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Timeline of machine learning

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AlphaFold 2 (2021), A team that used AlphaFold 2 (2020) repeated the placement in the CASP competition in November 2020. The team achieved a level of accuracy much higher than any other group. It scored above 90 for around two-thirds of the proteins in CASP's global distance test (GDT), a test that
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Delving into the text of Alexander Pushkin's novel in verse Eugene Onegin, Markov spent hours sifting through patterns of vowels and consonants. On January 23, 1913, he summarized his findings in an address to the Imperial Academy of Sciences in St. Petersburg. His analysis did not alter the
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Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach. Scientists begin creating programs for computers to analyze large amounts of data and draw conclusions – or "learn" – from the results.
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Canini, Kevin; Chandra, Tushar; Ie, Eugene; McFadden, Jim; Goldman, Ken; Gunter, Mike; Harmsen, Jeremiah; LeFevre, Kristen; Lepikhin, Dmitry; Llinares, Tomas Lloret; Mukherjee, Indraneel; Pereira, Fernando; Redstone, Josh; Shaked, Tal; Singer, Yoram.
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proves that standard multilayer feedforward networks are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
967:. The aim of the competition was to use machine learning to beat Netflix's own recommendation software's accuracy in predicting a user's rating for a film given their ratings for previous films by at least 10%. The prize was won in 2009. 568:
publishes the general method for automatic differentiation (AD) of discrete connected networks of nested differentiable functions. This corresponds to the modern version of backpropagation, but is not yet named as such.
552:, describing some of the limitations of perceptrons and neural networks. The interpretation that the book shows that neural networks are fundamentally limited is seen as a hindrance for research into neural networks. 988:
from Stanford University, who realized that the best machine learning algorithms wouldn't work well if the data didn't reflect the real world. For many, ImageNet was the catalyst for the AI boom of the 21st century.
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measures the degree to which a computational program predicted structure is similar to the lab experiment determined structure, with 100 being a complete match, within the distance cutoff used for calculating GDT.
208:(image based). Machine learning and AI enter the wider public consciousness. The commercial potential of AI based on machine learning causes large increases in valuations of companies linked to AI. 288: 3043: 185:
becomes feasible, which leads to machine learning becoming integral to many widely used software services and applications. Deep learning spurs huge advances in vision and text processing.
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detail their work on Sibyl, a proprietary platform for massively parallel machine learning used internally by Google to make predictions about user behavior and provide recommendations.
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Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; Uszkoreit, Jakob; Jones, Llion; Gomez, Aidan N.; Kaiser, Lukasz; Polosukhin, Illia (2017). "Attention Is All You Need".
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Gerald Dejong introduces Explanation Based Learning, where a computer algorithm analyses data and creates a general rule it can follow and discard unimportant data.
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understanding or appreciation of Pushkin's poem, but the technique he developed—now known as a Markov chain—extended the theory of probability in a new direction.
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Fukushima, Kunihiko (April 1980). "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position".
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program to beat an unhandicapped professional human player using a combination of machine learning and tree search techniques. Later improved as
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paper and algorithm achieves breakthrough results in image recognition in the ImageNet benchmark. This popularizes deep neural networks.
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joins IBM's Poughkeepsie Laboratory and begins working on some of the first machine learning programs, first creating programs that play
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Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. (October 1986). "Learning representations by back-propagating errors".
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revolutionizes the processing of text in machine learnings. It shows how each word can be converted into a sequence of numbers (
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proposes a 'learning machine' that could learn and become artificially intelligent. Turing's specific proposal foreshadows
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The representation of the cumulative rounding error of an algorithm as a Taylor expansion of the local rounding errors
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Rosenblatt, F. (1958). "The perceptron: A probabilistic model for information storage and organization in the brain".
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McCulloch, Warren S.; Pitts, Walter (December 1943). "A logical calculus of the ideas immanent in nervous activity".
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employees and American high school students. The MNIST database has since become a benchmark for evaluating
484:. The invention of the perceptron generated a great deal of excitement and was widely covered in the media. 3322: 3188: 2623: 2121: 1724: 1062:, create a neural network that learns to recognize cats by watching unlabeled images taken from frames of 922: 897: 854: 763: 502: 147: 1481: 1196:
architecture, which allows for faster parallel training of neural networks on sequential data like text.
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Eisenstein, Michael (23 November 2021). "Artificial intelligence powers protein-folding predictions".
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was created, which is the start of basic pattern recognition. The algorithm was used to map routes.
