Will Artificial Intelligence Help Us Solve Every Problem?

C O N T E N T S:

KEY TOPICS

  • We have a new tool to help us better manage the impacts of climate change and protect the planet: artificial intelligence (AI).(More…)
  • Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans.(More…)

POSSIBLY USEFUL

  • Machine learning, which developed out of earlier AI, involves the use of algorithms (sets of rules to follow to solve a problem) that can learn from data.(More…)
  • 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”.(More…)
  • What my colleagues and I would like (I’m also a skeptic of strong AI), then, is some good reason for thinking that however far AI is developed with advances in hardware and software, there will always remain a sharp discontinuity between machine and human intelligence, a discontinuity that cuts so deep and marks such a hard divide between the two that we can safely set aside the worry that machines will supplant us.(More…)

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Will Artificial Intelligence Help Us Solve Every Problem?
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KEY TOPICS

We have a new tool to help us better manage the impacts of climate change and protect the planet: artificial intelligence (AI). [1] This is just one example of “mission-driven artificial intelligence”–the responsible application of artificial intelligence (AI) to solve societal and ecological challenges. [2] Artificial intelligence systems can simulate potential zoning laws, building ordinances, and flood plains to help with urban planning and disaster preparedness. [1] Artificial intelligence can also help predict the spread of invasive species, follow marine litter, monitor ocean currents, keep track of dead zones and measure pollution levels. [1] As vehicles become able to communicate with each other and with the infrastructure, artificial intelligence will help drivers avoid hazards and traffic jams. [1]

Artificial Intelligence (AI), defined as the capability of machines to imitate intelligent human behavior and learn from data, is considered by many to be the final frontier of computing. [3]

Machine Learning provides Artificial Intelligence with the ability to learn and adapt and solve problems on its own based on some algorithms. [4] On top of the articles shared by Sol Palha, this article will help you understand more on the concepts around artificial intelligence. [4]

My instincts tell me we need a sense of urgency around the use of artificial intelligence (AI) in manufacturing. [5] AI refers to computer systems that “can sense their environment, think, learn, and act in response to what they sense and their programmed objectives,” according to a World Economic Forum report, Harnessing Artificial Intelligence for the Earth. [1] Artificial intelligence has been around since the late 1950s, but today, AI’s capacities are rapidly improving thanks to several factors: the vast amounts of data being collected by sensors (in appliances, vehicles, clothing, etc.), satellites and the Internet; the development of more powerful and faster computers; the availability of open source software and data; and the increase in abundant, cheap storage. [1] The Department of Energy’s SLAC National Accelerator Laboratory operated by Stanford University will use machine learning and artificial intelligence to identify vulnerabilities in the grid, strengthen them in advance of failures, and restore power more quickly when failures occur. [1] Microsoft believes that artificial intelligence, often encompassing machine learning and deep learning, is a “game changer” for climate change and environmental issues. [1] At TechEmergence, we?ve developed concrete definitions of both artificial intelligence and machine learning based on a panel of expert feedback. [6] TechEmergence conducts direct interviews and consensus analysis with leading experts in machine learning and artificial intelligence. [6] Before we can master the creation of artificial intelligence, we first need to describe what intelligence is–and that’s a problem that neither programmers nor philosophers are properly equipped to handle. [7] The synergistic approach in the former shows that by pairing human intelligence with artificial intelligence, the overall grading system costs less and accomplishes more. [6] When you watch a film about artificial intelligence or hear it discussed in public, it’s usually hyped up in some way. [7] The team is using artificial intelligence to analyze the high-resolution photographs and match them with Uriarte’s data–she has mapped and identified every single tree in given plots. [1] There’s a product launch almost every day boasting a new spin on Artificial Intelligence, and when even white goods manufacturers are getting involved it starts to feel like we?ve hit “peak AI?. [8] Uriarte says her work could not be done without artificial intelligence. [1] Recent breakthroughs in artificial intelligence offer enormous benefits for mission-driven organizations and could eventually revolutionize how they work. [2] Thanks for staying in touch we’re glad to keep you ahead of the curve on the applications and implications of artificial intelligence. [6]

Artificial intelligence (AI) is usually defined as “a part of computer science involving the computer software study focused on helping machines make practical decisions, solve problems and perform complex reasoning.” [9] She suggests that the answer won?t be piecing together algorithms, as we often do to solve complex problems with artificial intelligence. [10]

