Artificial Intelligence Definition

C O N T E N T S:


  • At TechEmergence, we?ve developed concrete definitions of both artificial intelligence and machine learning based on a panel of expert feedback.(More…)
  • “Artificial intelligence is a broad term that simply means: any intelligence run by a computer.(More…)
  • These appearances also lead to heightened expectations — some technologists argue that the type of intelligence in these systems is “assisted” or “augmented” rather than “artificial”, but recent advances in computing have certainly accelerated the potential of the technology.(More…)


  • Proposed “universal intelligence” tests aim to compare how well machines, humans, and even non-human animals perform on problem sets that are generic as possible.(More…)


Artificial Intelligence Definition
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description: The Many Ways to Define Artificial Intelligence | Intel Newsroom


At TechEmergence, we?ve developed concrete definitions of both artificial intelligence and machine learning based on a panel of expert feedback. [1] McCarthy recently reiterated his position at the [email protected] conference where he said “Artificial intelligence is not, by definition, simulation of human intelligence” ( Maker 2006 ). [2]

Gopnik, Alison, “Making AI More Human: Artificial intelligence has staged a revival by starting to incorporate what we know about how children learn”, Scientific American, vol. 316, no. 6 (June 2017), pp.60-65. [2] Mary Shelley’s Frankenstein considers a key issue in the ethics of artificial intelligence : if a machine can be created that has intelligence, could it also feel ? If it can feel, does it have the same rights as a human? The idea also appears in modern science fiction, such as the film A.I.: Artificial Intelligence, in which humanoid machines have the ability to feel emotions. [2] Onlookers commonly discount the behavior of an artificial intelligence program by arguing that it is not “real” intelligence after all; thus “real” intelligence is whatever intelligent behavior people can do that machines still cannot. [2] McCorduck 2004, pp.100-101, who writes that there are “two major branches of artificial intelligence: one aimed at producing intelligent behavior regardless of how it was accomplished, and the other aimed at modeling intelligent processes found in nature, particularly human ones.” [2] Throughout the novel, Dick portrays the idea that human subjectivity is altered by technology created with artificial intelligence. [2] With social media sites overtaking TV as a source for news for young people and news organisations increasingly reliant on social media platforms for generating distribution, major publishers now use artificial intelligence (AI) technology to post stories more effectively and generate higher volumes of traffic. [2] There are a lot of ways to define artificial intelligence – mostly since “intelligence” alone can be hard to pin down, but also because people ascribe AI to everything from the grandiose to the matter-of-fact. [3] Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding (known as an ” AI winter “), followed by new approaches, success and renewed funding. [2] According to Bloomberg’s Jack Clark, 2015 was a landmark year for artificial intelligence, with the number of software projects that use AI within Google increased from a “sporadic usage” in 2012 to more than 2,700 projects. [2] Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the AI effect. [2] If you keep track of industry trends at all, then I bet your newsfeed has been filled with exciting stories and bold predictions about artificial intelligence (AI), machine learning (ML), and neural networks. [4] Artificial Intelligence (AI) and Machine Learning (ML) are two terms often used interchangeably or considered to be synonyms. [4] What Is AI? – An introduction to artificial intelligence by John McCarthy –a co-founder of the field, and the person who coined the term. [2] Unlike previous waves of automation, many middle-class jobs may be eliminated by artificial intelligence; The Economist states 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”. [2] The opinion of experts within the field of artificial intelligence is mixed, with sizable fractions both concerned and unconcerned by risk from eventual superhumanly-capable AI. [2] The implications of a constructed machine exhibiting artificial intelligence have been a persistent theme in science fiction since the twentieth century. [2] Though yet to become a standard in schools, artificial intelligence in education has been “a thing” since AI’s uptick in the 1980s. [1] Other counterarguments revolve around humans being either intrinsically or convergently valuable from the perspective of an artificial intelligence. [2] The development of full artificial intelligence could spell the end of the human race. [2] Technological