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Ben-Hur, Asa; Horn, David; Siegelmann, Hava; Vapnik, Vladimir (2001). "Support vector clustering".
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Students at Stanford University develop a cart that can navigate and avoid obstacles in a room.
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is published two years after his death, having been amended and edited by a friend of Bayes,
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Le, Quoc V. (2013). "Building high-level features using large scale unsupervised learning".
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Algoritmin kumulatiivinen pyoristysvirhe yksittaisten pyoristysvirheiden taylor-kehitelmana
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first describes techniques he used to analyse a poem. The techniques later become known as
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Please help update this article to reflect recent events or newly available information.
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develop a mathematical model that imitates the functioning of a biological neuron, the
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Hochreiter, Sepp; Schmidhuber, Jürgen (1 November 1997). "Long Short-Term Memory".
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A program that learns to pronounce words the same way a baby does, is developed by
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Solomonoff, R.J. (June 1964). "A formal theory of inductive inference. Part II".
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Proceedings of 3rd International Conference on Document Analysis and Recognition
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Griewank, Andreas (2012). "Who Invented the Reverse Mode of Differentiation?".
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Taigman, Yaniv; Yang, Ming; Ranzato, Marc'Aurelio; Wolf, Lior (24 June 2014).
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2013 IEEE International Conference on Acoustics, Speech and Signal Processing
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Tesauro, Gerald (March 1995). "Temporal difference learning and TD-Gammon".
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and Dean Edmonds build the first neural network machine, able to learn, the
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Turing, A. M. (1 October 1950). "I.—COMPUTING MACHINERY AND INTELLIGENCE".
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creates a 'machine' consisting of 304 match boxes and beads, which uses
58:. Major discoveries, achievements, milestones and other major events in 2415: 2398: 2090: 1886: 1635: 1604: 1159: 1081: 1063: 964: 201: 1529: 2831:"Inside Sibyl, Google's Massively Parallel Machine Learning Platform" 2495:
Collobert, Ronan; Benigo, Samy; Mariethoz, Johnny (30 October 2002).
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and then in 2017 generalized to Chess and more two-player games with
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describes the "méthode des moindres carrés", known in English as the
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AlphaFold 1 (2018) placed first in the overall rankings of the 13th
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both proprietary and open source, notably enabling products such as
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Hofmann, Thomas; Schölkopf, Bernhard; Smola, Alexander J. (2008).
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Critical Assessment of Techniques for Protein Structure Prediction
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Nouvelles méthodes pour la détermination des orbites des comètes
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Siegelmann, Hava (1995). "Computation Beyond the Turing Limit".
1211: 3087: 2631: 2741:"The data that transformed AI research—and possibly the world" 2581:"ImageNet: the data that spawned the current AI boom — Quartz" 1873:(1976). "Taylor expansion of the accumulated rounding error". 1796:"Menace: the Machine Educable Noughts And Crosses Engine Read" 1504:"An Essay Towards Solving a Problem in the Doctrine of Chance" 1025: 984:
is created. ImageNet is a large visual database envisioned by
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Mason, Harding; Stewart, D; Gill, Brendan (6 December 1958).
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An Essay Towards Solving a Problem in the Doctrine of Chances
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Commercialization of Machine Learning on Personal Computers
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which is considered to be the first neural model invented.
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leads to revolutionary models, creating a proliferation of
2857:"Google achieves AI 'breakthrough' by beating Go champion" 1953:(2015). "Deep learning in neural networks: An overview". 1926:
Principles and Techniques of Algorithmic Differentiation
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AI: The Tumultuous Search for Artificial Intelligence
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Conference on Computer Vision and Pattern Recognition
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Cortes, Corinna; Vapnik, Vladimir (September 1995).