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. [4] Artificial Intelligence is a branch of Computer Science dedicated to creating intelligent machines that work and react like humans. [4]

Artificial intelligence ( AI, also machine intelligence, MI ) is intelligence demonstrated by machines, in contrast to the natural intelligence ( NI ) displayed by humans and animals. [11] Artificial intelligence and machine learning, a method of AI, make it possible to build special-purpose machines to perform useful cognitive tasks, in some cases better than humans. [12] Can you draw a line cutting through data, machine learning and artificial intelligence, from the above explanation? Data that is fed by a data scientist is facilitating machine learning, while machine learning is a method that is facilitating AI. [4] 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. [11] Potential clinical uses of artificial intelligence (AI) receive much attention but actual real-world applications are far less common. [13] 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. [11] Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the AI effect. [11] Artificial intelligence is the field of study devoted to making machines intelligent. 3 Intelligence measures a system’s ability to determine the best course of action to achieve its goals in a wide range of environments. 4 The field of AI has a number of sub-disciplines and methods used to create intelligent behavior, and one of the most prominent is machine learning. [12] Artificial Intelligence (AI) and Machine Learning (ML) are two extremely hot buzzwords at the present time, and frequently appear to be utilized reciprocally. [4] We are in the midst of an ever accelerating and expanding global revolution in artificial intelligence (AI) and machine learning, with enormous implications for future economic and military competitiveness. [12] 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. [11] A couple of tech terms you may have heard lately are Artificial Intelligence (AI) and Machine Learning (ML). [14] Artificial Intelligence (AI) and machine learning have now given ordinary citizens (i.e. those who aren?t necessarily rich or powerful) a disproportionate ability to influence people’s hearts and minds on a major scale. [15] 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. [11] It is intended as an introduction to the impact of advances in artificial intelligence for national security and an initial exploration into how AI may change the international security environment. [12] 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”. [11] 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. [11] What Is AI? – An introduction to artificial intelligence by John McCarthy –a co-founder of the field, and the person who coined the term. [11] Artificial Intelligence is empowering machines to behave like humans. [4] Artificial Intelligence can be defined as any code, technique or algorithm which enables a machine to mimic human cognitive processes; thus, the phrase “artificial intelligence”. [4] 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. [11] Deep Learning makes it possible for Artificial Intelligence to function like a human, and probably even a more intelligent version of a human. [4] Artificial intelligence is a branch of computer science that aims to create intelligent machines. [4] 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. [11] The implications of a constructed machine exhibiting artificial intelligence have been a persistent theme in science fiction since the twentieth century. [11] Nations with access to the best data, computing resources, human capital, and processes of innovation are poised to leap ahead in the era of artificial intelligence. [12] 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. [11] 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. [11] Deep learning has transformed many important subfields of artificial intelligence, including computer vision, speech recognition, natural language processing and others. [11] IBM has created its own artificial intelligence computer, the IBM Watson, which has beaten human intelligence (at some levels). [11] Throughout the novel, Dick portrays the idea that human subjectivity is altered by technology created with artificial intelligence. [11] 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.” [11] The development of full artificial intelligence could spell the end of the human race. [11] Once humans develop artificial intelligence, it will take off on its own and redesign itself at an ever-increasing rate. [11] Other counterarguments revolve around humans being either intrinsically or convergently valuable from the perspective of an artificial intelligence. [11] 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. [11] “AlphaGo beats human Go champ in milestone for artificial intelligence”. latimes.com. [11] Artificial intelligence isn’t an industry so much as a technology poised to transform business across a wide variety of sectors–and probably more than you think. [16] Young technology enthusiasts are opting for artificial intelligence developer as a profession, enterprises are looking for ways to opt artificial intelligence software development to revamp their business operations. [4]

Banks use artificial intelligence systems today to organize operations, maintain book-keeping, invest in stocks, and manage properties. [11] Widespread use of artificial intelligence could have unintended consequences that are dangerous or undesirable. [11] Note that they use the term “computational intelligence” as a synonym for artificial intelligence. [11] This approach to the philosophical problems associated with artificial intelligence forms the basis of the Turing test. [11] Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th ed.). [11] “Some philosophical problems from the standpoint of artificial intelligence”. [11]

Radiation treatment planning is one clinical problem that Adaptive Intelligence can help us solve. [13]