singularity is when accelerating progress in technologies will cause a runaway effect wherein artificial intelligence will exceed human intellectual capacity and control, thus radically changing or even ending civilization. [2] “AlphaGo beats human Go champ in milestone for artificial intelligence”. [2] Once humans develop artificial intelligence, it will take off on its own and redesign itself at an ever-increasing rate. [2] One high-profile example is that DeepMind in the 2010s developed a “generalized artificial intelligence” that could learn many diverse Atari games on its own, and later developed a variant of the system which succeeds at sequential learning. [2] People “think we are recreating a brain,” Amir Khosrowshahi, chief technology officer of the Artificial Intelligence Products Group, said in an interview. [3] Artificial intelligence will transform the relationship between people and technology, charging our creativity and skills. [5] “Bill Gates on dangers of artificial intelligence: ‘I don’t understand why some people are not concerned ‘ “. [2] Note that they use the term “computational intelligence” as a synonym for artificial intelligence. [2] Banks use artificial intelligence systems today to organize operations, maintain book-keeping, invest in stocks, and manage properties. [2] Widespread use of artificial intelligence could have unintended consequences that are dangerous or undesirable. [2] IBM has created its own artificial intelligence computer, the IBM Watson, which has beaten human intelligence (at some levels). [2] Deep learning has transformed many important subfields of artificial intelligence, including computer vision, speech recognition, natural language processing and others. [2] Intel Fellow Pradeep Dubey calls artificial intelligence “a simple vision where computers become indistinguishable between humans.” [3] This approach to the philosophical problems associated with artificial intelligence forms the basis of the Turing test. [2] The synergistic approach in the former shows that by pairing human intelligence with artificial intelligence, the overall grading system costs less and accomplishes more. [1] In early 2016, Wealthfront announced it was taking an AI-first approach, promising “an advice engine rooted in artificial intelligence and modern APIs, an engine that we believe will deliver more relevant and personalized advice than ever before.” [1] In video games, artificial intelligence is routinely used to generate dynamic purposeful behavior in non-player characters (NPCs). [2] Another study is using artificial intelligence to try and monitor multiple high-risk patients, and this is done by asking each patient numerous questions based on data acquired from live doctor to patient interactions. [2] Artificial Intelligence: Foundations of Computational Agents (2nd ed.). [2] Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th ed.). [2] “Some philosophical problems from the standpoint of artificial intelligence”. [2] TechEmergence conducts direct interviews and consensus analysis with leading experts in machine learning and artificial intelligence. [1] “The role of cognitive architectures in general artificial intelligence”. [2] Artificial Intelligence and Law. 25 (3): 341-363. doi : 10.1007/s10506-017-9210-0. [2] “Content: Plug & Pray Film – Artificial Intelligence – Robots -“. [2] This marked the completion of a significant milestone in the development of Artificial Intelligence as Go is an extremely complex game, more so than Chess. [2] A common concern about the development of artificial intelligence is the potential threat it could pose to humanity. [2] There is no simpler or more practical way to define artificial intelligence. [6] “Commonsense reasoning and commonsense knowledge in artificial intelligence”. [2] Mechanical system controls using PLCs and automation servers that have existed for years, for example, is a form of artificial intelligence. [4] After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. [2] “ACM Computing Classification System: Artificial intelligence”. [2] The Nature of Self-Improving Artificial Intelligence. presented and distributed at the 2007 Singularity Summit, San Francisco, CA. ^ a b c Technological singularity : [2]

In 2017, Vladimir Putin stated that “Whoever becomes the leader in (artificial intelligence) will become the ruler of the world”. [2] Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”. [2] Edward Fredkin argues that “artificial intelligence is the next stage in evolution”, an idea first proposed by Samuel Butler’s ” Darwin among the Machines ” (1863), and expanded upon by George Dyson in his book of the same name in 1998. [2] For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology. [2]

This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity. [2]

The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, “AI is whatever hasn’t been done yet.” [2]

