Applications of artificial intelligence

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Artificial intelligence (AI) has been used in applications to solve specific problems throughout industry and academia. AI, like electricity or computers, is a general purpose technology that has a multitude of applications. It has enhanced language translation, image recognition, credit scoring, e-commerce and many other domains.[1]

Internet and e-commerce[edit]

Search engines[edit]

Main article: Search engine
See also: Google Search

Recommendation systems[edit]

Main article: Recommendation system
See also: Netflix, Amazon (company), and YouTube

A recommendation system predicts the "rating" or "preference" a user would give to an item.[2][3] Recommender systems are used in a variety of areas, such as generating playlists for video and music services, product recommendations for online stores, or content recommendations for social media platforms and open web content recommenders.[4][5]

Targeted advertising and increasing internet engagement[edit]

Main article: Marketing and artificial intelligence
See also: AdSense and Facebook

AI is used to target web advertisements to those most likely to click on them. It is also used to increase time spent on a website by selecting attractive content. It can predict or generalize the behavior of customers from their digital footprints.[6]

Online gambling companies use AI to improve customer targeting.[7]

Personality computing AI models add psychological targeting to more traditional sociodemographic or behavioral targeting.[8] AI has been used to customize shopping options and personalize offers.[9]

Virtual assistants[edit]

Main article: Virtual assistant

Intelligent personal assistants use AI to understand many natural language requests.[10]

Spam filtering[edit]

Main article: Spam filter

Language translation[edit]

Main article: Machine translation
See also: Microsoft Translator and Google Translate

AI has been used to automatically translate spoken language and textual documents.[11]

Facial recognition and image labeling[edit]

Main articles: Facial recognition system and Automatic image annotation
See also: Face ID and DeepFace

AI has been used in facial recognition systems, with a 99% accuracy rate.[12]

Another AI generates speech that describes images to blind people.[13]

Games[edit]

Games have been an important test of AI's capabilities since the 1950s. In the 21st century, AIs have produced superhuman results in many games, including chess (Deep Blue), Jeopardy! (Watson),[14] Go (AlphaGo),[15][16][17][18][19][20][21] poker (Pluribus[22] and Cepheus),[23] E-sports (StarCraft),[24][25] and general game playing (AlphaZero[26][27][28] and MuZero).[29][30][31][32] AI has replaced hand-coded algorithms in most chess programs.[33] Unlike go or chess, poker is an imperfect-information game, so a program that plays poker has to reason under uncertainty. The general game players work using feedback from the game system, without knowing the rules.

Economic and social challenges[edit]

AI for Good is an ITU initiative supporting institutions employing AI to tackle some of the world's greatest economic and social challenges. For example, the University of Southern California launched the Center for Artificial Intelligence in Society, with the goal of using AI to address problems such as homelessness. At Stanford, researchers use AI to analyze satellite images to identify high poverty areas.[34]

Agriculture[edit]

See also: Precision agriculture and Digital agriculture

In agriculture, AI has helped farmers identify areas that need irrigation, fertilization or pesticide treatments, increasing yield[35] Agronomists use AI to conduct research and development. AI has been used to predict the ripening time for crops such as tomatoes,[36] monitor soil moisture, operate agricultural robots, conduct predictive analytics.[37][38] automate greenhouses,[39] and detect disease and pests.[40][41]

Cybersecurity[edit]

Cybersecurity must confront hacking attacks of many sorts that afflict all kinds of organizations. Security companies have begun to adopt neural networks, machine learning, and natural language processing (NLP) solutions to improve their systems.[42]

Possible applications of AI in cybersecurity include:

Education[edit]

AI tutors allow students to get one-on-one help. They can reduce anxiety and stress for students stemming from tutor labs or human tutors.[44]

AI can create a dysfunctional environment with revenge effects[45] such as technology that hinders students’ ability to stay on task.[46] In other scenario, AI can help educator for student early prediction in virtual learning environment (VLE) such as Moodle.[47] Especially, during the COVID-19 pandemic, learning activity is force to be conducted in online to reduce the virus spread through face-to-face meeting.

Finance[edit]

Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. The use of AI in banking can be began in 1987 when Security Pacific National Bank launched a fraud prevention taskforce to counter the unauthorized use of debit cards.[48] Kasisto and Moneystream use AI.

Banks use AI to organize operations, for bookkeeping, invest in stocks, and manage properties. AI can react to changes when business is not taking place.[49] AI is used to combat fraud and financial crimes by monitoring behavioral patterns for any abnormal changes or anomalies.[50][51][52]

The use of AI in applications such as online trading and decision making has changed major economic theories.[53] For example, AI-based buying and selling platforms estimate individualized demand and supply curves and thus enable individualized pricing. AI machines reduce information asymmetry in the market and thus make markets more efficient.[54]

Trading and investment[edit]

Algorithmic trading involves the use of AI systems to make trading decisions at speeds orders of magnitude greater than any human is capable of, making millions of trades in a day without human intervention. Such high-frequency trading represents is a fast-growing sector. Many banks, funds, and proprietary trading firms now have entire portfolios that are AI-managed. Automated trading systems are typically used by large institutional investors, but include smaller firms trading with their own AI systems.[55]

Large financial institutions use AI to assist with their investment practices. BlackRock’s AI engine, Aladdin, is used both within the company and by clients to help with investment decisions. Its functions includes the use of natural language processing to analyze text such as news, broker reports, and social media feeds. It then gauges the sentiment on the companies mentioned and assigns a score. Banks such as UBS and Deutsche Bank use Sqreem (Sequential Quantum Reduction and Extraction Model) to mine data to develop consumer profiles and match them with wealth management products.[56]

Underwriting[edit]

Online lender Upstart analyzes consumer data and uses machine learning to develop credit risk models that predict default likelihood and for underwriting.[57]

ZestFinance's Zest Automated Machine Learning (ZAML) platform is used for credit underwriting. This platform uses machine learning to analyze data including purchase transactions and how a customer fills out a form) to score borrowers. The platform is particularly useful to assign credit scores to those with limited credit histories.[58]

Audit[edit]

AI makes continuous auditing possible. Potential benefits include reducing audit risk, increasing the level of assurance, and reducing audit duration.[59][quantify]

History[edit]

In the 1980s, AI started to become prominent in finance as expert systems were commercialized. For example, Dupont created 100 expert systems, which helped them to save almost $10 million per year.[60] One of the first systems was the Protrader expert system that predicted the 87-point drop in the Dow Jones Industrial Average in 1986. "The major junctions of the system were to monitor premiums in the market, determine the optimum investment strategy, execute transactions when appropriate and modify the knowledge base through a learning mechanism."[61]

One of the first expert systems to help with financial plans was PlanPowerm and Client Profiling System, created by Applied Expert Systems (APEX). It was launched in 1986. It helped create personal financial plans for people.[62]

In the 1990s AI was applied to fraud detection. In 1993 FinCEN Artificial Intelligence System (FAIS) launched. It was able to review over 200,000 transactions per week and over two years it helped identify 400 potential cases of money laundering equal to $1 billion.[63] These expert systems were later replaced by machine learning systems.[64]

Government[edit]

Main article: Artificial intelligence in government

AI facial recognition systems are used for mass surveillance, notably in China.[65][66]

In 2019, Bengaluru, India deployed AI-managed traffic signal. This system uses cameras to monitor traffic density and adjust signal timing based on the interval needed to clear traffic.[67]