Now, do we really differentiate between Artificial Intelligence and Machine Learning? It is obvious, that there is a difference, but we cannot separate them. [4] We have for long heard the phrase Artificial Intelligence, more so because of exhilarating movies like the Matrix and The Terminator. [4] Adaptive Intelligence combines artificial intelligence and other methods with knowledge of the clinical, operational, or personal context in which they are used, so it is able to do a better job of satisfying all those constraints more quickly and with fewer iterations. [13] In video games, artificial intelligence is routinely used to generate dynamic purposeful behavior in non-player characters (NPCs). [11]

While the debate rages on about artificial intelligence and how it will affect the workforce of those in developed nations, those in developing nations could benefit from the intervention of technology into their lives. [17] Artificial Intelligence, a term authored by a computer scientist John McCarthy, depended on the ideas of an English mathematician Alan Turing, frequently alluded to as the father of modern computers. [4] “Bill Gates on dangers of artificial intelligence: ‘I don’t understand why some people are not concerned ‘ “. [11] After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. [11] Over the past five years Artificial Intelligence Development has boomed the world. [4] “Content: Plug & Pray Film – Artificial Intelligence – Robots -“. plugandpray-film.de. [11] “Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence” (PDF). [11]

Artificial intelligence can help companies — even small businesses — solve everyday problems. [18] Today’s artificial intelligence (AI) systems are narrow AIs: they can excel in one domain (like arithmetic calculations, playing chess, etc) but they cannot solve problems in new domains. [19]

Grantees of Microsoft’s AI for Earth, a program aimed at helping groups address complex environmental problems, met at Microsoft headquarters recently to learn new ways to apply artificial intelligence and cloud computing to their respective projects. [20] While we?re growing more used to the idea of AI completing practical or empirical tasks, common sense says the world of human creativity should be beyond the grasp of artificial intelligence. [21] Artificial intelligence promises to enhance human content creation in the realm of editing, as well. 20th Century Fox recently made a splash when they hired IBM’s AI, Watson, to select the most appropriately dramatic scenes for a human editor to include in a trailer for the 2016 movie Morgan. [21] That definition inclines toward what experts consider “strong AI,” which focuses on artificial intelligence systems that are as much as flexible as the human brain when it comes to performance. [9] AI Business is the world’s first news portal dedicated to the advancement of Artificial intelligence and it’s impact on business. [22] Artificial Intelligence (AI) has received a lot of attention due to its hype in the startup sector. [9] Most of the healthcare data collected is unstructured data that is very difficult to use in artificial intelligence applications. [23] Pediatric Bone Age Assesment Another major problem with artificial intelligence solutions in healthcare is the data problem. [23] How do you describe the analysis results in a way that everyone understands? This is precisely why we need Artificial Intelligence to reshape data into easy-to-understand insights at scale. [9] The term artificial intelligence came into being in 1956, but its popularity has increased today, thanks to high data volumes, advanced algorithms, and efficiency in computing power and storage. [9] Chalmers argued that a machine, one more advanced than we have today, could become conscious, but Koch disagreed, based on the current state of neuroscience and artificial intelligence technology. [10] Artificial intelligence aims to refine and empower machines with cognitive capabilities to develop an intelligent agent that understands its environment and performs actions that heighten the chance of success to achieve the goal. [9] Studies have shown artificial intelligence algorithms–including those robots use to identify people and objects–tend to reflect their developers’ inherent gender and racial biases. [24] Byron explores issues around artificial intelligence and conscious computers in his new book The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity. [25] The problem areas that artificial intelligence applications in healthcare are able to tackle could go a long way towards solving the global healthcare crisis. [23] If we look closer, we find that artificial intelligence in TV and film production isn?t a threat to human creativity; it’s an exciting tool with the potential to push our audiovisual experiences to new heights. [21] How can many dashboards be described all at once? As artificial intelligence applies reasoning to data, it can define what this information means at scale. [9] There are several problems presented by artificial intelligence solutions in healthcare, however. [23] Even Jordan, the editor who sounded the alarm bell on the artificial intelligence disruption to the editing industry, writes that AI’s ability to do high-level, emotionally and narratively complex editing will take some time to develop. In the meantime, Jordan writes, content creators will have an opportunity to learn new skills and adapt. [21] Artificial intelligence offers content creators the potential to take much of the perspiration out of making TV and film, leaving creators more time to make more compelling shows, more exciting videos and “stickier” advertising content. [21] Diabetic Retinopathy Detection Besides diagnostic assistance and treatment identification, artificial intelligence solutions are also in development for behavior analysis — including ensuring whether or not healthcare professionals wash their hands, and tracking how much time is spent with patients. [23] You may insert your own quip about God making man in his own image here if you wish, but what a way for artificial intelligence to enter the universe. [26] Beran gave the example of works of art generated by artificial intelligence. [10] Mongabay’s Rhett Butler moderates a grantee panel featuring Fei Fang of Carnegie Mellon University, Matthew McKown of Conservation Metrics, and Jason Holmberg of WildMe discussing their work with artificial intelligence for their respective conservation projects. [20] We could conservatively estimate that each of these could benefit from custom-built artificial intelligence powered diagnostic, therapeutic and management tools, putting the eventual number of potential stand-alone artificial intelligence solutions in the hundreds. [23] We haven’t found satisfactory definitions in the 70 years since artificial intelligence first emerged as an academic pursuit. [10] In recent years, countries and companies have turned to the latest breakthroughs in Artificial Intelligence. [22] In the future, we may even have fully robotic surgery powered by artificial intelligence. [23] Take, for example, an article recently published on BBC, which tried to grapple with the idea of artificial intelligence with a soul. [10]

