580: 1570:Old Faithful 1542: 1516:algorithm), 1504: 1468: 1434: 1428: 1401: 1381:Horn clauses 1370: 1344: 1339: 1335: 1332: 1328: 1324: 1321: 1296:is used for 1291: 1263: 1252: 1238: 1230:Local search 1228: 1225:(the height) 1209:Local search 1199:game-playing 1197:is used for 1193: 1177:search space 1171: 1157: 1148:local search 1141: 1133: 1117: 1101: 1083: 1040: 1022: 993:transformers 982: 970:micro-worlds 954:Noam Chomsky 951: 917: 908:optimization 894: 875: 856: 850: 839: 812: 797: 790: 763: 750: 734: 719: 702: 683: 674: 634: 630:neuroscience 598:formal logic 559: 468: 436:intelligence 431: 427: 426: 300:Chinese room 189:Applications 55: 44: 24935:Cybernetics 24853:Ornithology 24838:Meteorology 24823:Mathematics 24813:Ichthyology 24648:Archaeology 24643:Agriculture 24627:engineering 24505:Qian Xuesen 24385:Gordon Pask 24282:Synergetics 24247:Homeostasis 24187:Biorobotics 24158:cybernetics 24025:Max Tegmark 24010:Martin Rees 23818:Longtermism 23778:AI takeover 23472:Open-source 23325:Space probe 23315:Necrobotics 23305:Microbotics 23268:Biorobotics 23197:Educational 23180:Articulated 23161:Animatronic 23146:Claytronics 22934:Moore's law 22865:Neuroethics 22860:Cyberethics 22681:Atomtronics 22500:Video games 22480:Digital art 22237:Concurrency 22106:Data mining 22018:Probability 21751:Interpreter 21527:Categories 21475:Autoencoder 21430:Transformer 21298:Alex Graves 21246:OpenAI Five 21150:IBM Watsonx 20772:Convolution 20750:Overfitting 20591:Mating pool 20341:Main Topics 20247:Ian Hacking 20232:Thomas Kuhn 20217:Karl Popper 20197:C. D. Broad 20114:Roger Bacon 20042:Non-science 19984:Linguistics 19964:Archaeology 19859:Rationalism 19849:Determinism 19836:Physicalism 19801:Fallibilism 19751:Coherentism 19681:Testability 19634:Observation 19629:Objectivity 19590:alternative 19521:Correlation 19511:Consilience 19381:information 19372:Metaphysics 19346:Tabula rasa 19156:Physicalism 19141:Parallelism 19069:Behaviorism 19026:Michael Tye 19021:Alan Turing 19006:John Searle 18881:Dharmakirti 18856:Tyler Burge 18851:C. D. Broad 18627:In Our Time 18544:20 February 18292:Press, Eyal 18284:Introduced 17548:18 November 17533:"Reasoning" 17484:14 November 17373:25 November 16983:25 December 16752:25 November 16429:(1): 2–16. 16359:AI Magazine 16276:AI Magazine 16214:(1): 9–11. 16165:18 November 15972:What is AI? 15895:25 December 15000:Sainath, T. 14840:AI Magazine 14830:12 November 14804:Good, I. J. 14789:VentureBeat 14630:: 254–280. 14517:18 November 14378:Basic Books 14343:22 November 14233:Cybenko, G. 14198:23 November 13487:Altman, Sam 13211:18 November 13173:17 December 12913:Good (1965) 12873:23 February 12847:23 February 12821:23 February 12768:23 February 12739:23 February 12708:23 February 12506:Katz (2012) 12470:Fearn (2007 12090:Moore's Law 12078:Wong (2023) 11787:Simon (1965 11703:Turing test 11067:VentureBeat 11022:AI Business 10902:AAAI (2014) 10821:30 December 10795:30 December 10387:Lohr (2017) 9864:Rose (2023) 9820:Rose (2023) 8826:7 September 8041:AI Business 8015:VentureBeat 7970:25 December 7724:Perceptrons 7488:classifiers 7397:algorithm: 7345:, chpt. 18) 7335:Game theory 7283:, chpt. 17) 7223:, chpt. 19) 7144:unification 7105:, chpt. 10) 7089:, chpt. 15) 7057:, chpt. 13) 6750:Thro (1993) 6494:builtin.com 6327:Game theory 5970:(including 5968:inheritance 5649:Howe (1994) 5362:thinking)." 