Military[edit]

Further information: Artificial intelligence arms race, Lethal autonomous weapon, and Unmanned combat aerial vehicle

Various countries are deploying AI military applications.[68] The main applications enhance command and control, communications, sensors, integration and interoperability.[69] Research is targeting intelligence collection and analysis, logistics, cyber operations, information operations, and semiautonomous and autonomous vehicles.[68] AI technologies enable coordination of sensors and effectors, threat detection and identification, marking of enemy positions, target acquisition, coordination and deconfliction of distributed Joint Fires between networked combat vehicles involving manned and unmanned teams.[69] AI was incorporated into military operations in Iraq and Syria.[68]

Worldwide annual military spending on robotics rose from US$5.1 billion in 2010 to US$7.5 billion in 2015.[70][71] Military drones capable of autonomous action are in wide use.[72] Many researchers avoid military applications.[69]

Health[edit]

Healthcare[edit]

Main article: Artificial intelligence in healthcare
X-ray of a hand, with automatic calculation of bone age by a computer software
A patient-side surgical arm of Da Vinci Surgical System

AI in healthcare is often used for classification, to evaluate a CT scan or electrocardiogram or to identify high-risk patients for population health. AI is helping with the high-cost problem of dosing. One study suggested that AI could save $16 billion. In 2016, a study reported that an AI-derived formula derived the proper dose of immunosuppressant drugs to give to transplant patients.[73]

Microsoft's AI project Hanover helps doctors choose cancer treatments from among the more than 800 medicines and vaccines.[74][75] Its goal is to memorize all the relevant papers to predict which (combinations of) drugs will be most effective for each patient. Myeloid leukemia is one target. Another study reported on an AI that was as good as doctors in identifying skin cancers.[76] Another project monitors multiple high-risk patients by asking each patient questions based on data acquired from doctor/patient interactions.[77] In one study done with transfer learning, an AI diagnosed eye conditions similarly to an ophthalmologist within 30 seconds and recommended treatment referrals with more than 95% accuracy.[78]

Another study demonstrated surgery with an autonomous robot. The team supervised the robot while it performed soft-tissue surgery, stitching together a pig's bowel judged better than a surgeon.[79]

Artificial neural networks are used as clinical decision support systems for medical diagnosis,[80] such as in concept processing technology in EMR software.

Other health care tasks thought suitable for an AI that are in development include:

  • Heart sound analysis[81]
  • Companion robots for elder care[82]
  • Medical record analysis
  • Treatment plan design
  • Medication management
  • Assisting blind people[83]
  • Consultations
  • Drug creation[84]
  • Clinical training[85]
  • Outcome prediction for surgical procedures
  • HIV prognosis

Workplace health and safety[edit]

Main article: Workplace impact of artificial intelligence § Health and safety applications

AI-enabled chatbots decrease the need for humans to perform basic call center tasks.[86]

Machine learning in sentiment analysis can spot fatigue in order to prevent overwork.[86] Similarly, decision support systems can prevent industrial disasters and make disaster response more efficient.[87] For manual workers in material handling, predictive analytics may be used to reduce musculoskeletal injury.[88] Data collected from wearable sensors can improve workplace health surveillance, risk assessment, and research.[87][how?]

AI can auto-code workers' compensation claims.[89][90] AI‐enabled virtual reality systems can enhance safety training for hazard recognition.[87] AI can more efficiently detect accident near misses, which are important in reducing accident rates, but are often underreported.[91]

Biochemistry[edit]

AlphaFold 2 can determine the 3D structure of a protein in hours rather than the months required by earlier automated approaches.[92][93]

Law[edit]

Main article: Legal informatics § Artificial intelligence

Legal analysis[edit]

AI is a mainstay of law-related professions. Algorithms and machine learning do some tasks previously done by entry-level lawyers.[94]

The electronic discovery industry uses machine learning to reduce manual searching.[95]

Law enforcement and legal proceedings[edit]

COMPAS is a commercial system used by U.S. courts to assess the likelihood of recidivism.[96]

One concern relates to algorithmic bias, AI programs may become biased after processing data that exhibits bias.[97] ProPublica claims that the average COMPAS-assigned recidivism risk level of black defendants is significantly higher than that of white defendants.[96]

Services[edit]

Human resources[edit]

Main article: Artificial intelligence in hiring

Another application of AI is in human resources. AI can screen resumes and rank candidates based on their qualifications, predict candidate success in given roles, and automate repetitive communication tasks via chatbots.[98]

Job search[edit]

AI has simplified the recruiting /job search process for both recruiters and job seekers. According to Raj Mukherjee from Indeed, 65% of job searchers search again within 91 days after hire. An AI-powered engine streamlines the complexity of job hunting by assessing information on job skills, salaries, and user tendencies, matching job seekers to the most relevant positions. Machine intelligence calculates appropriate wages and highlights resume information for recruiters using NLP, which extracts relevant words and phrases from text. Another application is an AI resume builder that compiles a CV in 5 minutes.[99] Chatbots assist website visitors and refine workflows.

Online and telephone customer service[edit]

An automated online assistant providing customer service on a web page.

AI underlies avatars (automated online assistants) on web pages.[100] It can reduce operation and training costs.[100] Pypestream automated customer service for its mobile application to streamline communication with customers.[101]

A Google app analyzes language and converts speech into text. The platform can identify angry customers through their language and respond appropriately.[102] Amazon uses a chatbot for customer service that can perform tasks like checking the status of an order, cancelling orders, offering refunds and connecting the customer with a human representative.[103]

Hospitality[edit]

In the hospitality industry, AI is used to reduce repetitive tasks, analyze trends, interact with guests, and predict customer needs.[104] AI hotel services come in the form of a chatbot,[105] application, virtual voice assistant and service robots.

Media[edit]

Image restoration

AI applications analyze media content such as movies, TV programs, advertisement videos or user-generated content. The solutions often involve computer vision.

Typical scenarios include the analysis of images using object recognition or face recognition techniques, or the analysis of video for scene recognizing scenes, objects or faces. AI-based media analysis can facilitate media search, the creation of descriptive keywords for content, content policy monitoring (such as verifying the suitability of content for a particular TV viewing time), speech to text for archival or other purposes, and the detection of logos, products or celebrity faces for ad placement.

Deepfakes[edit]

Deepfakes can be used for comedic purposes, but are better known for fake news and hoaxes.

In January 2016,[106] in Europe, the Horizon 2020 program financed the InVID Project[107][108] to help journalists and researchers detect fake documents, made available as browser plugins.[109][110]

In June 2016, the visual computing group of the Technical University of Munich and from Stanford University developed Face2Face,[111] a program that animates photographs of faces, mimicking the facial expressions of another person. The technology has been demonstrated animating the faces of people including Barack Obama and Vladimir Putin. Other methods have been demonstrated based on deep neural networks, from which the name deepfake was taken.

In September 2018, U.S. Senator Mark Warner proposed to penalize social media companies that allow sharing of deepfake documents on their platforms.[112]

In 2018, Vincent Nozick found a way to detect faked content by analyzing eyelid movements.[citation needed] DARPA gave 68 million dollars to work on deepfake detection.[113]

Audio deepfakes,[114][115] and AI software capable of detecting deepfakes and cloning human voices have been developed.[116][117]

Music[edit]

Main article: Music and artificial intelligence

AI has been used to compose music of various genres.