Conversations today around artificial intelligence (AI) — machine learning, automation and natural language processing — often focus on the sensational, eye-catching aspects of the technology. [18] Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. [27]

POSSIBLY USEFUL

Machine learning, which developed out of earlier AI, involves the use of algorithms (sets of rules to follow to solve a problem) that can learn from data. [1] “I believe that for every environmental problem, governments, non-profits, academia and the technology industry need to ask two questions: “How can AI help solve this?? and “How can we facilitate the application of AI??,” Joppa said. [3] “It’s how AI could actually help us save the planet and solve scientific mysteries.” [3]

In marketing, AI will help us communicate in a more sophisticated way and retain customers?–?only using the data they give us to ensure we never send them something irrelevant. [8] Data from sensors in the field that monitor crop moisture, soil composition and temperature help AI improve production and know when crops need watering. [1] We?ll use AI to help people understand whether the asking price for a property is fair. [8]

Instead of supporting AI progress, it actually jeopardizes the value of machine intelligence by disregarding important AI safety principles and setting unrealistic expectations about what AI can really do for humanity. [28] 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. [6] To be clear, AI is a broad term that captures the constantly evolving advances in machines’ capabilities to perform tasks that would ordinarily require human intelligence. [2] The public sector typically lacks the human talent with the right technological capabilities to fully reap the benefits of machine intelligence. [28] Not every problem is best addressed by applying machine intelligence to it. [28]

As a Senior Publisher for Elsevier’s Computer Science journals, Sweitze Roffel focuses on artificial and computational intelligence and theory. [29] Dr. Gary Marcus is Professor of Psychology and Neural Science, New York University, former CEO of the machine learning startup Geometric Intelligence, acquired by Uber in 2017. [29] Our approach to AI solves genuine customer problems that make the traditional brokerage model so flawed. [8]

“My greatest hope for the technology is that we will be able to do automated scientific reasoning, and use it to solve problems like cancer that, because of the sheer number of molecular interactions, are too complex for humans to understand. [29] She writes: “My biggest hope would be that AI could solve some of the biggest problems we have. [29] Can we solve these problems and keep moving toward a general AI? Slowly but surely, the answer is yes. [7] To wit, Microsoft announced in December 2017 that it is expanding its “AI for Earth” program and committing $50 million over the next five years to put AI technologies in the hands of individuals and organizations working to solve global environmental challenges, including climate change as well as water, agriculture and biodiversity issues. [3]

The company’s AI for Earth program has committed $50 million over five years to create and test new applications for AI. Eventually it will help scale up and commercialize the most promising projects. [1] AI remains a tool – albeit a powerful one – and like any tool, whether it harms or helps is largely up to the user. [29] We help leaders gain insight on the applications and implications of AI in their industry. [6] The IBM Watson for Oncology programme was a piece of AI that was meant to help doctors treat cancer. [28] AI can help to monitor ecosystems and wildlife and their interactions. [1] AI helps us make these conversations more efficient for everyone involved. [8]