3310: 3282: 3222: 3179: 3121: 2473:LeCun, Yann; Cortes, Corinna; Burges, Christopher. 1591:Langston, Nancy (2013). "Mining the Boreal North". 321:method. The least squares method is used widely in 2956:"Google's DeepMind predicts 3D shapes of proteins" 137:causes a resurgence in machine learning research. 2655:"Computer Wins on 'Jeopardy!': Trivial, It's Not" 1692:McCarthy, J.; Feigenbaum, E. (1 September 1990). 1326:Siegelmann, H.T.; Sontag, E.D. (February 1995). 86:Statistical methods are discovered and refined. 2168:Proceedings of the National Academy of Sciences 2060:"位置ずれに影響されないパターン認識機構の神経回路のモデル --- ネオコグニトロン ---" 98:research is conducted using simple algorithms. 2715:"How Many Computers to Identify a Cat? 16,000" 2364:Tin Kam Ho (1995). "Random decision forests". 1549:(in French). Paris: Firmin Didot. p. viii 3099: 1679: 8: 2019:"Deep Learning (Section on Backpropagation)" 1328:"On the Computational Power of Neural Nets" 562:Automatic Differentiation (Backpropagation) 3106: 3092: 3084: 3067:Artificial Intelligence: A Modern Approach 2606:"Reasons to Believe the A.I. Boom Is Real" 2475:"THE MNIST DATABASE of handwritten digits" 296:. The essay presents work which underpins 253: 69: 2917: 2414: 2197: 2187: 2125: 2042: 1966: 1728: 1519: 1456: 1446: 1343: 1020:Using a combination of machine learning, 1489:Proceedings of KDD Cup and Workshop 2007 828:Tin Kam Ho publishes a paper describing 1923:Griewank, Andreas; Walther, A. (2008). 1910:Documenta Matematica, Extra Volume ISMP 1694:"In memoriam—Arthur Samuel (1901–1990)" 1675: 1624:The Bulletin of Mathematical Biophysics 1361:Journal of Computer and System Sciences 1332:Journal of Computer and System Sciences 1268: 2936: 2925: 2531: 2520: 2285: 2274: 2144: 2133: 1480:Bennett, James; Lanning, Stan (2007). 1309: 1307: 1305: 1303: 1301: 1299: 1024:and information retrieval techniques, 697:(first applied to neural networks by 509:(also known as noughts and crosses). 166:Support-Vector Clustering and other 7: 2058:Fukushima, Kunihiko (October 1979). 1859:(Thesis) (in Finnish). pp. 6–7. 1431:"Kernel methods in machine learning" 1412:Journal of Machine Learning Research 1313: 3214:Quantum computing and communication 2264:Watksin, Christopher (1 May 1989). 2066:(in Japanese). J62-A (10): 658–665. 1247:Timeline of artificial intelligence 875:beats the world champion at chess. 345:Théorie Analytique des Probabilités 3034:Marr, Bernard (19 February 2016). 2653:Markoff, John (16 February 2011). 1242:History of artificial intelligence 1123:researchers publish their work on 14: 2801:Jack Baskin School of Engineering 2368:. Vol. 1. pp. 278–282. 2579:Gershgorn, Dave (26 July 2017). 2303:Markoff, John (29 August 1990). 1502:Bayes, Thomas (1 January 1763). 599:first publishes his work on the 222: 22: 3046:from the original on 2022-12-05 2954:Sample, Ian (2 December 2018). 2803:. UC Santa Cruz. Archived from 2604:Hardy, Quentin (18 July 2016). 2266:"Learning from Delayed Rewards" 2120:Le Cun, Yann. "Deep Learning". 1794:Child, Oliver (13 March 2016). 1568:O'Connor, J J; Robertson, E F. 1543:Legendre, Adrien-Marie (1805). 1252:Timeline of machine translation 1098:A widely cited paper nicknamed 1032:beats two human champions in a 729:Universal approximation theorem 482:Cornell Aeronautical Laboratory 2713:Markoff, John (26 June 2012). 940:Torch Machine Learning Library 536:Limitations of Neural Networks 1: 3232:Free and open-source software 3069:. London: Pearson Education. 2829:Woodie, Alex (17 July 2014). 1290:10.1016/S0019-9958(64)90131-7 758:Christopher Watkins develops 613:convolutional neural networks 172:unsupervised machine learning 2889:. Google Inc. Archived from 2630:. Kaggle Inc. Archived from 2162:Hopfield, J J (April 1982). 