David Cope created an AI called Emily Howell that managed to become well known in the field of algorithmic computer music.[118] The algorithm behind Emily Howell is registered as a US patent.[119]

In 2012, AI Iamus created the first complete classical album.[120]

AIVA (Artificial Intelligence Virtual Artist), composes symphonic music, mainly classical music for film scores.[121] It achieved a world first by becoming the first virtual composer to be recognized by a musical professional association.[122]

Melomics creates computer-generated music for stress and pain relief.[123]

At Sony CSL Research Laboratory, the Flow Machines software creates pop songs by learning music styles from a huge database of songs. It can compose in multiple styles.

The Watson Beat uses reinforcement learning and deep belief networks to compose music on a simple seed input melody and a select style. The software was open sourced[124] and musicians such as Taryn Southern[125] collaborated with the project to create music.

South Korean singer Hayeon's debut song, "Eyes on You" was composed using AI which was supervised by real composers, including NUVO.[126]

Writing and reporting[edit]

Narrative Science sells computer-generated news and reports. It summarizes sporting events based on statistical data from the game. It also creates financial reports and real estate analyses.[127] Automated Insights generates personalized recaps and previews for Yahoo Sports Fantasy Football.[128]

Yseop, uses AI to turn structured data into natural language comments and recommendations. Yseop writes financial reports, executive summaries, personalized sales or marketing documents and more in multiple languages, including English, Spanish, French, and German.[129]

TALESPIN made up stories similar to the fables of Aesop. The program started with a set of characters who wanted to achieve certain goals. The story narrated their attempts to satisfy these goals.[citation needed] Mark Riedl and Vadim Bulitko asserted that the essence of storytelling was experience management, or "how to balance the need for a coherent story progression with user agency, which is often at odds."[130]

While AI storytelling focuses on story generation (character and plot), story communication also received attention. In 2002, researchers developed an architectural framework for narrative prose generation. They faithfully reproduced text variety and complexity on stories such as Little Red Riding Hood.[131] In 2016, a Japanese AI co-wrote a short story and almost won a literary prize.[132]

South Korean company Hanteo Global uses a journalism bot to write articles.[133]

Video games[edit]

Main article: Artificial intelligence in video games

In video games, AI is routinely used to generate behavior in non-player characters (NPCs). In addition, AI is used for pathfinding. Some researchers consider NPC AI in games to be a "solved problem" for most production tasks. Games with less typical AI include the AI director of Left 4 Dead (2008) and the neuroevolutionary training of platoons in Supreme Commander 2 (2010).[134][135] AI is also used in Alien Isolation (2014) as a way to control the actions the Alien will perform next.[136]

Kinect, which provides a 3D body–motion interface for the Xbox 360 and the Xbox One, uses algorithms that emerged from AI research.[137][which?]

Art[edit]

Further information: Artificial intelligence art

AI has been used to produce visual art. Initiatives such as Google Magenta, conducted by the Google Brain team, use AI to create art.[138]

The exhibition "Thinking Machines: Art and Design in the Computer Age, 1959–1989" at MoMA[139] provided an overview of AI applications for art, architecture, and design. Exhibitions showcasing the usage of AI to produce art include the 2016 Google-sponsored benefit and auction at the Gray Area Foundation in San Francisco, where artists experimented with the DeepDream algorithm[140] and the 2017 exhibition "Unhuman: Art in the Age of AI", which took place in Los Angeles and Frankfurt.[141][142] In spring 2018, the Association for Computing Machinery dedicated a magazine issue to the subject of computers and art.[143] In June 2018, "Duet for Human and Machine",[144] an art piece permitting viewers to interact with an artificial intelligence, premiered at the Beall Center for Art + Technology.[145] The Austrian Ars Electronica and Museum of Applied Arts, Vienna opened exhibitions on AI in 2019.[146][147] Ars Electronica's 2019 festival "Out of the box" explored art's role in a sustainable societal transformation.[148]

Utilities[edit]

Power electronics converters are used in renewable energy, energy storage, electric vehicles and high-voltage direct current transmission. These converters are failure-prone, which can interrupt service and require costly maintenance or catastrophic consequences in mission critical applications.[citation needed] AI can guide the design process for reliable power electronics converters, by calculating exact design parameters that ensure the required lifetime.[149]

Many telecommunications companies make use of heuristic search to manage their workforces. For example, BT Group deployed heuristic search[150] in an application that schedules 20,000 engineers.

Manufacturing[edit]

Main articles: Artificial intelligence in industry and Artificial intelligence in heavy industry

Sensors[edit]

Artificial intelligence has been combined with digital spectrometry[disambiguation needed] by IdeaCuria Inc.,[151][152] enable applications such as at-home water quality monitoring.

Toys and games[edit]

In the 1990s early AIs controlled Tamagotchis and Giga Pets, the Internet, and the first widely released robot, Furby. Aibo was a domestic robot in the form of a robotic dog with intelligent features and autonomy.

Mattel created an assortment of AI-enabled toys that "understand" conversations, give intelligent responses, and learn.[153]

Transport[edit]

Automotive[edit]

Main article: Self-driving car

AI in transport is expected to provide safe, efficient, and reliable transportation while minimizing the impact on the environment and communities. The major development challenge is the complexity of transportation systems that involves independent components and parties, with potentially conflicting objectives.[154]

AI-based fuzzy logic controllers operate gearboxes. For example, the 2006 Audi TT, VW Touareg[citation needed] and VW Caravell feature the DSP transmission. A number of Škoda variants (Škoda Fabia) include a fuzzy logic-based controller. Cars have AI-based driver-assist features such as self-parking and adaptive cruise control.

AI has been used to optimize traffic management, which reduces wait times, energy use, and emissions by as much as 25 percent.[155]

Transportation's complexity means that in most cases training an AI in a real-world driving environment is impractical. Simulator-based testing can reduce the risks of on-road training.[156]

AI underpins self-driving vehicles. Companies involved with AI include Tesla, WayMo, and General Motors. AI-based systems control functions such as braking, lane changing, collision prevention, navigation and mapping.[157]

Autonomous trucks are in the testing phase. The UK government passed legislation to begin testing of autonomous truck platoons in 2018.[158] A group of autonomous trucks follow closely behind each other. German corporation Daimler is testing its Freightliner Inspiration.[159]

Autonomous vehicles require accurate maps to be able to navigate between destinations.[160] Some autonomous vehicles do not allow human drivers (they have no steering wheels or pedals).[161]

Military[edit]

The Royal Australian Air Force (RAAF) Air Operations Division (AOD) uses AI for expert systems. AIs operate as surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries.[162]

Aircraft simulators use AI for training aviators. Flight conditions can be simulated that allow pilots to make mistakes without risking themselves or expensive aircraft. Air combat can also be simulated.

AI can also be used to operate planes analogously to their control of ground vehicles. Autonomous drones can fly independently or in swarms.[163]

AOD uses the Interactive Fault Diagnosis and Isolation System, or IFDIS, which is a rule-based expert system using information from TF-30 documents and expert advice from mechanics that work on the TF-30. This system was designed to be used for the development of the TF-30 for the F-111C. The system replaced specialized workers. The system allowed regular workers to communicate with the system and avoid mistakes, miscalculations, or having to speak to one of the specialized workers.

Speech recognition allows traffic controllers to give verbal directions to drones.