Some argue that some kind of (currently-undiscovered) conceptually straightforward, but mathematically difficult, “Master Algorithm” could lead to AGI. Finally, a few “emergent” approaches look to simulating human intelligence extremely closely, and believe that anthropomorphic features like an artificial brain or simulated child development may someday reach a critical point where general intelligence emerges. [2]

Artificial Intelligence is a branch of Computer Science dedicated to creating intelligent machines that work and react like humans. [7] Deep Learning makes it possible for Artificial Intelligence to function like a human, and probably even a more intelligent version of a human. [7]

Artificial intelligence are software programs that mimic the way humans learn and solve complex problem. [7] Machine Learning provides Artificial Intelligence with the ability to learn and adapt and solve problems on its own based on some algorithms. [7] While machine learning algorithms have been around for decades, they’ve attained new popularity as artificial intelligence (AI) has grown in prominence. [8] AI stands for artificial intelligence, where intelligence is defined as the ability to acquire and apply knowledge. [7] The introduction of artificial intelligence (AI) technologies into speech analytics has turned this once-quiet backwater of the customer service world into a growing market for customer insight across sales, service, and marketing. [9] Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. [7] This method involves selecting from a choice of words generated from the machine and constructing sentences in collaboration with the artificial intelligence model. [10] While we may be decades away from interacting with intelligent robots, artificial intelligence and machine learning has already found its way into our routines. [11] In nature, we can find many similarities to this kind of artificial intelligence way to solve problems. [7] Artificial intelligence way is to let ants to make local decisions to be successful as a whole. [7] A YouTube video was released this week that explained Bitcoin in a rather creative way using the predictive text from an artificial intelligence model. [10] Kyndi’s office in San Mateo, Calif. The company’s focus on the reasoning side of artificial intelligence distinguishes it from the branch known as deep learning, in which computers train themselves by processing massive amounts of data. [12] For the past five years, the hottest thing in artificial intelligence has been a branch known as deep learning. [12] If the reach of deep learning is limited, too much money and too many fine minds may now be devoted to it, said Oren Etzioni, chief executive of the Allen Institute for Artificial Intelligence. [12] Botnik Studios released the video as part of a creative series that explores the use of artificial intelligence for creating artistic representations of language. [10] The danger, some experts warn, is that A.I. will run into a technical wall and eventually face a popular backlash — a familiar pattern in artificial intelligence since that term was coined in the 1950s. [12] Machine learning is one example of artificial intelligence in practice. [11] Why this happens, and could we do any better? Could ants somehow know where the areas are and adapt their behavior to make them more successful? This is where artificial intelligence comes into play. [7] Here’s one definition: Artificial intelligence is the development of algorithms that mimic human thought. [13]

Artificial Intelligence (AI) is basically intelligence demonstrated outside the human mind, essentially by machines. [14] From Artificial Intelligence (AI) infused computers, to handheld communications devices, to robots that can replicate human tasks, to lethal autonomous weapons systems, fiction has become fact. [15] Artificial Intelligence is the development of any computer system that mimics human capabilities, but in ways that its creators don’t fully understand. [13] Computers can beat humans at chess but once that had happened, people stopped thinking if playing chess as artificial intelligence. [13]

“Artificial intelligence is a broad term that simply means: any intelligence run by a computer. [7]