To tap into external data sources, organizations can also use data analytics solutions such as Tableau and Alteryx, which both have programs to help mission-driven organizations use their platforms. [2] Google used machine learning to help predict when its data centers? energy was most in demand. [1] Incorporating this information with that from drones, which are also used to monitor conditions, can help increasingly automatic AI systems know the best times to plant, spray and harvest crops, and when to head off diseases and other problems. [1]

Currently the algorithm analyzes past ranger patrols and poachers? behavior from crime data; a Microsoft grant will help train it to incorporate real-time data to enable rangers to improve their patrols. [1]

This is the philosophy that, given enough data, machine learning algorithms can solve all of humanity’s problems. [28] Build a small team, start collecting data around a pilot business problem, and learn how the best approaches can solve a manufacturing problem. [5]

These are some of the biggest–yet least popularized–problems we?ll have to solve to keep moving forward in the realm of AI. 1. [7] Companies like Salesforce and Intuit (the developer of QuickBooks) are able to draw upon the data of many customers, which solves this challenge for many capacity-building applications. [2] Like reasonable wealth distribution – how do we reward merit and provide motivation while ensuring that enough people have enough money to employ each other and keep societies together? That’s been a really hard problem to solve for 1,000 years. [29] At the other end, people picture algorithms so powerful they can solve every major problem facing mankind. [29] “My greatest fear is that it would be used to solve more nefarious problems. [29] Prof. Gary Marcus, NYU: “My greatest fear is that it would be used to solve more nepharious problems.” [29]

It should be a tool to solve genuine problems?–?problems that it would be impractical or impossible for a human to tackle. [8]

Amazon uses artificial neural networks to generate these product recommendations. [6] 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. [6] While I?ve written before that I think the reality of AI’s “intelligence” is complex mathematics, I got a more enlightened vision when I posed that view to a true expert. [5]

CEO Austin Buchin notes that the organization’s plan is to eventually help these partner programs pool their data with data-sharing agreements, and when they do, “the quality of the predictions is going to skyrocket.” [2] By improving weather forecasts, these types of programs can help keep people safe. [1]

Where it can?t understand a question, we can have an expert human adviser seamlessly interject to help. [8] New software development platforms from Google, Amazon, Microsoft, and others help automate the process of building machine learning systems, which lowers barriers and greatly expands the number of software developers capable of wielding these tools on the behalf of mission-driven organizations. [2] The “social movement ecology” framework can help funders collaborate with organization that operate using other theories of change. [2] This will help improve the accuracy of climate change projections. [1]

Big Think Edge helps organizations by catalyzing conversation around the topics most critical to 21st century business success. [28] How well are you harnessing information to improve business outcomes? A new CIO Playbook will help. [7] This can help decision-makers determine the most important areas for fish productivity and conservation efforts, as well as the tradeoffs of potential decisions. [1]

Chatbots help organizations improve their responsiveness by responding conversationally to requests for information and other simple questions, much like an automated frequently asked questions (FAQs). [2] Their expertise helps train the algorithm and, with the advent of Open Banking, it will help them to provide the best advice. [8] It will also make our communication strategy more efficient by reducing the man-hours needed to help customers through our journey. [8] Another IBM system in development could help cities plan for future heat waves. [1]

Similar problems arose in the legal domain when algorithms were used in courts in the U.S. to sentence criminals. [28] According to a 2015 report by the Texas Transportation Institut e at Texas A&M University, commute times in the U.S. have been steadily climbing year-over-year, resulting in 42 hours of rush-hour traffic delay per commuter in 2014–more than a full work week per year, with an estimated $160 billion in lost productivity. [6]

You want diversity in order to be able to solve a lot of different problems. [29]

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”. [11] It uses AI (a computer system that can perform tasks that normally require human intelligence) to process data. [15] 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.” [11] 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. [11] Many of the problems in this article may also require general intelligence, if machines are to solve the problems as well as people do. [11] 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. [11]

In the twenty-first century, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and AI techniques have become an essential part of the technology industry, helping to solve many challenging problems in computer science. [11] AI has developed a large number of tools to solve the most difficult problems in computer science. [11]

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. [11] 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. [11] Many people concerned about risk from superintelligent AI also want to limit the use of artificial soldiers. [11]

