Peter Norvig

Last updated

Peter Norvig
Peter Norvig in 2019 (cropped).jpg
Peter Norvig in 2019
Born (1956-12-14) December 14, 1956 (age 67)
Nationality American
Alma mater Brown University
University of California, Berkeley
Known for Artificial Intelligence: A Modern Approach
Paradigms of AI Programming: Case Studies in Common Lisp
Awards
Scientific career
Fields Artificial Intelligence [2]
Institutions Stanford University
Google
Ames Research Center
University of Southern California
Brown University
University of California, Berkeley
Thesis A Unified Theory of Inference for Text Understanding  (1986)
Doctoral advisor Robert Wilensky [3]
Website www.norvig.com OOjs UI icon edit-ltr-progressive.svg
Signature
Peter Norvig signature.png

Peter Norvig (born December 14, 1956) is an American computer scientist and Distinguished Education Fellow at the Stanford Institute for Human-Centered AI. [4] He previously served as a director of research and search quality at Google. [5] [2] [6] Norvig is the co-author with Stuart J. Russell of the most popular textbook in the field of AI: Artificial Intelligence: A Modern Approach used in more than 1,500 universities in 135 countries. [7]

Contents

Education

Norvig received a Bachelor of Science in applied mathematics from Brown University [8] and a Ph.D. in computer science from the University of California, Berkeley. [3]

Career and research

Norvig is a councilor of the Association for the Advancement of Artificial Intelligence and co-author, with Stuart J. Russell, of Artificial Intelligence: A Modern Approach , now the leading college text in the field. [9] He was head of the Computational Sciences Division (now the Intelligent Systems Division) at NASA Ames Research Center, where he oversaw a staff of 200 scientists performing NASA's research and development in autonomy and robotics, automated software engineering and data analysis, neuroengineering, collaborative systems research, and simulation-based decision-making. Before that he was chief scientist at Junglee, where he helped develop one of the first Internet comparison-shopping services; chief designer at Harlequin Inc.; and senior scientist at Sun Microsystems Laboratories.

Norvig has served as an assistant professor at the University of Southern California and as a research faculty member at Berkeley. He has over fifty publications in various areas of computer science, concentrating on artificial intelligence, natural language processing, information retrieval [10] and software engineering, including the books Artificial Intelligence: A Modern Approach , [11] Paradigms of AI Programming: Case Studies in Common Lisp , [12] Verbmobil: A Translation System for Face-to-Face Dialog, and Intelligent Help Systems for UNIX. [13]

Norvig is one of the creators of JScheme. Norvig is listed under "Academic Faculty & Advisors" for the Singularity University. [14] In 2011, Norvig worked with Sebastian Thrun to develop a popular online course in Artificial Intelligence [15] that had more than 160,000 students enrolled. [16] He also teaches an online course via the Udacity platform. [17]

Selected publications and presentations

By 2022, Artificial Intelligence: A Modern Approach , which Norvig first co-authored with Stuart J. Russell in 1995, was the leading textbook in the field used by over 1400 schools globally. [9] [7]

In 2001, Norvig published a short article titled Teach Yourself Programming in Ten Years, [18] arguing against the fashionable introductory programming textbooks that purported to teach programming in days or weeks. The article was widely shared and discussed, and has attracted contributed translations to over 20 languages. [18]

Norvig is also known for his 2003 Gettysburg Powerpoint Presentation, [19] a satire about bad presentation practices [20] using Abraham Lincoln's famous Gettysburg Address.

His 2009 IEEE Intelligent Systems article, "The Unreasonable Effectiveness of Data" co-authored with Alon Y. Halevy and Fernando Pereira, described how the best approach to highly complex natural language understanding problems is to harness large quantities of data, not to depend on "tidy", simple formulas. [8] They said that by generating "large amounts of unlabeled, noisy data, new algorithms can be used to build high-quality models from the data. This has informed the development of foundation models. [8] "But invariably, simple models and a lot of data trump more elaborate models based on less data." [8] : 9  "Choose a representation that can use unsupervised learning on unlabeled data, which is so much more plentiful than labeled data." [8] : 12  The title refers to the physicist Eugene Wigner's 1960 journal article, "The Unreasonable Effectiveness of Mathematics in the Natural Sciences". [21]

In a 23 September 2010 lecture presented as part of the Vancouver-based University of British Columbia's Department of Computer Science's Distinguished Lecture Series, Norvig, who was then the Director of Research at Google, described how large quantities of data deepen our understanding of phenomena. [22]

In his June 2012 Ted Talk, described the fall of 2011 hybrid class on artificial intelligence attended by 100,000 online students around the globe that he co-taught with Sebastian Thrun at Stanford University. [23]

Awards and honors

Norvig was elected an AAAI Fellow in 2001 and a fellow of the Association for Computing Machinery in 2006.