Many professionals across the world wide web are contemplating an ultimate partnership between Artificial Intelligence and Human Intelligence (AI+HI) where tools like AI are being active partners rather than just passive extensions of one’s self. [14] Over 100 government, academic, business, and technology leaders gathered at the White House recently to discuss Artificial Intelligence (AI). [13] The challenge of artificial intelligence isn’t so much the technology as it is our own attitude about machines and intelligence. [16] As innovations in artificial intelligence, robotics, and other technology bring us virtual assistants, wearable health tech, autonomous vehicles, and more, many industries are transforming rapidly. [17] Artificial intelligence (AI) has tremendous potential to benefit the American people, and has already demonstrated immense value in enhancing our national security and growing our economy. [13] Artificial Intelligence (AI) has enormous potential to shape India’s future. [18] As artificial intelligence transforms everything from agriculture to manufacturing to transportation — the potential for AI remains breathtaking. [13] Practical adoption of artificial intelligence (AI) is driven by an exclusive club of companies. [19] The paradox is that once computers figure out how to do things, it becomes harder to think of them as artificial intelligence. [13] Obviously, we?ve only just scratched the surface of what chatbots, artificial intelligence, and machine learning can do for our organizations. [20] I have also made clear that while America will always approach artificial intelligence prudently, we will not hamstring American potential on the international stage. [13] I want to focus on The White House approach to artificial intelligence and American industry–particularly how we can support the American worker, promote R&D, and remove barriers to innovation. [13]

This is the Definition which is frequently quoted about Artificial Intelligence. [21] While the Act provides its own definitions, there is currently no universally agreed-upon definition of artificial intelligence. [22] Artificial Intelligence is taking a step forward in creating machines and computers as intelligent as human beings. [21] The ability for a computer to not only persuasively compete in a debate against a live person, but to actually win the argument, is only likely to feed into fears expressed by Tesla and SpaceX CEO Elon Musk and the late cosmologist Stephen Hawking that artificial intelligence could spell doom for human civilization. [23]

These appearances also lead to heightened expectations — some technologists argue that the type of intelligence in these systems is “assisted” or “augmented” rather than “artificial”, but recent advances in computing have certainly accelerated the potential of the technology. [18] While machine learning comprises of AI, utilizing and involving its technology across all of its applications, machine learning itself is not artificial intelligence. [24] Our artificial intelligence strategy is to help ensure that every data scientist, developer and practitioner has access to the best platform and easiest starting point to solve the AI problem being tackled from the data center to the edge. [25] Abstract: All it takes to identify the computer programs which are Artificial Intelligence is to give them a test and award AI to those that pass the test. [26] Naveen Rao, vice president and general manager of the Artificial Intelligence Products Group at Intel Corporation, opens Intel AI DevCon on Wednesday, May 23, 2018, in San Francisco. [25] The first was Preparing for the Future of Artificial Intelligence ( SciPol brief available ), which surveyed the current state of AI, its existing and potential applications, and the questions that progress in AI raises for society and public policy. [22] On February 21, 2018, the Bulletin of the Atomic Scientists, which manages the international Doomsday Clock, have recognized in a study on Artificial Intelligence and National Security that, “advances in AI will affect national security by driving change in three areas: military superiority, information superiority, and economic superiority.” [22] The purpose and responsibilities of the Commission would be to review the current state of artificial intelligence (AI) and associated technologies to better equip the nation with the means of addressing its national security needs including economic risks, needs of the Department of Defense (DOD), and other security risks as defined by the Commission. [22] Artificial intelligence will merge with human brains to transform the way we think (The Verge). [27] The San Francisco event was the first time anyone outside of IBM was able to witness a live debate between a human and its artificial intelligence system. [23] IBM shows off an artificial intelligence that can debate a human and it does it surprisingly well. [23] By allowing machines to learn, reason, act and adapt in the real world, artificial intelligence and machine learning are helping businesses unlock deeper levels of knowledge and insights from massive amounts of data. [25] The point of the experiment was to show how easy it is to bias any artificial intelligence if you train it on biased data. [28] Artificial intelligence is the science and engineering of making computers behave in ways that, until recently, we thought required human intelligence. [27] Within five years, artificial intelligence will be behind your every decision (Ginni Rometty of IBM via Computer World ). [27] In a thought-piece published in AAAI in 1997, UCLA Professor of Computer Science Richard Korf noted that the word artificial intelligence had acquired a “taint” due to “failing to deliver on its early promises”. [27] In the same article, he reveals that while IBM often described Deep Blue as a “supercomputer”, they took pains to explicitly claim “that Deep Blue did not use artificial intelligence”. [27] We encounter artificial intelligence in our daily tasks when we use talk-to-text and photo tagging technology. [25] To put the present argument in context, I wouldn’t rule out the use of the term artificial intelligence. [27] The National Security Commission Artificial Intelligence Act of 2018 follows a series of reports issues by the NSTC Committee on Technology in 2016. [22] HR 4625 and S 2217, the FUTURE of Artificial Intelligence Act of 2017 – Introduced by Representative Maria Cantwell (D-WA-1), Representative Todd Young (R-IN-9), and Senator Ed Markey (D-MA) are bills currently under review in both chambers of Congress to require the Department of Commerce to establish the Federal Advisory Committee on the Development and Implementation of Artificial Intelligence ( SciPol Brief Available ). [22] Proposes the establishment of a temporary National Security Commission on Artificial Intelligence to assess and recommend the development of artificial intelligence to support the US’s natural security interests and advantage. [22] Artificial intelligence is transforming the way we work (Venture Beat), turning all of us into hyper-productive business centaurs (The Next Web). [27] Even though artificial intelligence isn?t a new field, we?re a long, long way from producing something that, as Gideon Lewis-Kraus wrote in The New York Times Magazine, can “demonstrate a facility with the implicit, the interpretive.” [28]