Artificial intelligence supported design of aircraft,[164] or AIDA, is used to help designers in the process of creating conceptual designs of aircraft. This program allows the designers to focus more on the design itself and less on the design process. The software also allows the user to focus less on the software tools. The AIDA uses rule based systems to compute its data. This is a diagram of the arrangement of the AIDA modules. Although simple, the program is proving effective.

NASA[edit]

In 2003 a Dryden Flight Research Center project created software that could enable a damaged aircraft to continue flight until a safe landing can be achieved.[165] The software compensated for damaged components by relying on the remaining undamaged components.[166]

The 2016 Intelligent Autopilot System combined apprenticeship learning and behavioural cloning whereby the autopilot observed low-level actions required to maneuver the airplane and high-level strategy used to apply those actions.[167]

Maritime[edit]

Neural networks are used by situational awareness systems in ships and boats.[168]

Computer science[edit]

Programming assistance[edit]

Main articles: Automatic programming and Programming environment

GitHub Copilot is an artificial intelligence model developed by GitHub and OpenAI that is able to autocomplete code in multiple programming languages.[169]

Neural network design[edit]

AI can be used to create other AIs. For example, around November 2017, Google's AutoML project to evolve new neural net topologies created NASNet, a system optimized for ImageNet and POCO F1. NASNet's performance exceeded all previously published performance on ImageNet.[170]

Historical contributions[edit]

AI researchers have created many tools to solve the most difficult problems in computer science. Many of their inventions have been adopted by mainstream computer science and are no longer considered AI. All of the following were originally developed in AI laboratories:[171]

List of applications[edit]

Other fields in which AI methods are implemented[edit]

See also[edit]

Footnotes[edit]