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. [11] 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 ). [11] 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. [11] “Artificial intelligence” has been misused to describe almost kind of computerized analysis or automation, regardless of whether the technology can be described as “intelligent”. [4] For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology. [11] 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. [11] In 2017, Vladimir Putin stated that “Whoever becomes the leader in (artificial intelligence) will become the ruler of the world”. [11] Artificial General Intelligence (AGI) refer to human-level intelligence capable of abstracting concepts from limited experience and transferring knowledge between domains. [4]

AI has applications for defense, intelligence, homeland security, diplomacy, surveillance, cybersecurity, information, and economic tools of statecraft. [12] The application of soft computing to AI is studied collectively by the emerging discipline of computational intelligence. [11] IEEE Transactions on Computational Intelligence and AI in Games. 5 (4): 293-311. doi : 10.1109/TCIAIG.2013.2286295. [11] Approaches include statistical methods, computational intelligence, and traditional symbolic AI. [11]

Their algorithm was able to play near or above human level at more than half of the 49 games it played. (A different algorithm had to be trained for each game, due to catastrophic forgetting; the moves in Pac-Man are different than the moves in Asteroids, so learning how to play one does not help an AI learn to play the other.) [12] Next week professional services firm Accenture will be launching a new tool to help its customers identify and fix unfair bias in AI algorithms. [30] Information processing and solution finding are the backbone of AI, and enlisting its help can generate the data required by global initiatives to identify regions in the greatest need of aid. [17] Feature detection (pictured: edge detection ) helps AI compose informative abstract structures out of raw data. [11] Humans also have a powerful mechanism of ” folk psychology ” that helps them to interpret natural-language sentences such as “The city councilmen refused the demonstrators a permit because they advocated violence”. (A generic AI has difficulty inferring whether the councilmen or the demonstrators are the ones alleged to be advocating violence.) [11] The UN is developing strategies at conferences like AI for Good Global Summit to figure out how AI can help them fulfill their Sustainable Development Goals, while the World Bank is taking a more direct approach. [17] According to Bloomberg Technology, Microsoft has developed AI to help doctors find the right treatments for cancer. [11]

Now, you may ask how does the Machine do that? How does it learn without being programmed? This is where data comes in, the machines are fed huge amounts of data, that helps the defined set of algorithms in training themselves to perform a task automatically. [4] Data classification – AI systems can be used to help classify data, from images to song genres to medical imagery and diagnosis. 27 In many cases, AI systems can classify data more reliably and accurately than humans. [12] Some deep neural networks used for image recognition can have hundreds of thousands of artificial neurons. 8 Neural networks can learn via supervised learning, unsupervised learning, or reinforcement learning, depending on whether the data used to train the neural network is labeled, unlabeled, or comes from environmental feedback. [12] Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. [11]

The first work that is now generally recognized as AI was McCullouch and Pitts ‘ 1943 formal design for Turing-complete “artificial neurons”. [11] 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. [11] This issue was addressed by Wendell Wallach in his book titled Moral Machines in which he introduced the concept of artificial moral agents (AMA). [11]

Machines with intelligence have the potential to use their intelligence to make ethical decisions. [11] The field was founded on the claim that human intelligence “can be so precisely described that a machine can be made to simulate it”. [11] 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.” [11] 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. [11] 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 ). [11] The main areas of competition include general machine intelligence, conversational behavior, data-mining, robotic cars, and robot soccer as well as conventional games. [11] 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”. [11] The result is an “idiot-savant” form of intelligence; AI systems may perform far better than humans in some areas while simultaneously failing to exhibit common sense. [12] 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 [11] The new intelligence could thus increase exponentially and dramatically surpass humans. [11]

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. [11] Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence. [11] The general problem of simulating (or creating) intelligence has been broken down into sub-problems. [11] The narrow nature of current AI systems can make their intelligence “brittle.” [12]

Markets, technologies, and people are changing faster than ever, and we want an AI assistant to serve us, solve our queries, warn us of upcoming issues, and protect us from fraud. [31] “Tech can definitely help but part of this is having people understand that this is an informational tool, it will help you, but it’s not going to solve all your problems for you.” [30] Does engaging conversation help us solve our problems? According to a survey by Oracle, 80 percent of businesses say they already use or plan to use chatbots by 2020. [31]