Experts involved with the National Science and Technology Council (NSTC)? Committee on Technology ?believe that it will take decades before society advances to artificial “general” intelligence. [22] Even people who study AI have a healthy respect for the field’s ultimate goal, artificial general intelligence, or an artificial system that mimics human thought patterns. [28] For some, the phrase “artificial intelligence” conjures nightmare visions — something out of the ?04 Will Smith flick I, Robot, perhaps, or the ending of Ex Machina — like a boot smashing through the glass of a computer screen to stamp on a human face, forever. [28] In most of these works, “AI” isn’t used as the name of a field but rather to refer to specific entities as “artificial intelligences”. [27]

The generally accepted definition of AI as “the theory and development of computer systems able to perform tasks normally requiring human intelligence” can be further broken down into its respective sub-disciplines. [24]


Proposed “universal intelligence” tests aim to compare how well machines, humans, and even non-human animals perform on problem sets that are generic as possible. [2] Moravec’s paradox generalizes that low-level sensorimotor skills that humans take for granted are, counterintuitively, difficult to program into a robot; the paradox is named after Hans Moravec, who stated in 1988 that “it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility”. [2] Are there limits to how intelligent machines- or human-machine hybrids- can be? A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that would possess intelligence far surpassing that of the brightest and most gifted human mind [2] Ronald, E. M. A. and Sipper, M. Intelligence is not enough: On the socialization of talking machines, Minds and Machines, vol. 11, no. 4, pp.567-576, November 2001. [2] The Dartmouth proposal “Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it.” [2] Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter’s turtles and the Johns Hopkins Beast. [2] Even specific straightforward tasks, like machine translation, require that a machine read and write in both languages ( NLP ), follow the author’s argument ( reason ), know what is being talked about ( knowledge ), and faithfully reproduce the author’s original intent ( social intelligence ). [2] Machines with intelligence have the potential to use their intelligence to make ethical decisions. [2]

The new intelligence could thus increase exponentially and dramatically surpass humans. [2] The general problem of simulating (or creating) intelligence has been broken down into sub-problems. [2] Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence. [2] Turing, Alan (October 1950), “Computing Machinery and Intelligence”, Mind, LIX (236): 433-460, doi : 10.1093/mind/LIX.236.433, ISSN 0026-4423. [2] That said, computer intelligence isn?t our generation’s Golem or Frankenstein’s creation. [29] Sub-symbolic methods manage to approach intelligence without specific representations of knowledge. [2] Explore how we harness talent, data and intelligence to reinvent operations. [5] The timeline for some of these changes is unclear, as predictions vary about when self-driving cars will become a reality: BI Intelligence predicts fully-autonomous vehicles will debut in 2019; Uber CEO Travis Kalanick says the timeline for self-driving cars is “a years thing, not a decades thing”; Andrew Ng, Chief Scientist at Baidu and Stanford faculty member, predicted in early 2016 that self-driving cars will be mass produced by 2021. [1] “?Superintelligence?? may also refer to the form or degree of intelligence possessed by such an agent. [2] Because the capabilities of such an intelligence may be impossible to comprehend, the technological singularity is an occurrence beyond which events are unpredictable or even unfathomable. [2]