  1. ^ Brynjolfsson, Erik; Mitchell, Tom (22 December 2017). "What can machine learning do? Workforce implications". Science. pp. 1530–1534. Bibcode:2017Sci...358.1530B. doi:10.1126/science.aap8062. Retrieved 7 May 2018.
  2. ^ Francesco Ricci and Lior Rokach and Bracha Shapira, Introduction to Recommender Systems Handbook, Recommender Systems Handbook, Springer, 2011, pp. 1-35
  3. ^ Grossman, Lev (27 May 2010). "How Computers Know What We Want — Before We Do". Time. Archived from the original on 30 May 2010. Retrieved 1 June 2015.
  4. ^ Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Bosagh Zadeh WTF:The who-to-follow system at Twitter, Proceedings of the 22nd international conference on World Wide Web
  5. ^ Baran, Remigiusz; Dziech, Andrzej; Zeja, Andrzej (1 June 2018). "A capable multimedia content discovery platform based on visual content analysis and intelligent data enrichment". Multimedia Tools and Applications. 77 (11): 14077–14091. doi:10.1007/s11042-017-5014-1. ISSN 1573-7721. S2CID 36511631.
  6. ^ Matz, S. C.; Kosinski, M.; Nave, G.; Stillwell, D. J. (28 November 2017). "Psychological targeting as an effective approach to digital mass persuasion". Proceedings of the National Academy of Sciences of the United States of America. 114 (48): 12714–12719. doi:10.1073/pnas.1710966114. JSTOR 26485255. PMC 5715760. PMID 29133409.
  7. ^ Busby, Mattha (30 April 2018). "Revealed: how bookies use AI to keep gamblers hooked". The Guardian.
  8. ^ Celli, Fabio; Massani, Pietro Zani; Lepri, Bruno (2017). "Profilio". Proceedings of the 25th ACM international conference on Multimedia. pp. 546–550. doi:10.1145/3123266.3129311. ISBN 978-1-4503-4906-2. S2CID 767688.
  9. ^ "How artificial intelligence may be making you buy things". BBC News. 9 November 2020. Retrieved 9 November 2020.
  10. ^ Rowinski, Dan (15 January 2013). "Virtual Personal Assistants & The Future Of Your Smartphone [Infographic]". ReadWrite. Archived from the original on 22 December 2015.
  11. ^ Clark, Jack (8 December 2015b). "Why 2015 Was a Breakthrough Year in Artificial Intelligence". Bloomberg L.P. Archived from the original on 23 November 2016. Retrieved 23 November 2016.
  12. ^ Heath, Nick (11 December 2020). "What is AI? Everything you need to know about Artificial Intelligence". ZDNet. Retrieved 1 March 2021.
  13. ^ Clark 2015b.
  14. ^ Markoff, John (16 February 2011). "Computer Wins on 'Jeopardy!': Trivial, It's Not". The New York Times. Archived from the original on 22 October 2014. Retrieved 25 October 2014.
  15. ^ "AlphaGo – Google DeepMind". Archived from the original on 10 March 2016.
  16. ^ "Artificial intelligence: Google's AlphaGo beats Go master Lee Se-dol". BBC News. 12 March 2016. Archived from the original on 26 August 2016. Retrieved 1 October 2016.
  17. ^ Metz, Cade (27 May 2017). "After Win in China, AlphaGo's Designers Explore New AI". Wired. Archived from the original on 2 June 2017.
  18. ^ "World's Go Player Ratings". May 2017. Archived from the original on 1 April 2017.
  19. ^ "柯洁迎19岁生日 雄踞人类世界排名第一已两年" (in Chinese). May 2017. Archived from the original on 11 August 2017.
  20. ^ "MuZero: Mastering Go, chess, shogi and Atari without rules". Deepmind. Retrieved 1 March 2021.
  21. ^ Steven Borowiec; Tracey Lien (12 March 2016). "AlphaGo beats human Go champ in milestone for artificial intelligence". Los Angeles Times. Retrieved 13 March 2016.
  22. ^ Solly, Meilan. "This Poker-Playing A.I. Knows When to Hold 'Em and When to Fold 'Em". Smithsonian. Pluribus has bested poker pros in a series of six-player no-limit Texas Hold'em games, reaching a milestone in artificial intelligence research. It is the first bot to beat humans in a complex multiplayer competition.
  23. ^ Bowling, Michael; Burch, Neil; Johanson, Michael; Tammelin, Oskari (9 January 2015). "Heads-up limit hold'em poker is solved". Science. 347 (6218): 145–149. Bibcode:2015Sci...347..145B. doi:10.1126/science.1259433. ISSN 0036-8075. PMID 25574016. S2CID 3796371.
  24. ^ Ontanon, Santiago; Synnaeve, Gabriel; Uriarte, Alberto; Richoux, Florian; Churchill, David; Preuss, Mike (December 2013). "A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft". IEEE Transactions on Computational Intelligence and AI in Games. 5 (4): 293–311. CiteSeerX 10.1.1.406.2524. doi:10.1109/TCIAIG.2013.2286295. S2CID 5014732.
  25. ^ "Facebook Quietly Enters StarCraft War for AI Bots, and Loses". WIRED. 2017. Retrieved 7 May 2018.
  26. ^ Silver, David; Hubert, Thomas; Schrittwieser, Julian; Antonoglou, Ioannis; Lai, Matthew; Guez, Arthur; Lanctot, Marc; Sifre, Laurent; Kumaran, Dharshan; Graepel, Thore; Lillicrap, Timothy; Simonyan, Karen; Hassabis, Demis (7 December 2018). "A general reinforcement learning algorithm that masters chess, shogi, and go through self-play". Science. 362 (6419): 1140–1144. Bibcode:2018Sci...362.1140S. doi:10.1126/science.aar6404. PMID 30523106.
  27. ^ Sample, Ian (18 October 2017). "'It's able to create knowledge itself': Google unveils AI that learns on its own". The Guardian. Retrieved 7 May 2018.
  28. ^ "The AI revolution in science". Science | AAAS. 5 July 2017. Retrieved 7 May 2018.
  29. ^ "The superhero of artificial intelligence: can this genius keep it in check?". The Guardian. 16 February 2016. Archived from the original on 23 April 2018. Retrieved 26 April 2018.
  30. ^ Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis (26 February 2015). "Human-level control through deep reinforcement learning". Nature. 518 (7540): 529–533. Bibcode:2015Natur.518..529M. doi:10.1038/nature14236. PMID 25719670. S2CID 205242740.
  31. ^ Sample, Ian (14 March 2017). "Google's DeepMind makes AI program that can learn like a human". The Guardian. Archived from the original on 26 April 2018. Retrieved 26 April 2018.
  32. ^ Schrittwieser, Julian; Antonoglou, Ioannis; Hubert, Thomas; Simonyan, Karen; Sifre, Laurent; Schmitt, Simon; Guez, Arthur; Lockhart, Edward; Hassabis, Demis; Graepel, Thore; Lillicrap, Timothy (23 December 2020). "Mastering Atari, Go, chess and shogi by planning with a learned model". Nature. 588 (7839): 604–609. arXiv:1911.08265. Bibcode:2020Natur.588..604S. doi:10.1038/s41586-020-03051-4. ISSN 1476-4687. PMID 33361790. S2CID 208158225.
  33. ^ K, Bharath (2 April 2021). "AI In Chess: The Evolution of Artificial Intelligence In Chess Engines". Medium. Retrieved 6 January 2022.
  34. ^ National Science and Technology Council. Preparing for the future of artificial intelligence. OCLC 965620122.
  35. ^ Gambhire, Akshaya; Shaikh Mohammad, Bilal N. (8 April 2020). Use of Artificial Intelligence in Agriculture. Proceedings of the 3rd International Conference on Advances in Science & Technology (ICAST) 2020. SSRN 3571733.
  36. ^ "The Future of AI in Agriculture". Intel. Retrieved 5 March 2019.
  37. ^ Sennaar, Kumba. "AI in Agriculture – Present Applications and Impact | Emerj - Artificial Intelligence Research and Insight". Emerj. Retrieved 5 March 2019.
  38. ^ G. Jones, Colleen (26 June 2019). "Artificial Intelligence in Agriculture: Farming for the 21st Century". Retrieved 8 February 2021.
  39. ^ Moreno, Millán M.; Guzmán, Sevilla E.; Demyda, S. E. (1 November 2011). "Population, Poverty, Production, Food Security, Food Sovereignty, Biotechnology and Sustainable Development: Challenges for the XXI Century". Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Veterinary Medicine. 1 (68). doi:10.15835/buasvmcn-vm:1:68:6771 (inactive 28 February 2022).{{cite journal}}: CS1 maint: DOI inactive as of February 2022 (link)