Rather than being a drawback, this flexibility is precisely the point of designing an AI system – to allow a machine to determine the best course of action to solve a problem, given a variety of potential environmental conditions. [12] His laboratory at Stanford ( SAIL ) focused on using formal logic to solve a wide variety of problems, including knowledge representation, planning and learning. [11] They solve most of their problems using fast, intuitive judgements. [11]

Data will have multi dimensions- Type (quantitative or qualitative), amount (big or small size) and number of variables available to solve a problem. [4] “Previously people didn’t have that ability to visualize and understand that their data may actually not be adequate for what they’re trying to solve for.” [30]

Input data flows into one end of the network, then signals cascade across the network through the artificial neurons to an output layer. [12] Deep learning is any artificial neural network that can learn a long chain of causal links. [11] Neural networks are loosely inspired by biological neurons and use a series of artificial neurons connected in a layered network. [12] 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. [11] 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. [11]

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. [11] 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). [11] Approaches based on cybernetics or artificial neural networks were abandoned or pushed into the background. [11] Similar to shallow artificial neural networks, deep neural networks can model complex non-linear relationships. [11]

Or, you?re a tech founder who’s actively working with AI. In either case, you have the opportunity to help us make new technologies more ethical, equitable and productive. [15] The tool was co-prototyped with the help of a data study group at the UK’s Alan Turing Institute, using publicly available data-sets. [30] “So while this tool does help with corrections it is part of this larger process where you may actually have to go back and get new data, get different data. [30]

According to a recent CSO Online Article, 24% of security professionals want to use AI-based cybersecurity technology to help their organization better identify and communicate risk to the business. [14] As the name implies, this helps to determine that a user is an actual person and not a computer posing as a human. [11] Capital One deployed its own gender neutral chatbot, Eno in 2017 to help customers with their personal money queries so that they did not have to speak to a human. [31]

The right kind of data can help identify issues that impoverished regions face, which, in turn, can lead to solutions. [17] We?re building this technology to help people regain their focus. [15] GrowthBot integrates with over a dozen systems and APIs to help people accomplish more with less distraction. [15] We are working to help people focus, accomplish more, and realize their own genius. [15]

Default logics, non-monotonic logics and circumscription are forms of logic designed to help with default reasoning and the qualification problem. [11] Some are essential to make our site work; others help us improve your user experience. [14] When a disaster hits, those traceable demographics could potentially help identify and track the most vulnerable users (such as women with young children) and get aid to them faster, even in remote or dangerous areas. [17]

Also through developing these kinds of tools to help the process along.” [30] The first part of our tool helps you identify which variables in your dataset that are potentially sensitive are influencing other variables,” she explains. [30] The feedback you provide will help us show you more relevant content in the future. [4] Anomaly detection – AI systems can help detect anomalous behavior, such as fraudulent financial transactions or new malware. 28 AI systems can find anomalies whose signatures are not yet known by analyzing routine patterns of behavior (financial, cyber, or other) and then identifying new behavior that is outside the norm. [12] Better testing and evaluation of AI systems in realistic environments can help identify these behaviors in advance, but this challenge is likely to remain a risk for complex autonomous systems interacting with real-world environments. [12]

The simplest intelligent agents are programs that solve specific problems. [11] Computers are unable to solve the problem, so correct solutions are deemed to be the result of a person taking the test. [11] In practice, it is almost never possible to consider every possibility, because of the phenomenon of ” combinatorial explosion “, where the amount of time needed to solve a problem grows exponentially. [11] To the best of my knowledge, Philips is unique in its ability to solve this very challenging problem and make a significant difference in patient care. [13]

This is roughly 10^100 (a googol) more complex than chess and more than the number of atoms in the known universe. 18 For Go, the number of calculations to mathematically solve the game is so large that the same kinds of brute force methods used in checkers and early chess programs are inadequate. [12]

A study conducted by the McKinsey Global Institute recently estimated that roughly 45 percent of job tasks currently being done in the U.S. economy could be automated using existing technology. [12] This effort by the U.S. Geological Survey (USGS) combines remote sensing and AI to create a frequently updated map of croplands, cropping intensity, productivity, and water use. [20] In all these cases, AI depends on a set of algorithms -a formula or set of rules that neural networks use to process information to help you get an answer. [9]