These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning”), the use of particular tools (“logic” or artificial neural networks ), or deep philosophical differences. [2] Those algorithms come under different names: deep artificial neural networks, support-vector machines, Gaussian models, multilayer perceptrons, LSTMs, convolutional networks, logistic regression, random forests. [6] According to one overview, the expression “Deep Learning” was introduced to the Machine Learning community by Rina Dechter in 1986 and gained traction after Igor Aizenberg and colleagues introduced it to Artificial Neural Networks in 2000. [2] Similar to shallow artificial neural networks, deep neural networks can model complex non-linear relationships. [2] This layered framework is often referred to as an artificial “neural network” because of its intended resemblance to neural networks in human brains. [4] Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. [2] An agent that solves a specific problem can use any approach that works – some agents are symbolic and logical, some are sub-symbolic artificial neural networks and others may use new approaches. [2] Amazon uses artificial neural networks to generate these product recommendations. [1] Many people concerned about risk from superintelligent AI also want to limit the use of artificial soldiers. [2] An evolutionary system can induce goals by using a ” fitness function ” to mutate and preferentially replicate high-scoring AI systems; this is similar to how animals evolved to innately desire certain goals such as finding food, or how dogs can be bred via artificial selection to possess desired traits. [2] The first work that is now generally recognized as AI was McCullouch and Pitts ‘ 1943 formal design for Turing-complete “artificial neurons”. [2]

This issue was addressed by Wendell Wallach in his book titled Moral Machines in which he introduced the concept of artificial moral agents (AMA). [2] The neural network – technically an “artificial neural network” since it’s based on how we think the brain works – provides the math that makes it work. [3] Approaches based on cybernetics or artificial neural networks were abandoned or pushed into the background. [2] Artificial neural networks are an example of soft computing they are solutions to problems which cannot be solved with complete logical certainty, and where an approximate solution is often sufficient. [2] Deep learning is any artificial neural network that can learn a long chain of causal links. [2]

The artificial brain argument The brain can be simulated by machines and because brains are intelligent, simulated brains must also be intelligent; thus machines can be intelligent. [2] “A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures”. [2]

Joseph Weizenbaum wrote that AI applications cannot, by definition, successfully simulate genuine human empathy and that the use of AI technology in fields such as customer service or psychotherapy was deeply misguided. [2] Definition: AI is math and code that makes decisions about data. [6] A more formal definition of machine learning used at Intel is: “the construction and study of algorithms that can learn from data to make predictions or decisions.” [3] The definition used in this article, in terms of goals, actions, perception and environment, is due to Russell & Norvig (2003). [2]

Other definitions also include knowledge and learning as additional criteria. [2] Google offers a tool where you can actually play with a neural network in your browser, and also offers a simplified definition: “First, a collection of software “neurons? are created and connected together, allowing them to send messages to each other. [3] The definition of algorithm is simply a combination of math and logic, and the logic is written in code. [6] It must further personalize its results based on your own definition of what constitutes spam–perhaps that daily deals email that you consider spam is a welcome sight in the inboxes of others. [1]

Many of the problems in this article may also require general intelligence, if machines are to solve the problems as well as people do. [2] Some cognitive architectures are custom-built to solve a narrow problem; others, such as Soar, are designed to mimic human cognition and to provide insight into general intelligence. [2]