5278:Nouvelle AI 5016:Paul Werbos 4952:Alan Turing 4881:Alan Turing 4635:Karel Čapek 4594:(1984) and 4534:Karel Čapek 4449:singularity 4439:called an " 4350:John Searle 4339:Jerry Fodor 4194:fuzzy logic 4186:intractable 4095:Symbolic AI 4000:Alan Turing 3983:Turing test 3882:mathematics 3847:Lofti Zadeh 3843:Judea Pearl 3780:Perceptrons 3720:Turing test 3696:cybernetics 3688:Alan Turing 3471:Open source 3385:AI takeover 2947:stereotypes 2913:. In 2016, 2909:becoming a 2903:U.S. courts 2866:recruitment 2685:power from 2642:sui generis 2359:Joint Fires 2291:Alpha Proof 2275:classifiers 2273:or trained 2271:fine-tuning 2247:Claude Opus 2223:Mathematics 2168:computer Go 2148:Brad Rutter 2146:champions, 2082:AlphaFold 2 1962:(including 1930:), driving 1697:Perceptrons 1646:human brain 1595:observation 1583:Classifiers 1520:(using the 1512:(using the 1496:game theory 1472:probability 1430:Fuzzy logic 1426:languages. 1408:intractable 1404:undecidable 1338:s that are 1318:quantifiers 841:Game theory 808:intractably 694:probability 622:linguistics 329:Turing test 305:Friendly AI 76:Major goals 24914:Categories 24868:Psychiatry 24777:Geography 24748:Entomology 23990:Shane Legg 23965:Sam Harris 23940:Sam Altman 23879:EleutherAI 23512:Ubiquitous 23502:Perceptual 23409:Navigation 23364:Locomotion 23342:Underwater 23227:Disability 23175:Industrial 22825:Automation 22558:Glossaries 22430:E-commerce 22023:Statistics 21966:Algorithms 21924:Stochastic 21756:Middleware 21612:Peripheral 21516:Technology 21369:EleutherAI 21328:Fei-Fei Li 21323:Yann LeCun 21236:Q-learning 21219:Decisional 21145:IBM Watson 21053:Midjourney 20945:TensorFlow 20792:Activation 20745:Regression 20740:Clustering 20378:Algorithms 20134:David Hume 20107:Precursors 19989:Psychology 19969:Economics‎ 19863:Empiricism 19854:Pragmatism 19841:Positivism 19831:Naturalism 19701:scientific 19585:Hypothesis 19548:Experiment 19417:Task Force 19385:perception 19259:Artificial 19209:Creativity 19131:Nondualism 19031:Vasubandhu 18951:John Locke 18921:David Hume 18876:Andy Clark 18516:3 February 17967:. London. 17904:8 December 17855:algorithms 17200:8 December 16801:: 85–117. 16747:Codemotion 16732:30 January 16712:30 October 16689:1083694322 16644:8 December 16586:30 January 16542:1893/25490 16527:: 98–125. 16208:AI Matters 16190:13 January 15983:4 December 15876:16 October 15853:13 January 15828:31 January 15818:Fusion.net 15748:13 January 15652:30 October 15629:1110727808 15621:2019668143 15602:30 October 15572:ProPublica 15432:4 November 15402:25 October 15382:26 October 15063:30 October 14853:1606.08813 14794:8 December 14747:30 October 14722:30 October 14586:13 January 14274:18 October 14128:1233266753 14066:11 October 14032:30 October 13953:16 October 13815:30 January 13698:: e42936. 13648:Beal, J.; 13641:1039480085 13503:openai.com 13319:6 December 12909:I. J. Good 12667:argument: 12472:, chpt. 3) 12312:16 October 11552:1 November 11522:2 November 10970:TechCrunch 10849:Lee (2014) 10011:Quoted in 9982:Quoted in 9832:CNA (2019) 9274:GAO (2022) 9211:: 103140. 8998:28 January 8972:28 January 8938:28 January 8849:2307.15208 8793:24 January 8610:2402.19450 8504:28 January 8470:28 January 8389:28 January 8363:28 January 8327:28 January 8301:28 January 7923:Quoted in 7914:, sect. 8. 7902:, sect. 7. 7885:, sect. 6. 7873:, sect. 5. 7385:, chpt. 6. 