The company announced that it had brought us one step closer to “real AI ” (an intelligence as smart as a human) with its snappily named Project Debater: a supercomputer dedicated to the art of competitive debating. [26] Those people may treat it as such, since they will view the AI system’s intelligence, emotional expression, behavior, and perhaps even a belief in a god as signs of an internal something that could be defined as a soul. [10]

Another start-up, Sentient.ai, is focusing on evolutionary computation, which is a different branch of machine intelligence entirely from deep learning, and may prove promising in the future. [23] “To me it doesn?t matter whether an AI system has real intelligence All that matters is that it behaves in a manner that makes it beneficial to human society.” [10] What is intelligence, then? I?ll start out by saying it’s a term that does not have a consensus definition, so it’s kind of like you can?t be wrong, no matter what you say. [25] Is it actually intelligent? Is there any concept of actually the–does intelligence mean anything beyond the symptoms of intelligence and I don?t think so. [25]

Yeah, I think that’s just sort of a definition-people use “artificial” because they believe that humans are special. [25] Basically anything-intelligence is the sole domain of humanity and thus anything that is intelligent that’s not human must be artificial. [25]

Compared to the technology that would be required to create artificial sentience — whatever it may look like or however we may choose to define it — even our most advanced engineers are still huddled in caves, rubbing sticks together to make a fire and cook some woolly mammoth steaks. [10]

So our AI problem is that we want to find a way to repeatedly solve the easy questions while carefully escalating the hard questions. [25] You?re using the cat analogy just as kind of a metaphor and you?re saying, “Actually, that technology doesn?t help us solve the problem I?m interested in,” or are you using it tongue-in-cheekily to say, “The technology may be useful, it’s just that that particular use-case is inane.” [25]

RANKED SELECTED SOURCES(34 source documents arranged by frequency of occurrence in the above report)

1. (86) Artificial intelligence – Wikipedia

2. (21) Artificial Intelligence–A Game Changer for Climate Change and the Environment

3. (20) What is artificial intelligence/ML? – Quora

4. (18) Artificial Intelligence | Center for a New American Security

5. (13) Gigaom | Voices in AI Episode 48: A Conversation with David Barrett

6. (12) How Artificial Intelligence (AI) Is The New Business Intelligence

7. (11) Artificial Consciousness: How To Give A Robot A Soul

8. (10) Hopes and fears for AI: the experts’ view

9. (9) Artificial Intelligence as a Force for Good

10. (9) Artificial Intelligence Technologies Could Help Solve The Global Healthcare Crisis – Neuromation

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

12. (9) Avoiding an “us too? approach to AI – The Startup – Medium

13. (8) Scientists tackling conservation problems turn to artificial intelligence

14. (7) Why Content Creators Shouldnt Fear the AI Future of TV & Film

15. (7) Why A.I. can?t solve everything | Big Think

16. (7) Accenture wants to beat unfair AI with a professional toolkit TechCrunch

17. (6) Will We Use Big Data to Solve Big Problems? Why Emerging Technology is at a Crossroads

18. (5) Artificial Intelligence Targets World Hunger and Disaster Relief

19. (5) Artificial Intelligence’s Homunculus Problem: Why AI Is Unlikely Ever to Match Human Intelligence

20. (5) The 5 unsexy problems we need to solve for better AI | InfoWorld

21. (4) How AI can make a difference for cancer patients – Blog | Philips

22. (4) Saving the Earth with Artificial Intelligence (AI)

23. (3) Artificial Intelligence and Machine Learning – whats the difference?

24. (3) An Epidemic of Misdiagnosis: Using AI To Solve A Quiet Crisis In Healthcare

25. (3) AI assistants with a touch of humanity poised to win over customers | ZDNet

26. (3) Real Thinking About Artificial Intelligence – Advanced Manufacturing

27. (2) Beyond the Hype: What Are the Practical Applications for AI? – BizTech

28. (2) Superintelligence: A Balanced Approach – Disruption Hub

29. (2) Can Robotics Solve Its Diversity Problem? – Scientific American

30. (2) Who?d want to be friends with a robot? | 1843

31. (2) artificial intelligence | Definition, Examples, and Applications | Britannica.com

32. (1) How Artificial Intelligence Will Transform Your Business (and Everyone Else’s) | Inc.com

33. (1) Cloud Resources Open Up Healthcare AI Problem-Solving – HealthTech

34. (1) The biggest AI takeaways from TNW2018