To simplify the discussion, think of AI as the broader goal of autonomous machine intelligence, and machine learning as the specific scientific methods currently in vogue for building AI. All machine learning is AI, but not all AI is machine learning. [1] IEEE Transactions on Computational Intelligence and AI in Games. 5 (4): 293-311. doi : 10.1109/TCIAIG.2013.2286295. [2] The application of soft computing to AI is studied collectively by the emerging discipline of computational intelligence. [2] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. [2]

Applied Computational Intelligence and Soft Computing. 2012 : 1-20. doi : 10.1155/2012/850160. [2] IEEE Computational Intelligence Magazine. 9 (2): 48-57. doi : 10.1109/MCI.2014.2307227. [2]

The field was founded on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”. [2] The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. [30]

The main areas of competition include general machine intelligence, conversational behavior, data-mining, robotic cars, and robot soccer as well as conventional games. [2]

Thought-capable artificial beings appeared as storytelling devices in antiquity, and have been common in fiction, as in Mary Shelley’s Frankenstein or Karel ?apek’s R.U.R. (Rossum’s Universal Robots). [2]

In a computer simulation of their new artificial neural network design, they provided thousands of handwriting samples. [11] Being a property (not some sort of physical thing ) you should not apply the term “artificial” to it. [7] Signals act like artificial neurons and move across thousands of arrays to particular cross points, which function like synapses. [11] According to Kim, the design and materials that have been used to make these artificial synapses thus far have been less than ideal. [11]

Its A.I. technology learned from relatively few examples to mimic human visual intelligence, using data 300 times more efficiently than deep learning models. [12] This is more-so a form of augmented intelligence because the human operator has a large say in the creative process. [10]

Business intelligence (BI) and analytics vendors use machine learning in their software to help users automatically identify potentially important data points. [8] Credit Jason Henry for The New York Times The technology struggles in the more open terrains of intelligence — that is, meaning, reasoning and common-sense knowledge. [12] “There is no real intelligence there,” said Michael I. Jordan, a professor at the University of California, Berkeley, and the author of an essay published in April intended to temper the lofty expectations surrounding A.I. “And I think that trusting these brute force algorithms too much is a faith misplaced.” [12] While that program and other efforts vary, their common goal is a broader and more flexible intelligence than deep learning. [12] Intelligence should be regarded as a property of some system (usually biological) but we would like to apply it to hardware. [7] To Implement Human Intelligence in Machines ? Building systems that understand, think, learn, and behave like people. [7]

The machine was trained on dozens of Bitcoin definitions and the project was even described by the creators as a creative endeavour. [10] DJ Patil gives us a broad definition, basically that an AI is anything that can be run by a computer that does an intelligent task (i.e., producing a useful result from a set of information). [7] Statistical knowledge — on top of computational knowledge, experience, and judgment — matters for the definition of the response variable, the separation of the database, the certification of past data use, the separation of data between adjustment, validation and testing, and other sampling steps. [31] As the smart AFCI learns about the devices it encounters, it can simultaneously distribute its knowledge and definitions to every other home using the internet of things. [11] If Sarma and Siegel could embed similar technology into AFCIs, the circuit breakers could detect exactly what product is being plugged in and learn new object definitions over time. [11] The AFCI learns these definitions with the aid of a neural network. [11] The device can help AFCIs learn and update object definitions to prevent “nuisance trips? and make homes safer. [11]

The video was not an attempt to create a machine learning definition of Bitcoin but rather a creative portrayal of the Bitcoin movement in a semi-humorous manner. [10]

AI is all around us, and due to its loose definition (a machine that mimics human behavior and makes “smart? decisions), you don?t have to look very far to find it. [20] Beena is the global vice president for artficial intelligence, data and innovation at HPE. She is also the founder and CEO of Humans for AI. [19] If this new model of augmented intelligence and shared responsibility between man and machine terrifies you and threatens what you consider to be the uniquely human capability of decision-making, I’d suggest that you hold on tight because this storm is going to much worse than you thought. [16] Perhaps it’s time to start calling it what it is, Augmented Intelligence that we need in order to deal with and survive the increasing complexity of the machines and the world we inhabit. [16]