  40. ^ Liundi, Nicholas; Darma, Aditya Wirya; Gunarso, Rivaldi; Warnars, Harco Leslie Hendric Spits (2019). "Improving Rice Productivity in Indonesia with Artificial Intelligence". 2019 7th International Conference on Cyber and IT Service Management (CITSM). pp. 1–5. doi:10.1109/CITSM47753.2019.8965385. ISBN 978-1-7281-2909-9. S2CID 210930401.
  41. ^ Talaviya, Tanha; Shah, Dhara; Patel, Nivedita; Yagnik, Hiteshri; Shah, Manan (2020). "Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides". Artificial Intelligence in Agriculture. 4: 58–73. doi:10.1016/j.aiia.2020.04.002. S2CID 219064189.
  42. ^ Implications of artificial intelligence for cybersecurity : proceedings of a workshop. Anne Johnson, Emily Grumbling, Engineering, and Medicine. Computer Science and Telecommunications Board National Academies of Sciences, Engineering, and Medicine. Intelligence Community Studies Board National Academies of Sciences. Washington, DC. 2019. ISBN 978-0-309-49451-9. OCLC 1134854973.{{cite book}}: CS1 maint: others (link)
  43. ^ Parisi, Alessandro (2019). Hands-on artificial intelligence for cybersecurity : implement smart AI systems for preventing cyber attacks and detecting threats and network anomalies. Birmingham, UK. ISBN 978-1-78980-517-8. OCLC 1111967955.
  44. ^ "The Role Of Artificial Intelligence In The Classroom". eLearning Industry. 14 April 2018. Retrieved 14 January 2019.
  45. ^ Anabel, Quan-Haase (2020). TECHNOLOGY AND SOCIETY : social networks, power, and inequality. Oxford University Press. ISBN 978-0-19-903225-9. OCLC 1142724334.
  46. ^ Richtel, Matt (21 November 2010). "Growing Up Digital, Wired for Distraction". The New York Times.
  47. ^ Chen, Hsing-Chung; Prasetyo, Eko; Tseng, Shian-Shyong; Putra, Karisma Trinanda; Prayitno; Kusumawardani, Sri Suning; Weng, Chien-Erh (January 2022). "Week-Wise Student Performance Early Prediction in Virtual Learning Environment Using a Deep Explainable Artificial Intelligence". Applied Sciences. 12 (4): 1885. doi:10.3390/app12041885.
  48. ^ Christy, Charles A. (17 January 1990). "Impact of Artificial Intelligence on Banking". Los Angeles Times. Retrieved 10 September 2019.
  49. ^ O'Neill, Eleanor (31 July 2016). "Accounting, automation and AI". icas.com. Archived from the original on 18 November 2016. Retrieved 18 November 2016.
  50. ^ "CTO Corner: Artificial Intelligence Use in Financial Services – Financial Services Roundtable". Financial Services Roundtable. 2 April 2015. Archived from the original on 18 November 2016. Retrieved 18 November 2016.
  51. ^ "Artificial Intelligence Solutions, AI Solutions". sas.com.
  52. ^ Chapman, Lizette (7 January 2019). "Palantir once mocked the idea of salespeople. Now it's hiring them". Los Angeles Times. Retrieved 28 February 2019.
  53. ^ Marwala, Tshilidzi; Hurwitz, Evan (2017). Artificial Intelligence and Economic Theory: Skynet in the Market. London: Springer. ISBN 978-3-319-66104-9.
  54. ^ Marwala, Tshilidzi; Hurwitz, Evan (2017), "Efficient Market Hypothesis", Artificial Intelligence and Economic Theory: Skynet in the Market, Cham: Springer International Publishing, pp. 101–110, doi:10.1007/978-3-319-66104-9_9, ISBN 978-3-319-66103-2, retrieved 11 November 2020
  55. ^ "Algorithmic Trading". Investopedia. 18 May 2005.
  56. ^ "Beyond Robo-Advisers: How AI Could Rewire Wealth Management". 5 January 2017.
  57. ^ "Machine Learning Is the Future of Underwriting, But Startups Won't be Driving It". 3 April 2017.
  58. ^ "ZestFinance Introduces Machine Learning Platform to Underwrite Millennials and Other Consumers with Limited Credit History". 14 February 2017.
  59. ^ Chang, Hsihui; Kao, Yi-Ching; Mashruwala, Raj; Sorensen, Susan M. (10 April 2017). "Technical Inefficiency, Allocative Inefficiency, and Audit Pricing". Journal of Accounting, Auditing & Finance. 33 (4): 580–600. doi:10.1177/0148558X17696760. S2CID 157787279.
  60. ^ Durkin, J. (2002). "History and applications". Expert Systems. Vol. 1. pp. 1–22. doi:10.1016/B978-012443880-4/50045-4. ISBN 978-0-12-443880-4.
  61. ^ Chen, K.C.; Liang, Ting‐peng (1 May 1989). "PROTRADER: An Expert System for Program Trading". Managerial Finance. 15 (5): 1–6. doi:10.1108/eb013623.
  62. ^ Nielson, Norma; Brown, Carol E.; Phillips, Mary Ellen (July 1990). "Expert Systems for Personal Financial Planning". Journal of Financial Planning: 137–143. doi:10.11575/PRISM/33995. hdl:1880/48295.
  63. ^ Senator, Ted E.; Goldberg, Henry G.; Wooton, Jerry; Cottini, Matthew A.; Khan, A.F. Umar; Kilinger, Christina D.; Llamas, Winston M.; Marrone, MichaeI P.; Wong, Raphael W.H. (1995). "The FinCEN Artificial Intelligence System: Identifying Potential Money Laundering from Reports of Large Cash Transactions" (PDF). IAAI-95 Proceedings.
  64. ^ Sutton, Steve G.; Holt, Matthew; Arnold, Vicky (September 2016). "'The reports of my death are greatly exaggerated'—Artificial intelligence research in accounting". International Journal of Accounting Information Systems. 22: 60–73. doi:10.1016/j.accinf.2016.07.005.
  65. ^ Buckley, Chris; Mozur, Paul (22 May 2019). "How China Uses High-Tech Surveillance to Subdue Minorities". The New York Times.
  66. ^ "Security lapse exposed a Chinese smart city surveillance system".
  67. ^ "AI traffic signals to be installed in Bengaluru soon". NextBigWhat. 24 September 2019. Retrieved 1 October 2019.
  68. ^ a b c Congressional Research Service (2019). Artificial Intelligence and National Security (PDF). Washington, DC: Congressional Research Service.PD-notice
  69. ^ a b c Slyusar, Vadym (2019). "Artificial intelligence as the basis of future control networks". doi:10.13140/RG.2.2.30247.50087. {{cite journal}}: Cite journal requires |journal= (help)
  70. ^ "Getting to grips with military robotics". The Economist. 25 January 2018. Retrieved 7 February 2018.
  71. ^ "Autonomous Systems: Infographic". siemens.com. Retrieved 7 February 2018.
  72. ^ Allen, Gregory (6 February 2019). "Understanding China's AI Strategy". Center for a New American Security. Archived from the original on 17 March 2019. Retrieved 17 March 2019.
  73. ^ "10 Promising AI Applications in Health Care". Harvard Business Review. 10 May 2018. Archived from the original on 15 December 2018. Retrieved 28 August 2018.
  74. ^ HealthITAnalytics (29 October 2019). "Microsoft Using AI to Accelerate Cancer Precision Medicine". HealthITAnalytics. Retrieved 29 November 2020.
  75. ^ Dina Bass (20 September 2016). "Microsoft Develops AI to Help Cancer Doctors Find the Right Treatments". Bloomberg L.P. Archived from the original on 11 May 2017.
  76. ^ Gallagher, James (26 January 2017). "Artificial intelligence 'as good as cancer doctors'". BBC News. Archived from the original on 26 January 2017. Retrieved 26 January 2017.
  77. ^ Langen, Pauline A.; Katz, Jeffrey S.; Dempsey, Gayle, eds. (18 October 1994), Remote monitoring of high-risk patients using artificial intelligence, archived from the original on 28 February 2017, retrieved 27 February 2017
  78. ^ Kermany, Daniel S.; Goldbaum, Michael; Cai, Wenjia; Valentim, Carolina C.S.; Liang, Huiying; Baxter, Sally L.; McKeown, Alex; Yang, Ge; Wu, Xiaokang; Yan, Fangbing; Dong, Justin; Prasadha, Made K.; Pei, Jacqueline; Ting, Magdalene Y.L.; Zhu, Jie; Li, Christina; Hewett, Sierra; Dong, Jason; Ziyar, Ian; Shi, Alexander; Zhang, Runze; Zheng, Lianghong; Hou, Rui; Shi, William; Fu, Xin; Duan, Yaou; Huu, Viet A.N.; Wen, Cindy; Zhang, Edward D.; Zhang, Charlotte L.; Li, Oulan; Wang, Xiaobo; Singer, Michael A.; Sun, Xiaodong; Xu, Jie; Tafreshi, Ali; Lewis, M. Anthony; Xia, Huimin; Zhang, Kang (February 2018). "Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning". Cell. 172 (5): 1122–1131.e9. doi:10.1016/j.cell.2018.02.010. PMID 29474911. S2CID 3516426.