7140:Resolution 6976:13 January 6955:, chpt. 4) 6951:" search: 6935:, chpt. 5) 6897:best first 6883:, chpt. 8) 6831:, chpt. 3) 6664:, chpt. 6) 6499:30 October 6111:, §10.6), 6064:, §10.4), 6023:, §10.3), 5370:References 5360:simulating 5113:land mines 5056:Including 4869:philosophy 4652:Ex Machina 4597:The Matrix 4518:In fiction 4447:called a " 4437:I. J. Good 3981:See also: 3966:Philosophy 3874:statistics 3859:Yann LeCun 3823:perception 3727:a workshop 3708:McCullouch 3636:In a 2022 3573:Regulation 3515:Frameworks 3505:fine-tuned 3485:EleutherAI 3408:Yann LeCun 3374:Sam Altman 3354:Bill Gates 3327:government 3319:ideologies 3291:almost any 3247:paralegals 3226:gains are 3192:in China. 3154:propaganda 3087:terrorists 3081:, such as 3079:bad actors 3041:generative 3039:and other 2973:See also: 2919:ProPublica 2911:recidivist 2795:maximizing 2776:See also: 2697:See also: 2667:Apple Inc. 2629:robots.txt 2416:Midjourney 2268:supervised 2217:open-world 2077:microscopy 2022:, Apple's 1862:TensorFlow 1836:modalities 1832:Multimodal 1779:(GPT) are 1566:clustering 1545:perception 1534:perception 1490:, dynamic 1397:resolution 1373:leaf nodes 1354:conclusion 1282:ant trails 1189:Heuristics 1130:Techniques 1019:Perception 871:regression 686:deductions 626:philosophy 618:psychology 606:statistics 539:superhuman 523:generative 446:. It is a 334:Regulation 288:Philosophy 243:Healthcare 238:Government 140:Approaches 24723:Economics 24688:Chemistry 24663:Astronomy 24237:Emergence 24165:Subfields 24005:Huw Price 23995:Elon Musk 23899:Humanity+ 23773:AI safety 23563:Figure AI 23521:Companies 23497:Paradigms 23482:Adaptable 23462:Simulator 23156:Automaton 23151:Companion 23062:Geography 22855:Bioethics 22741:Millipede 22379:Rendering 22374:Animation 22005:computing 21956:Semantics 21647:Processor 21399:MIT CSAIL 21364:Anthropic 21333:Andrew Ng 21231:AlphaZero 21075:VideoPoet 21038:AlphaFold 20975:MindSpore 20929:SpiNNaker 20924:Memristor 20831:Diffusion 20807:Rectifier 20787:Batchnorm 20767:Attention 20762:Adversary 19974:Geography 19942:Chemistry 19901:Scientism 19696:ladenness 19516:Construct 19494:Causality 19281:Intuition 19214:Cognition 19178:Solipsism 18841:Ned Block 18811:Armstrong 18806:Aristotle 18376:220523562 18368:1610-1987 18268:205242740 18101:235959867 18032:deepfakes 17811:22 August 17698:22 August 17688:158829602 17680:0190-0692 17438:The Verge 17413:The Verge 17388:The Verge 17318:247302391 17236:0026-4423 17180:22 August 16941:22 August 16931:231867665 16897:22 August 16808:1404.7828 16551:205433041 16495:(2007) , 16376:22 August 16333:0099-9660 16079:219336439 16001:CiteSeerX 15945:30 August 15767:CiteSeerX 15718:166742927 15334:143452957 15183:2158-2041 15127:30 August 15053:0190-8286 15032:206485943 14888:(Report). 14846:(3): 50. 14654:0040-1625 14632:CiteSeerX 14482:22 August 14446:22 August 14338:TechTalks 14146:1202.2745 14007:206451986 13942:The Press 13913:1867-299X 13857:CiteSeerX 13740:256681439 13714:2817-1705 13283:22 August 12816:0261-3077 12734:Big Think 12663:Searle's 12232:17 August 12062:NRC (1999 11268:259614124 11260:2514-9369 11225:214766800 11209:1572-8633 11170:198775713 10444:17 August 10418:17 August 9386:1059-1028 9225:0926-5805 9186:1572-8099 9086:10 August 8967:0261-3077 8788:1059-1028 8733:PD-notice 8499:0261-3077 8438:0036-8075 8384:The Verge 8358:0362-4331 8296:0028-792X 8134:2673-5067 6971:KDnuggets 6893:Heuristic 6105:abduction 5685:NRC (1999 5669:AI Winter 5645:NRC (1999 5625:AI Winter 5605:NRC (1999 5579:(Japan), 5528:NRC (1999 5449:158433736 5441:0007-6813 5427:: 15–25. 