1985:10.1016/j.neunet.2014.09.003 1381:10.1126/science.268.5210.545 1225:Protein Structure Prediction 1207:Protein Structure Prediction 868:IBM Deep Blue Beats Kasparov 812:temporal-difference learning 701:) is used in experiments by 495:Machines Playing Tic-Tac-Toe 429:First Neural Network Machine 56:timeline of machine learning 2682:10.1109/ICASSP.2013.6639343 1047:Recognizing Cats on YouTube 1022:natural language processing 963:competition is launched by 795:Machines Playing Backgammon 524:nearest neighbour algorithm 174:methods become widespread. 3575: 3269:Virtualization development 2987:10.1038/d41586-021-03499-y 2444:10.1162/neco.1997.9.8.1735 2044:10.4249/scholarpedia.32832 1508:Philosophical Transactions 1458:10.1214/009053607000000677 1162:program becomes the first 1017:Beating Humans in Jeopardy 655:content-addressable memory 625:Explanation Based Learning 2556:. Netflix. Archived from 2550:"The Netflix Prize Rules" 2399:"Support-vector networks" 2374:10.1109/ICDAR.1995.598994 2331:Communications of the ACM 1929:(Second ed.). SIAM. 1875:BIT Numerical Mathematics 1680:Russell & Norvig 2003 1214:(CASP) in December 2018. 808:artificial neural network 695:automatic differentiation 605:artificial neural network 449:Machines Playing Checkers 409:Turing's Learning Machine 152:recurrent neural networks 31:This article needs to be 3019:. New York: BasicBooks. 1663:10.1093/mind/LIX.236.433 1435:The Annals of Statistics 1117:Leap in Face Recognition 798:Gerald Tesauro develops 715:internal representations 651:recurrent neural network 639:Recurrent Neural Network 156:super-Turing computation 3194:Artificial intelligence 1278:Information and Control 927:handwriting recognition 855:support-vector machines 843:Support-Vector Machines 830:random decision forests 825:Random Forest Algorithm 780:Axcelis, Inc. releases 148:Support-vector machines 111:probabilistic inference 3323:John Vincent Atanasoff 3115:Timelines of computing 2935:Cite journal requires 2863:. BBC. 27 January 2016 2837:. Tabor Communications 2676:. pp. 8595–8598. 2530:Cite journal requires 2284:Cite journal requires 2189:10.1073/pnas.79.8.2554 2143:Cite journal requires 2079:Biological Cybernetics 1570:"Pierre-Simon Laplace" 1521:10.1098/rstl.1763.0053 1345:10.1006/jcss.1995.1013 923:American Census Bureau 898:long short-term memory 853:publish their work on 764:reinforcement learning 755:Reinforcement Learning 503:reinforcement learning 3458:Klára Dán von Neumann 3264:Programming languages 2343:10.1145/203330.203343 1678:, pp. 34–35 and 806:program that uses an 480:while working at the 315:Adrien-Marie Legendre 277:The Underpinnings of 113:in machine learning. 3237:Hypertext technology 1717:Psychological Review 1155:Beating Humans in Go 341:Pierre-Simon Laplace 236:adding missing items 3559:Computing timelines 2235:1986Natur.323..533R 2180:1982PNAS...79.2554H 2035:2015SchpJ..1032832S 2015:Schmidhuber, Jürgen 1977:2014arXiv1404.7828S 1951:Schmidhuber, Jürgen 1482:"The netflix prize" 1373:1995Sci...268..545S 1077:Visual Recognition 693:'s reverse mode of 546:publish their book 109:are introduced for 3363:Edsger W. Dijkstra 3318:Kathleen Antonelli 3302:Web search engines 3292:Internet conflicts 3171:Women in computing 2893:on 30 January 2016 2659:The New York Times 2610:The New York Times 2432:Neural Computation 2416:10.1007/BF00994018 2091:10.1007/BF00344251 1887:10.1007/BF01931367 1800:Chalkdust Magazine 1636:10.1007/BF02478259 1605:10.1511/2013.101.1 1593:American Scientist 1000:Kaggle Competition 894:Jürgen Schmidhuber 711:Ronald J. Williams 653:that can serve as 597:Kunihiko Fukushima 417:genetic algorithms 234:; you can help by 3541: 3540: 3483:Bjarne Stroustrup 3388:Margaret Hamilton 3368:J. Presper Eckert 3242:Operating systems 2981:(7886): 706–708. 