  79. ^ Senthilingam, Meera (12 May 2016). "Are Autonomous Robots Your next Surgeons?". CNN. Archived from the original on 3 December 2016. Retrieved 4 December 2016.
  80. ^ Pumplun L, Fecho M, Wahl N, Peters F, Buxmann P (2021). "Adoption of Machine Learning Systems for Medical Diagnostics in Clinics: Qualitative Interview Study". Journal of Medical Internet Research. 23 (10): e29301. doi:10.2196/29301. PMC 8556641. PMID 34652275. S2CID 238990562.
  81. ^ Reed, Todd R.; Reed, Nancy E.; Fritzson, Peter (2004). "Heart sound analysis for symptom detection and computer-aided diagnosis". Simulation Modelling Practice and Theory. 12 (2): 129–146. doi:10.1016/j.simpat.2003.11.005.
  82. ^ Yorita, Akihiro; Kubota, Naoyuki (2011). "Cognitive Development in Partner Robots for Information Support to Elderly People". IEEE Transactions on Autonomous Mental Development. 3: 64–73. CiteSeerX 10.1.1.607.342. doi:10.1109/TAMD.2011.2105868. S2CID 13797196.
  83. ^ Ray, Dr Amit (14 May 2018). "Artificial intelligence for Assisting Navigation of Blind People". Inner Light Publishers.
  84. ^ "Artificial Intelligence Will Redesign Healthcare – The Medical Futurist". The Medical Futurist. 4 August 2016. Retrieved 18 November 2016.
  85. ^ Luxton, David D. (2014). "Artificial intelligence in psychological practice: Current and future applications and implications". Professional Psychology: Research and Practice. 45 (5): 332–339. doi:10.1037/a0034559.
  86. ^ a b Moore, Phoebe V. (7 May 2019). "OSH and the Future of Work: benefits and risks of artificial intelligence tools in workplaces". EU-OSHA. pp. 3–7. Retrieved 30 July 2020.
  87. ^ a b c Howard, John (November 2019). "Artificial intelligence: Implications for the future of work". American Journal of Industrial Medicine. 62 (11): 917–926. doi:10.1002/ajim.23037. PMID 31436850. S2CID 201275028.
  88. ^ Gianatti, Toni-Louise (14 May 2020). "How AI-Driven Algorithms Improve an Individual's Ergonomic Safety". Occupational Health & Safety. Retrieved 30 July 2020.
  89. ^ Meyers, Alysha R. (1 May 2019). "AI and Workers' Comp". NIOSH Science Blog. Retrieved 3 August 2020.
  90. ^ Webb, Sydney; Siordia, Carlos; Bertke, Stephen; Bartlett, Diana; Reitz, Dan (26 February 2020). "Artificial Intelligence Crowdsourcing Competition for Injury Surveillance". NIOSH Science Blog. Retrieved 3 August 2020.
  91. ^ Ferguson, Murray (19 April 2016). "Artificial Intelligence: What's To Come for EHS… And When?". EHS Today. Retrieved 30 July 2020.
  92. ^ "DeepMind is answering one of biology's biggest challenges". The Economist. 30 November 2020. ISSN 0013-0613. Retrieved 30 November 2020.
  93. ^ Jeremy Kahn, Lessons from DeepMind's breakthrough in protein-folding A.I., Fortune, 1 December 2020
  94. ^ Ashley, Kevin D. (2017). Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age. Cambridge: Cambridge University Press. doi:10.1017/9781316761380. ISBN 978-1-316-76138-0.[page needed]
  95. ^ Croft, Jane (2 May 2019). "AI learns to read Korean, so you don't have to". Financial Times. Retrieved 19 December 2019.
  96. ^ a b Jeff Larson, Julia Angwin (23 May 2016). "How We Analyzed the COMPAS Recidivism Algorithm". ProPublica. Archived from the original on 29 April 2019. Retrieved 19 June 2020.
  97. ^ "Commentary: Bad news. Artificial intelligence is biased". CNA. 12 January 2019. Archived from the original on 12 January 2019. Retrieved 19 June 2020.
  98. ^ Nawaz, Nishad; Gomes, Anjali Mary (2020). "Artificial Intelligence Chatbots are New Recruiters". International Journal of Advanced Computer Science and Applications. 10 (9). doi:10.2139/ssrn.3521915. S2CID 233762238. SSRN 3521915.
  99. ^ Kafre, Sumit (15 April 2018). "Automatic Curriculum Vitae using Machine learning and Artificial Intelligence". Asian Journal for Convergence in Technology (AJCT). 4.
  100. ^ a b Kongthon, Alisa; Sangkeettrakarn, Chatchawal; Kongyoung, Sarawoot; Haruechaiyasak, Choochart (2009). "Implementing an online help desk system based on conversational agent". Proceedings of the International Conference on Management of Emergent Digital Eco Systems - MEDES '09. p. 450. doi:10.1145/1643823.1643908. ISBN 9781605588292. S2CID 1046438.
  101. ^ Sara Ashley O'Brien (12 January 2016). "Is this app the call center of the future?". CNN. Retrieved 26 September 2016.
  102. ^ jackclarkSF, Jack Clark (20 July 2016). "New Google AI Brings Automation to Customer Service". Bloomberg L.P. Retrieved 18 November 2016.
  103. ^ "Amazon.com tests customer service chatbots". Amazon Science. 25 February 2020. Retrieved 23 April 2021.
  104. ^ "Advanced analytics in hospitality". McKinsey & Company. 2017. Retrieved 14 January 2020.
  105. ^ Zlatanov, Sonja; Popesku, Jovan (2019). "Current Applications of Artificial Intelligence in Tourism and Hospitality". Proceedings of the International Scientific Conference - Sinteza 2019. pp. 84–90. doi:10.15308/Sinteza-2019-84-90. ISBN 978-86-7912-703-7. S2CID 182061194.
  106. ^ "InVID kick-off meeting". InVID project. 22 January 2016. Retrieved 23 December 2021. We are kicking-off the new H2020 InVID research project.
  107. ^ (In Video Veritas)
  108. ^ "Consortium of the InVID project". InVID project. Retrieved 23 December 2021. The InVID vision: The InVID innovation action develops a knowledge verification platform to detect emerging stories and assess the reliability of newsworthy video files and content spread via social media.
  109. ^ Teyssou, Denis (2019). "Applying Design Thinking Methodology: The InVID Verification Plugin". Video Verification in the Fake News Era. pp. 263–279. doi:10.1007/978-3-030-26752-0_9. ISBN 978-3-030-26751-3. S2CID 202717914.
  110. ^ "Fake news debunker by InVID & WeVerify". Retrieved 23 December 2021.
  111. ^ "TUM Visual Computing & Artificial Intelligence: Prof. Matthias Nießner". niessnerlab.org.
  112. ^ "Will 'Deepfakes' Disrupt the Midterm Election?". Wired. November 2018.
  113. ^ Afchar, Darius; Nozick, Vincent; Yamagishi, Junichi; Echizen, Isao (2018). "Meso Net: A Compact Facial Video Forgery Detection Network". 2018 IEEE International Workshop on Information Forensics and Security (WIFS). pp. 1–7. arXiv:1809.00888. doi:10.1109/WIFS.2018.8630761. ISBN 978-1-5386-6536-7. S2CID 52157475.
  114. ^ Lyons, Kim (29 January 2020). "FTC says the tech behind audio deepfakes is getting better". The Verge.
  115. ^ "Audio samples from "Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis"". google.github.io.
  116. ^ Strickland, Eliza (11 December 2019). "Facebook AI Launches Its Deepfake Detection Challenge". IEEE Spectrum.
  117. ^ "Contributing Data to Deepfake Detection Research".
  118. ^ Cheng, Jacqui (30 September 2009). "Virtual composer makes beautiful music—and stirs controversy". Ars Technica.
  119. ^ US patent 7696426 
  120. ^ "Computer composer honours Turing's centenary". New Scientist. 4 July 2012. Archived from the original on 2016-04-13. Retrieved 27 December 2021.
  121. ^ Hick, Thierry (11 October 2016). "La musique classique recomposée". Luxemburger Wort.
  122. ^ "Résultats de recherche - La Sacem". repertoire.sacem.fr.
  123. ^ Requena, Gloria; Sánchez, Carlos; Corzo-Higueras, José Luis; Reyes-Alvarado, Sirenia; Rivas-Ruiz, Francisco; Vico, Francisco; Raglio, Alfredo (2014). "Melomics music medicine (M3) to lessen pain perception during pediatric prick test procedure". Pediatric Allergy and Immunology. 25 (7): 721–724. doi:10.1111/pai.12263. PMID 25115240. S2CID 43273958.
