Революция разума: на подступах к Сингулярности. Как технологии изменят общество и сознание - Рэймонд Курцвейл

16. Digital Equipment Corporation, PDP-1 Handbook (Maynard, MA: Digital Equipment Corporation, 1963), 10, http://s3data.computerhistory.org/pdp-1/DEC.pdp_1.1963.10263 6240.pdf.

17. Amin Vahdat and Mark Lohmeyer, “Enabling Next-Generation AI Workloads: Announcing TPU v5p and AI Hypercomputer”, Google Cloud, December 6, 2023, https://cloud.google.com/blog/products/ai-machine-learning/introducing-cloud-tpu-v5p-and-ai-hy percomputer.

18. Все источники данных для оценки соотношения цена/производительность компьютеров, упомянутых в этой книге, приведены в приложении.

19. V. L. Yu et al., “Antimicrobial Selection by a Computer: A Blinded Evaluation by Infectious Diseases Experts”, Journal of the American Medical Association 242, no. 12 (September 21, 1979): 1279–82, https://jamanetwork.com/journals/jama/article-abstract/366606.

20. Bruce G. Buchanan and Edward Hance Shortliffe, eds., Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project (Reading, MA: Addison-Wesley, 1984); Edward Edelson, “Programmed to Think”, MOSAIC 11, no. 5 (September/ October 1980): 22, https://books.google.co.uk/books?id=PU79ZK2tXeAC.

21. T. Grandon Gill, “Early Expert Systems: Where Are They Now?”, MIS Quarterly 19, no. 1 (March 1995): 51–81, https://www.jstor.org/stable/249711.

22. Краткое объяснение простым языком, каким именно образом машинное обучение снижает остроту проблемы потолка сложности, приведено в Deepanker Saxena, “Machine Learning vs. Rules Based Systems”, Socure, August 6, 2018, https://www.socure.com/blog/machine-learning-vs-rule-based-systems.

23. Cade Metz, “One Genius’ Lonely Crusade to Teach a Computer Common Sense”, Wired, March 24, 2016, https://www.wired.com/2016/03/doug-lenat-artificial-intelligence-com mon-sense-engine; “Frequently Asked Questions”, Cycorp, последняя проверка доступности 20 ноября 2021 года, https://cyc.com/faq.

24. Больше информации о проблеме «черного ящика» и непрозрачности ИИ содержится в Will Knight, “The Dark Secret at the Heart of AI”, MIT Technology Review, April 11, 2017, https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai; “AI Detectives Are Cracking Open the Black Box of Deep Learning”, Science Magazine, YouTube video, July 6, 2017, https://www.youtube.com/watch?v=gB_-LabED68; Paul Voosen, “How AI Detectives Are Cracking Open the Black Box of Deep Learning”, Science, July 6, 2017, https://doi.org /10.1126/science.aan7059; Harry Shum, “Explaining AI”, a16z, YouTube video, January 16, 2020, https://www.youtube.com/watch?v=rI_L95qnVkM; Future of Life Institute, “Neel Nanda on What Is Going On Inside Neural Networks”, YouTube video, February 9, 2023, https://www.youtube.com/watch?v=mUhO6st6M_0.

25. Отличный обзор по механистической интерпретируемости приведен в: Neel Nanda, Future of Life Institute, “Neel Nanda on What Is Going On Inside Neural Networks”.

26. Более подробно о методиках машинного обучения при неполных данных см. в Xander Steenbrugge, “An Introduction to Reinforcement Learning”, Arxiv Insights, YouTube video, April 2, 2018, https://www.youtube.com/watch?v=JgvyzIkgxF0; Alan Joseph Bekker and Jacob Goldberger, “Training Deep Neural-Networks Based on Unreliable Labels”, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (Shanghai, 2016), 2682–86, https://doi.org/10.1109/ICASSP.2016.7472164; Nagarajan Natarajan et al., “Learning with Noisy Labels”, Advances in Neural Information Processing Systems 26 (2013), https://papers.nips.cc/paper/5073-learning-with-noisy-labels; David Rolnick et al., “Deep Learning Is Robust to Massive Label Noise”, arXiv:1705.10694v3 [cs.LG], February 26, 2018, https://arxiv.org/pdf/1705.10694.pdf.

27. Больше информации о перцептроне, присущих ему ограничениях и о том, как некоторые виды нейросетей могут их обойти, см. Marvin L. Minsky and Seymour A. Papert, Perceptrons: An Introduction to Computational Geometry (Cambridge, MA: MIT Press, 1990; reissue of 1988 expanded edition); Melanie Lefkowitz, “Professor’s Perceptron Paved the Way for AI—60 Years Too Soon”, Cornell Chronicle, September 25, 2019, https://news.cornell.edu/stories/2019/09/professors-perceptron-paved-way-ai-60-years-too-soon; John Durkin, “Tools and Applications”, in Expert Systems: The Technology of Knowledge Management and Decision Making for the 21st Century, ed. Cornelius T. Leondes (San Diego: Academic Press, 2002), 45, https://books.google.co.uk/books?id=5kSam KhS56 °C; “Marvin Minsky: The Problem with Perceptrons (121/151)”, Web of Stories – Life Stories of Remarkable People, YouTube video, October 17, 2016, https://www.you tube.com/watch?v=QW_srPO-LrI; Heinz Mühlenbein, “Limitations of Multi-Layer Perceptron Networks: Steps Towards Genetic Neural Networks”, Parallel Computing 14, no. 3 (August 1990): 249–60, https://doi.org/10.1016/0167-8191(90)90079-O; Aniruddha Karajgi, “How Neural Networks Solve the XOR Problem”, Towards Data Science, November 4, 2020, https://towardsdatascience.com/how-neural-networks-solve-the-xor-problem-59763136bdd7.