2810:on 15 August 2017 2691:978-1-4799-0356-6 2229:(6088): 533–536. 1871:Linnainmaa, Seppo 1843:Linnainmaa, Seppo 1233: 1232: 1140:Researchers from 956:The Netflix Prize 774:Commercialization 647:Hopfield networks 397:artificial neuron 384:Artificial Neuron 252: 251: 212: 211: 204:(text-based) and 198:foundation models 52: 51: 3566: 3554:Machine learning 3468:Guido van Rossum 3453:John von Neumann 3398:David A. 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1541: 1537: 1501: 1500: 1496: 1484: 1479: 1478: 1474: 1428: 1427: 1423: 1409: 1408: 1404: 1367:(28): 632–637. 1358: 1357: 1353: 1325: 1324: 1320: 1312: 1297: 1275: 1274: 1270: 1265: 1260: 1238: 1104:word embeddings 890:Sepp Hochreiter 851:Vladimir Vapnik 736: 703:David Rumelhart 687:Backpropagation 674:Terry Sejnowski 611:later inspires 248: 242: 239: 223: 217: 135:backpropagation 133:Rediscovery of 82: 68: 54:This page is a 48: 42: 39: 36: 27: 23: 12: 11: 5: 3572: 3570: 3562: 3561: 3556: 3546: 3545: 3539: 3538: 3536: 3535: 3530: 3525: 3520: 3515: 3510: 3505: 3500: 3498:Linus Torvalds 3495: 3490: 3485: 3480: 3478:Frances Spence 3475: 3473:Claude Shannon 3470: 3465: 3463:Dennis Ritchie 3460: 3455: 3450: 3448:Marlyn Meltzer 3445: 3440: 3438:Joseph Kruskal 3435: 3430: 3425: 3420: 3415: 3410: 3405: 3400: 3395: 3390: 3385: 3380: 3375: 3370: 3365: 3360: 3355: 3350: 3345: 3340: 3335: 3330: 3325: 3320: 3314: 3312: 3311:Notable people 3308: 3307: 3305: 3304: 3299: 3294: 3288: 3286: 3280: 3279: 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493: 490: 486: 485: 471: 468: 465: 461: 460: 450: 447: 445: 441: 440: 430: 427: 425: 421: 420: 410: 407: 405: 401: 400: 386: 381: 378: 374: 373: 363: 360: 357: 353: 352: 349:Bayes' Theorem 338: 336:Bayes' Theorem 333: 331: 327: 326: 312: 309: 306: 302: 301: 281: 279:Bayes' Theorem 275: 272: 268: 267: 264: 261: 258: 250: 249: 229: 227: 216: 213: 210: 209: 191: 187: 186: 180: 176: 175: 168:kernel methods 164: 160: 159: 143: 139: 138: 131: 127: 126: 119: 115: 114: 104: 100: 99: 92: 88: 87: 84: 78: 77: 74: 67: 64: 62:are included. 50: 49: 30: 28: 21: 13: 10: 9: 6: 4: 3: 2: 3571: 3560: 3557: 3555: 3552: 3551: 3549: 3534: 3531: 3529: 3528:Steve Wozniak 3526: 3524: 3523:Niklaus Wirth 3521: 3519: 3516: 3514: 3511: 3509: 3506: 3504: 3501: 3499: 3496: 3494: 3491: 3489: 3486: 3484: 3481: 3479: 3476: 3474: 3471: 3469: 3466: 3464: 3461: 3459: 3456: 3454: 3451: 3449: 3446: 3444: 3441: 3439: 3436: 3434: 3431: 3429: 3426: 3424: 3423:Nancy Leveson 3421: 3419: 3416: 3414: 3413:Andrew Koenig 3411: 3409: 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32832. 2028: 2024: 2020: 2016: 2010: 2007: 2002: 1998: 1994: 1990: 1986: 1982: 1978: 1974: 1969: 1964: 1960: 1956: 1952: 1946: 1943: 1938: 1932: 1928: 1927: 1919: 1916: 1911: 1904: 1901: 1896: 1892: 1888: 1884: 1880: 1876: 1872: 1866: 1863: 1854: 1850: 1849: 1844: 1838: 1835: 1823: 1816: 1813: 1801: 1797: 1790: 1787: 1775: 1771: 1764: 1761: 1756: 1752: 1748: 1744: 1740: 1736: 1731: 1726: 1722: 1718: 1711: 1708: 1703: 1699: 1695: 1688: 1685: 1682:, p. 17. 