  124. ^ "Watson Beat on GitHub". GitHub. 10 October 2018.
  125. ^ "Songs in the Key of AI". Wired. 17 May 2018.
  126. ^ "Hayeon, sister of Girls' Generation's Taeyeon, debuts with song made by AI". koreajoongangdaily.joins.com. Retrieved 23 October 2020.
  127. ^ business intelligence solutions Archived 3 November 2011 at the Wayback Machine. Narrative Science. Retrieved 21 July 2013.
  128. ^ Eule, Alexander. "Big Data and Yahoo's Quest for Mass Personalization". Barron's.
  129. ^ "Artificial Intelligence Software that Writes like a Human Being". Archived from the original on 12 April 2013. Retrieved 11 March 2013.
  130. ^ Riedl, Mark Owen; Bulitko, Vadim (6 December 2012). "Interactive Narrative: An Intelligent Systems Approach". AI Magazine. 34 (1): 67. doi:10.1609/aimag.v34i1.2449.
  131. ^ Callaway, Charles B.; Lester, James C. (August 2002). "Narrative prose generation". Artificial Intelligence. 139 (2): 213–252. doi:10.1016/S0004-3702(02)00230-8.
  132. ^ "A Japanese AI program just wrote a short novel, and it almost won a literary prize". Digital Trends. 23 March 2016. Retrieved 18 November 2016.
  133. ^ "Bot News". Hanteo News. 20 October 2020. Retrieved 20 October 2020.
  134. ^ "Why AI researchers like video games". The Economist. Archived from the original on 5 October 2017.
  135. ^ Yannakakis, Geogios N. (2012). "Game AI revisited". Proceedings of the 9th conference on Computing Frontiers - CF '12. p. 285. doi:10.1145/2212908.2212954. ISBN 978-1-4503-1215-8. S2CID 4335529.
  136. ^ Maass, Laura E. Shummon (1 July 2019). "Artificial Intelligence in Video Games". Medium. Retrieved 23 April 2021.
  137. ^ Fairhead, Harry (26 March 2011) [Update 30 March 2011]. "Kinect's AI breakthrough explained". I Programmer. Archived from the original on 1 February 2016.
  138. ^ Souppouris, Aaron (23 May 2016). "Google's 'Magenta' project will see if AIs can truly make art". Engadget.
  139. ^ "Thinking Machines: Art and Design in the Computer Age, 1959–1989". The Museum of Modern Art. Retrieved 23 July 2019.
  140. ^ Retrieved July 29
  141. ^ "Unhuman: Art in the Age of AI – State Festival". Statefestival.org. Retrieved 13 September 2018.
  142. ^ Chun, Rene (21 September 2017). "It's Getting Hard to Tell If a Painting Was Made by a Computer or a Human". Artsy. Retrieved 23 July 2019.
  143. ^ Retrieved July 29
  144. ^ "Home". Retrieved 13 August 2020.
  145. ^ "Rebase: Activate | Beall Center for Art + Technology". beallcenter.uci.edu. Retrieved 13 August 2020.
  146. ^ "Understanding AI". Ars Electronica Center.
  147. ^ "UNCANNY VALUES | VIENNA BIENNALE FOR CHANGE 2019 - MAK Museum Vienna". mak.at.
  148. ^ "European Platform for Digital Humanism - A conference by the European ARTificial Intelligence Lab". Out of the Box.
  149. ^ Dragicevic, Tomislav; Wheeler, Patrick; Blaabjerg, Frede (August 2019). "Artificial Intelligence Aided Automated Design for Reliability of Power Electronic Systems". IEEE Transactions on Power Electronics. 34 (8): 7161–7171. Bibcode:2019ITPE...34.7161D. doi:10.1109/TPEL.2018.2883947. S2CID 116390072.
  150. ^ Success Stories Archived 4 October 2011 at the Wayback Machine.
  151. ^ "Digital Spectrometry". 8 October 2018.
  152. ^ US 9967696B2, "Digital Spectrometry Patent", published 2018-10-08 
  153. ^ "How artificial intelligence is moving from the lab to your kid's playroom". The Washington Post. Retrieved 18 November 2016.
  154. ^ Artificial Intelligence in Transportation: Information for Application. 29 January 2007. doi:10.17226/23208. ISBN 978-0-309-42929-0.[page needed]
  155. ^ author., National Science and Technology Council (U.S.). Committee on Technology. Subcommittee on Machine Learning and Artificial Intelligence. Preparing for the future of artificial intelligence. OCLC 965620122. {{cite book}}: |last= has generic name (help)
  156. ^ Hallerbach, Sven; Xia, Yiqun; Eberle, Ulrich; Koester, Frank (3 April 2018). "Simulation-Based Identification of Critical Scenarios for Cooperative and Automated Vehicles". SAE International Journal of Connected and Automated Vehicles. 1 (2): 93–106. doi:10.4271/2018-01-1066.
  157. ^ West, Darrell M. (20 September 2016). "Moving forward: Self-driving vehicles in China, Europe, Japan, Korea, and the United States". Brookings.
  158. ^ Burgess, Matt (24 August 2017). "The UK is about to Start Testing Self-Driving Truck Platoons". Wired UK. Archived from the original on 22 September 2017. Retrieved 20 September 2017.
  159. ^ Davies, Alex (5 May 2015). "World's First Self-Driving Semi-Truck Hits the Road". Wired. Archived from the original on 28 October 2017. Retrieved 20 September 2017.
  160. ^ McFarland, Matt (25 February 2015). "Google's artificial intelligence breakthrough may have a huge impact on self-driving cars and much more". The Washington Post.
  161. ^ "Programming safety into self-driving cars". National Science Foundation. 2 February 2015.
  162. ^ "AI bests Air Force combat tactics experts in simulated dogfights". Ars Technica. 29 June 2016.
  163. ^ Jones, Randolph M.; Laird, John E.; Nielsen, Paul E.; Coulter, Karen J.; Kenny, Patrick; Koss, Frank V. (15 March 1999). "Automated Intelligent Pilots for Combat Flight Simulation". AI Magazine. 20 (1): 27. doi:10.1609/aimag.v20i1.1438.
  164. ^ AIDA Homepage. Kbs.twi.tudelft.nl (17 April 1997). Retrieved 21 July 2013.
  165. ^ The Story of Self-Repairing Flight Control Systems. NASA Dryden. (April 2003). Retrieved 25 August 2016.
  166. ^ Adams, Eric (28 March 2017). "AI Wields the Power to Make Flying Safer—and Maybe Even Pleasant". Wired. Retrieved 7 October 2017.
  167. ^ Baomar, Haitham; Bentley, Peter J. (2016). "An Intelligent Autopilot System that learns flight emergency procedures by imitating human pilots". 2016 IEEE Symposium Series on Computational Intelligence (SSCI). pp. 1–9. doi:10.1109/SSCI.2016.7849881. ISBN 978-1-5090-4240-1. S2CID 2021875.
  168. ^ "UB invests in student-founded startup". buffalo.edu. Retrieved 24 December 2020.
  169. ^ Gershgorn, Dave (29 June 2021). "GitHub and OpenAI launch a new AI tool that generates its own code". The Verge. Retrieved 3 September 2021.
  170. ^ "Google AI creates its own 'child' bot". The Independent. 5 December 2017. Retrieved 5 February 2018.
  171. ^ Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey: Prentice Hall, ISBN 0-13-790395-2
  172. ^ "Research at NVIDIA: Transforming Standard Video Into Slow Motion with AI". Archived from the original on 21 December 2021 – via YouTube.
  173. ^ "Artificial intelligence is helping old video games look like new". The Verge. 18 April 2019.
  174. ^ "Review: Topaz Sharpen AI is Amazing". petapixel.com. 4 March 2019.
  175. ^ Griffin, Matthew (26 April 2018). "AI can now restore your corrupted photos to their original condition".
  176. ^ "NVIDIA's AI can fix bad photos by looking at other bad photos". Engadget.
  177. ^ "Using AI to Colorize and Upscale a 109-Year-Old Video of New York City to 4K and 60fps". petapixel.com. 24 February 2020.
  178. ^ "YouTubers are upscaling the past to 4K. Historians want them to stop". Wired UK.
  179. ^ "Facebook's image outage reveals how the company's AI tags your photos". The Verge. 3 July 2019.
  180. ^ "Application of artificial intelligence in oil and gas industry: Exploring its impact". 15 May 2019.
  181. ^ Salvaterra, Neanda (14 October 2019). "Oil and Gas Companies Turn to AI to Cut Costs". The Wall Street Journal.

Further reading[edit]

External links[edit]

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