The fatal flaw in AI isn’t the technology or its intelligence, it’s something far more difficult to change. [16] Artifical Intelligence and automation ought to be the new drivers of employment, especially for India’s $150 billion IT industry, which employs over four million people. [18] While most of them claim to be AI-enabled, only a few have managed to achieve conversational intelligence with its proprietary algorithm extending to Language Generation. [14]

The biggest impediment to AI is not the technology but the very term we use to describe it, Artificial. [16] By definition, off-the-shelf AI is suitable for a firm’s use cases that are identical or very similar to other firms? use cases. [19] Consider a computer playing chess; this may not strike many people today as AI, but it certainly fits the definition of a system that has been given rules and calculates probabilities and decisions on the fly based on the moves of the opponent. [18] I disagree with your definition of AI. Machine learning is a subset. [13]

Both the terms are symbiotic but also mutually exclusive in their own right with different definitions. [14] West argues that by expanding the definition of work and encouraging the government to provide benefits, such as health care and retirement contributions, to citizens who are working in nontraditional ways, the United States can alleviate many of the growing pains associated with these technological advancements and avoid major political instability. [17]

AI is software that is meant to perform functions that human intelligence can undertake like learning and problem solving among other things like reasoning, planning, perception as well as Natural Language Understanding (NLU) and Natural Language Processing (NLP). [14]

RANKED SELECTED SOURCES(31 source documents arranged by frequency of occurrence in the above report)

1. (90) Artificial intelligence – Wikipedia

2. (14) What is artificial intelligence? – Quora

3. (10) The Trump Administrations take on Artificial Intelligence (AI) – without bullshit

4. (9) Everyday Examples of Artificial Intelligence and Machine Learning

5. (9) Revolutionizing everyday products with artificial intelligence | MIT News

6. (8) Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So – The New York Times

7. (8) National Security Commission Artificial Intelligence Act of 2018 (HR 5356 / S 2806, 115th Congress) | SciPol

8. (8) From AI to ML to AI: On Swirling Nomenclature Slurried Thought Approximately Correct

9. (6) Artificial intelligence creates creative definition of Bitcoin using predictive keyboard

10. (6) Definition Of Artificial Intelligence

11. (5) AI and Its Impact On Humanity – DZone AI

12. (5) It’s Time to Stop Calling It ‘Artificial’ Intelligence |

13. (4) Can Artificial Intelligence transform India? | Deccan Herald

14. (4) Artificial Intelligence | Intel Newsroom

15. (4) MIT fed an AI data from Reddit, and now it only thinks about murder – The Verge

16. (4) Artificial Intelligence: A Definition for Colocation Providers

17. (4) Definition of Artificial Intelligence (AI) – Deeplearning4j: Open-source, Distributed Deep Learning for the JVM

18. (3) Artificial intelligence: Do it your way – SD Times

19. (3) IBM’s Project Debater uses artificial intelligence to debate a human

20. (2) Artificial intelligence will disrupt the future of work. Are we ready?

21. (2) Everything HR Needs to Know About Artificial Intelligence – #HR Bartender

22. (2) Artificial Intelligence Definition | Its the future|

23. (2) Demystifying Artificial Intelligence: Informed Definitions of Key AI-Related Terminology — zenruption

24. (2) Artificial Intelligence | Accenture

25. (2) What is machine learning (ML)? – Definition from

26. (1) Government robots, chatbots are coming — better define their role now | TheHill

27. (1) [1806.04915] The IQ of Artificial Intelligence

28. (1) AI is a threat to humanity, depending on how you define it

29. (1) artificial intelligence | Definition of artificial intelligence in English by Oxford Dictionaries

30. (1) Updating the Definition of Data Scientist as Machine Learning Evolves – AI Trends

31. (1) Forrester : Artificial Intelligence (AI)