5336:earlier." 5308:Bloomberg 5008:Yu-Chi Ho 4865:economics 4553:A common 4354:strong AI 3944:Go player 3878:economics 3789:AI winter 3759:criticism 3604:Index at 3587:AI safety 3424:AI safety 3404:Andrew Ng 3358:Elon Musk 3283:sentience 3274:stated, " 3162:Deepfakes 3091:criminals 3073:AI safety 3049:Anthropic 3037:DeepDream 2907:defendant 2817:In 2022, 2739:Microsoft 2683:computing 2675:Microsoft 2587:unethical 2560:copyright 2524:Deep Mind 2293:all from 2229:reasoning 2172:handicaps 2164:Lee Sedol 2144:Jeopardy! 2128:quiz show 2124:Jeopardy! 2115:Deep Blue 2018:(used by 2000:Microsoft 1950:(such as 1906:(such as 1510:reasoning 1458:A simple 1414:language 1389:backwards 1320:such as " 1298:reasoning 1259:selecting 997:attention 835:heuristic 831:iteration 730:databases 698:economics 690:uncertain 653:its risks 637:AI winter 614:economics 562:reasoning 485:(used by 364:AI winter 265:Military 128:AI safety 24893:Virology 24878:Robotics 24843:Mycology 24833:Medicine 24678:Calculus 24117:Category 23985:Bill Joy 23751:Concepts 23685:Category 23603:Symbotic 23553:FarmWise 23507:Situated 23477:Software 23445:Research 23389:Climbing 23212:Military 23207:Juggling 23192:Domestic 23124:Humanoid 23047:Glossary 23028:Robotics 22776:UltraRAM 22538:Category 22366:Graphics 22141:Security 21803:Compiler 21702:Networks 21599:Hardware 21507:Portals 21266:Auto-GPT 21098:Word2vec 20902:Hardware 20819:Datasets 20721:Concepts 20606:Journals 20269:Category 19921:Vitalism 19744:Theories 19718:Variable 19639:Paradigm 19526:function 19484:A priori 19473:Analysis 19466:Concepts 19402:Category 19249:Identity 19192:Concepts 19062:Theories 19046:Zhuangzi 18976:Alva Noë 18718:ALGOL 60 18535:Archived 18510:Archived 18506:BBC News 18472:Archived 18460:26819042 18408:Archived 18318:alone", 18272:Archived 18260:25719670 18188:Archived 18154:Archived 18142:26017442 18093:34265844 18036:cartoons 17969:Archived 17864:(2015). 17805:Archived 17801:46890682 17779:(2000). 17740:archived 17692:Archived 17625:Archived 17598:Archived 17594:54131797 17586:11229402 17542:Archived 17509:24 April 17503:Archived 17460:(1993). 17442:Archived 17417:Archived 17392:Archived 17335:Archived 17331:BBC News 17310:36211133 17259:Archived 17174:Archived 17147:24 April 17141:Archived 17071:Archived 17044:22 March 17035:Archived 17024:(1956). 17014:32710913 16935:Archived 16909:(1999). 16888:Archived 16884:55303721 16855:(1980). 16843:(2022). 16833:11715509 16825:25462637 16706:Archived 16702:Observer 16667:(2019). 16638:Archived 16623:20 March 16580:Archived 16576:BBC News 16561:27 April 16555:Archived 16447:Archived 16405:(2008). 16367:Archived 16350:(1983). 16290:(1976). 16264:10767011 16232:Archived 16184:Archived 16159:Archived 16139:(1988). 16127:(1967), 16091:archived 16052:14987656 16023:37272949 15977:archived 15969:(1999), 15933:(1955). 15907:(1986), 15847:Archived 15822:Archived 15801:aaai.org 15742:Archived 15722:archived 15646:Archived 15576:Archived 15512:(2005). 15502:16622160 15451:Archived 15426:Archived 15396:Archived 15392:"Kismet" 15376:Archived 15351:Archived 15347:Fox News 15326:17835457 15264:Archived 15246:(2011). 15228:26185243 15191:59298502 15146:Archived 15121:Archived 15100:Archived 15057:Archived 14979:(1985). 14946:Archived 14916:Archived 14806:(1965), 14741:Archived 14716:Archived 14676:26 April 14670:Archived 14668:. 2016. 