1681: 1677: 1672: 1669: 1664: 1660: 1656: 1652: 1645: 1642: 1637: 1633: 1629: 1625: 1618: 1615: 1611: 1606: 1602: 1598: 1594: 1587: 1584: 1571: 1564: 1561: 1548: 1547: 1539: 1536: 1531: 1527: 1522: 1517: 1513: 1509: 1505: 1498: 1495: 1490: 1483: 1476: 1473: 1468: 1464: 1459: 1454: 1449: 1444: 1440: 1436: 1432: 1425: 1422: 1417: 1413: 1406: 1403: 1398: 1394: 1390: 1386: 1382: 1378: 1374: 1370: 1366: 1362: 1355: 1352: 1346: 1341: 1337: 1333: 1329: 1322: 1319: 1315: 1310: 1308: 1306: 1304: 1302: 1300: 1296: 1291: 1287: 1283: 1279: 1272: 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273: 270: 269: 265: 262: 259: 256: 255: 246: 243:December 2022 237: 233: 230:This list is 228: 221: 220: 214: 207: 203: 199: 195: 194:Generative AI 192: 189: 188: 184: 183:Deep learning 181: 178: 177: 173: 169: 165: 162: 161: 157: 153: 149: 144: 141: 140: 136: 132: 129: 128: 124: 120: 117: 116: 112: 108: 105: 102: 101: 97: 93: 90: 89: 85: 80: 79: 75: 72: 71: 65: 63: 61: 57: 46: 34: 29: 20: 19: 16: 3493:Ken Thompson 3433:Donald Knuth 3428:Ada Lovelace 3393:Grace Hopper 3358:Stephen Cook 3343:George Boole 3297:Web browsers 3208: 3204:Cryptography 3066: 3048:. Retrieved 3039: 3016: 2978: 2974: 2968: 2960:The Guardian 2959: 2949: 2928:cite journal 2907: 2895:. Retrieved 2891:the original 2886: 2877: 2865:. Retrieved 2860: 2851: 2839:. Retrieved 2834: 2824: 2812:. Retrieved 2805:the original 2800: 2786: 2774:. Retrieved 2770: 2760: 2749:. Retrieved 2747:. 2017-07-26 2744: 2735: 2723:. Retrieved 2721:. p. B1 2718: 2708: 2673: 2667: 2658: 2648: 2636:. Retrieved 2632:the original 2627: 2618: 2609: 2599: 2588:. Retrieved 2584: 2574: 2562:. Retrieved 2558:the original 2553: 2544: 2523:cite journal 2511:. Retrieved 2504:the original 2490: 2478:. Retrieved 2468: 2435: 2431: 2425: 2406: 2402: 2392: 2365: 2359: 2337:(3): 58–68. 2334: 2330: 2324: 2312:. Retrieved 2308: 2298: 2277:cite journal 2259: 2226: 2222: 2216: 2171: 2167: 2157: 2136:cite journal 2115: 2082: 2078: 2072: 2063: 2053: 2026: 2023:Scholarpedia 2022: 2009: 1958: 1954: 1945: 1925: 1918: 1909: 1903: 1878: 1874: 1865: 1852: 1847: 1837: 1825:. Retrieved 1815: 1803:. 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IECE 1704:(3): 10–11. 1698:AI Magazine 1514:: 370–418. 1222:Achievement 1204:Achievement 1194:transformer 1192:invent the 1164:Computer Go 1152:Achievement 1114:Achievement 1044:Achievement 1014:Achievement 865:Achievement 792:Achievement 737: [ 734:Kurt Hornik 699:Paul Werbos 684:Application 549:Perceptrons 507:Tic-tac-toe 492:Achievement 413:Alan Turing 150:(SVMs) and 94:Pioneering 43:August 2021 3548:Categories 3513:Larry Wall 3508:Paul Vixie 3378:Lois Haibt 3353:John Cocke 3247:DOS family 3189:Algorithms 3166:Scientific 3050:2022-12-25 2919:1706.03762 2751:2023-09-12 2590:2018-03-30 1961:: 85–117. 1912:: 389–400. 1258:References 1188:A team at 1182:Discovery 1092:Discovery 1074:Discovery 986:Fei-Fei Li 915:Yann LeCun 804:backgammon 760:Q-learning 478:perceptron 470:Perceptron 380:Discovery 343:publishes 260:Event type 232:incomplete 3348:Vint Cerf 3136:1950–1979 3123:Computing 2995:244528561 2883:"AlphaGo" 2700:206741597 2251:205001834 2122:CiteSeerX 2107:206775608 1968:1404.7828 1895:122357351 1725:CiteSeerX 1314:Marr 2016 1263:Citations 1172:AlphaZero 1158:Google's 1060:Jeff Dean 1056:Andrew Ng 1034:Jeopardy! 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Index

machine learning
machine learning
Bayesian methods
probabilistic inference
AI winter
backpropagation
Support-vector machines
recurrent neural networks
super-Turing computation
kernel methods
unsupervised machine learning
Deep learning
Generative AI
foundation models
ChatGPT
Stable Diffusion
incomplete
adding missing items
Bayes' Theorem
Thomas Bayes
An Essay Towards Solving a Problem in the Doctrine of Chances
Richard Price
Bayes theorem
Adrien-Marie Legendre
least squares
data fitting
Bayes' Theorem
Pierre-Simon Laplace
Bayes' Theorem
Andrey Markov

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