28. Все источники данных для оценки соотношения цена/производительность компьютеров, упомянутых в этой книге, приведены в приложении.

29. Tim Fryer, “Da Vinci Drawings Brought to Life”, Engineering & Technology 14, no. 5 (May 21, 2019): 18, https://eandt.theiet.org/content/articles/2019/05/da-vinci-drawings-brought-to-life.

30. Хронология возникновения жизни на Земле и более подробные научные сведения содержатся в: Michael Marshall, “Timeline: The Evolution of Life”, New Scientist, July 14, 2009, https://www.newscientist.com/article/dn17453; Dyani Lewis, “Where Did We Come From? A Primer on Early Human Evolution”, Cosmos, June 9, 2016, https://cosmos magazine.com/palaeontology/where-did-we-come-from-a-primer-on-early-human-evolution; John Hawks, “How Has the Human Brain Evolved?”, Scientific American, July 1, 2013, https://www.scientificamerican.com/article/how-has-human-brain-evolved; Laura Freberg, Discovering Behavioral Neuroscience: An Introduction to Biological Psychology, 4th ed. (Boston: Cengage Learning, 2018), 62–63, https://books.google.co.uk/books?id=HhBED wAAQBAJ; Jon H. Kaas, “Evolution of the Neocortex”, Current Biology 16, no. 21 (2006): R910–R914, https://www.cell.com/current-biology/pdf/S0960-9822(06)02290-1.pdf; R. Glenn Northcutt, “Evolution of Centralized Nervous Systems: Two Schools of Evolutionary Thought”, Proceedings of the National Academy of Sciences 109, suppl. 1 (June 22, 2012): 10626–33, https://doi.org/10.1073/pnas.1201889109.

31. Marshall, “Timeline: The Evolution of Life”; Holly C. Betts et al., “Integrated Genomic and Fossil Evidence Illuminates Life’s Early Evolution and Eukaryote Origin”, Nature Ecology & Evolution 2 (August 20, 2018): 1556–62, https://doi.org/10.1038/s41559-018-0644-x; Elizabeth Pennisi, “Life May Have Originated on Earth 4 Billion Years Ago, Study of Controversial Fossils Suggests”, Science, December 18, 2017, https://www.sciencemag.org /news/2017/12/life-may-have-originated-earth-4-billion-years-ago-study-controversial-fossils-suggests.

32. Ethan Siegel, “Ask Ethan: How Do We Know the Universe Is 13.8 Billion Years Old?”, Big Think, October 22, 2021, https://bigthink.com/starts-with-a-bang/universe-13-8-billion-years; Mike Wall, “The Big Bang: What Really Happened at Our Universe’s Birth?”, Space.com, October 21, 2011, https://www.space.com/13347-big-bang-origins-universe-birth.html; Nola Taylor Reed, “How Old Is Earth?”, Space.com, February 7, 2019, https:// www.space.com/24854-how-old-is-earth.html.

33. Marshall, “Timeline: The Evolution of Life”.

34. Marshall, “Timeline: The Evolution of Life”.

35. Freberg, Discovering Behavioral Neuroscience, 62–63; Kaas, “Evolution of the Neocortex”; R. Northcutt, “Evolution of Centralized Nervous Systems”; Frank Hirth, “On the Origin and Evolution of the Tripartite Brain”, Brain, Behavior and Evolution 76, no. 1 (October 2010): 3–10, https://doi.org/10.1159/000320218.

36. Kaas, “Evolution of the Neocortex”.

37. Два захватывающих видео о том, как работает естественный отбор: Hank Green, “Natural Selection: Crash Course Biology #14”, CrashCourse, YouTube video, April 30, 2012, https://www.youtube.com/watch?v=aTftyFboC_M; Primer, “Simulating Natural Selection”, YouTube video, November 14, 2018, https://www.youtube.com/watch?v=0ZGbIK d0XrM.

38. Suzana Herculano-Houzel, “Coordinated Scaling of Cortical and Cerebellar Numbers of Neurons”, Frontiers in Neuroanatomy 4, no. 12 (March 10, 2010), https://doi.org/10.3389 /fnana.2010.00012.

39. Объяснение этого феномена см. в: Ainslie Johnstone, “The Amazing Phenomenon of Muscle Memory”, Medium, Oxford University, December 14, 2017, https:// medium.com/oxford-university/the-amazing-phenomenon-of-muscle-memory-fb1cc4c4726; Sara Chodosh, “Muscle Memory Is Real, But It’s Probably Not What You Think”, Popular Science, January 25, 2019, https://www.popsci.com/what-is-muscle-memory; Merim Bilalić, The Neuroscience of Expertise (Cambridge, UK: Cambridge University Press, 2017), 171–72, https://books.google.co.uk/books?id=QILTDQAAQBAJ; The Brain from Top to Bottom,