14604:Archived 14580:Archived 14536:Archived 14511:Archived 14476:Archived 14458:(1998). 14440:Archived 14398:(1972). 14372:(2015). 14317:Archived 14286:(1991). 14265:Archived 14217:Archived 14192:Archived 14105:(2020). 14060:Archived 14044:(1995). 14026:Archived 14021:BBC News 13965:Computer 13947:Archived 13875:Archived 13840:(1990). 13809:Archived 13788:(2014). 13767:9 August 13758:Archived 13732:38875587 13723:11041459 13680:32437713 13612:13 April 13606:Archived 13590:10168773 13507:Archived 13465:Archived 13429:(1994). 13408:(2004), 13386:(1993). 13313:Archived 13295:(2017). 13277:Archived 13259:(1998). 13227:(2003), 13205:Archived 13185:(1998). 13167:Archived 13147:(2004). 13105:20190474 13083:(2021). 12868:euronews 12842:Newsweek 12357:The Drum 12306:Archived 12155:15 March 12149:Archived 12123:Big data 12092:and AI: 11843:NRC 1999 11546:Archived 11217:32236794 11091:14 April 11046:14 April 11001:14 April 10975:14 April 10949:14 April 10738:Fox News 10634:28 March 10628:Archived 10624:CBS News 10332:Archived 10291:Archived 9751:Archived 9535:Archived 9512:Archived 9488:Archived 9463:Archived 9391:26 April 9357:26 April 9111:Archived 8993:euronews 8912:14 March 8906:Archived 8881:14 March 8875:Archived 8817:Archived 8667:AI Math. 8637:7 August 8549:35140384 8446:31296650 8269:38632492 8260:11062903 8191:34265844 8090:31363513 7437:and the 7071:equality 6343:Learning 5808:and the 5503:, §1.2). 5403:Archived 5356:actually 5266:Embodied 5115:as well. 5074:Stanford 5045:fairness 5014:(1970); 5002:(1962); 4998:(1962); 4994:(1960); 4986:(1972); 4982:(1971); 4978:(1965); 4970:(1959); 4966:(1957); 4954:(1948); 4669:See also 4624:Multivac 4580:HAL 9000 4370:Sapience 4071:paradigm 4059:buzzword 3940:DeepMind 3920:fairness 3913:ImageNet 3831:learning 3827:robotics 3777:'s book 3735:checkers 3646:Fox News 3606:Stanford 3339:language 3333:and the 3313:Second, 3146:classify 2893:anything 2882:fairness 2874:policing 2858:medicine 2807:partisan 2787:Facebook 2655:Big Tech 2625:fair use 2614:fairness 2493:disaster 2457:chatbots 2440:Pentagon 2335:Military 2192:DeepMind 2188:Pluribus 2069:organoid 2065:big data 2050:medicine 2020:Facebook 2004:DeepFace 1944:Facebook 1876:such as 1801:chatbots 1766:ImageNet 1599:data set 1526:planning 1518:learning 1385:forwards 1358:premises 1274:flocking 1185:too slow 1163:planning 1005:bar exam 978:thesauri 847:Learning 741:ontology 582:robotics 574:learning 570:planning 527:creative 464:learning 462:and use 456:software 440:machines 387:Glossary 381:Glossary 359:Progress 354:Timeline 314:Takeover 275:Projects 248:Industry 211:Finance 201:Deepfake 151:Symbolic 123:Robotics 98:Planning 24858:Physics 24808:Geology 24718:Ecology 24668:Biology 24623:science 23697:Outline 23627:Related 23618:Yaskawa 23533:Anybots 23413:mapping 23382:Hexapod 23377:Walking 23222:Service 23217:Medical 23129:Android 23114:Aerobot 23057:History 23042:Outline 22722:Memory 22548:Outline 21389:Meta AI 21226:AlphaGo 21210:PanGu-Σ 21180:ChatGPT 21155:Granite 21103:Seq2seq 21082:Whisper 21003:WaveNet 20998:AlexNet 20970:Flux.jl 20950:PyTorch 20802:Sigmoid 20797:Softmax 20662:General 19979:History 19947:Physics 19937:Biology 19735:more... 19723:control 19619:Inquiry 19412:Project 19365:Related 19224:Concept 19079:Dualism 19052:more... 18911:Goldman 18612:(ed.). 18569:Scholia 18478:19 June 18440:Bibcode 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