Related Research Articles

Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. Such machines may be called AIs.

<span class="mw-page-title-main">Eliezer Yudkowsky</span> American AI researcher and writer (born 1979)

Eliezer S. Yudkowsky is an American artificial intelligence researcher and writer on decision theory and ethics, best known for popularizing ideas related to friendly artificial intelligence. He is the founder of and a research fellow at the Machine Intelligence Research Institute (MIRI), a private research nonprofit based in Berkeley, California. His work on the prospect of a runaway intelligence explosion influenced philosopher Nick Bostrom's 2014 book Superintelligence: Paths, Dangers, Strategies.

In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. The Symbolic AI paradigm led to seminal ideas in search, symbolic programming languages, agents, multi-agent systems, the semantic web, and the strengths and limitations of formal knowledge and reasoning systems.

Friendly artificial intelligence is hypothetical artificial general intelligence (AGI) that would have a positive (benign) effect on humanity or at least align with human interests or contribute to fostering the improvement of the human species. It is a part of the ethics of artificial intelligence and is closely related to machine ethics. While machine ethics is concerned with how an artificially intelligent agent should behave, friendly artificial intelligence research is focused on how to practically bring about this behavior and ensuring it is adequately constrained.

In the history of artificial intelligence (AI), neat and scruffy are two contrasting approaches to AI research. The distinction was made in the 1970s, and was a subject of discussion until the mid-1980s.

The Association for the Advancement of Artificial Intelligence (AAAI) is an international scientific society devoted to promote research in, and responsible use of, artificial intelligence. AAAI also aims to increase public understanding of artificial intelligence (AI), improve the teaching and training of AI practitioners, and provide guidance for research planners and funders concerning the importance and potential of current AI developments and future directions.

<i>Artificial Intelligence: A Modern Approach</i> Book by Stuart J. Russell and Peter Norvig

Artificial Intelligence: A Modern Approach (AIMA) is a university textbook on artificial intelligence (AI), written by Stuart J. Russell and Peter Norvig. It was first published in 1995, and the fourth edition of the book was released on 28 April 2020.

<span class="mw-page-title-main">Stuart J. Russell</span> British computer scientist and author (born 1962)

Stuart Jonathan Russell is a British computer scientist known for his contributions to artificial intelligence (AI). He is a professor of computer science at the University of California, Berkeley and was from 2008 to 2011 an adjunct professor of neurological surgery at the University of California, San Francisco. He holds the Smith-Zadeh Chair in Engineering at University of California, Berkeley. He founded and leads the Center for Human-Compatible Artificial Intelligence (CHAI) at UC Berkeley. Russell is the co-author with Peter Norvig of the authoritative textbook of the field of AI: Artificial Intelligence: A Modern Approach used in more than 1,500 universities in 135 countries.

A rational agent or rational being is a person or entity that always aims to perform optimal actions based on given premises and information. A rational agent can be anything that makes decisions, typically a person, firm, machine, or software.

Synthetic intelligence (SI) is an alternative/opposite term for artificial intelligence emphasizing that the intelligence of machines need not be an imitation or in any way artificial; it can be a genuine form of intelligence. John Haugeland proposes an analogy with simulated diamonds and synthetic diamonds—only the synthetic diamond is truly a diamond. Synthetic means that which is produced by synthesis, combining parts to form a whole; colloquially, a human-made version of that which has arisen naturally. A "synthetic intelligence" would therefore be or appear human-made, but not a simulation.

<span class="mw-page-title-main">Intelligent agent</span> Software agent which acts autonomously

In intelligence and artificial intelligence, an intelligent agent (IA) is an agent that perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or acquiring knowledge.

<span class="mw-page-title-main">History of artificial intelligence</span>

The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The study of logic and formal reasoning from antiquity to the present led directly to the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain.

The philosophy of artificial intelligence is a branch of the philosophy of mind and the philosophy of computer science that explores artificial intelligence and its implications for knowledge and understanding of intelligence, ethics, consciousness, epistemology, and free will. Furthermore, the technology is concerned with the creation of artificial animals or artificial people so the discipline is of considerable interest to philosophers. These factors contributed to the emergence of the philosophy of artificial intelligence.

The following outline is provided as an overview of and topical guide to artificial intelligence:

<span class="mw-page-title-main">Nils John Nilsson</span> American computer scientist (1933–2019)

Nils John Nilsson was an American computer scientist. He was one of the founding researchers in the discipline of artificial intelligence. He was the first Kumagai Professor of Engineering in computer science at Stanford University from 1991 until his retirement. He is particularly known for his contributions to search, planning, knowledge representation, and robotics.

This is a timeline of artificial intelligence, sometimes alternatively called synthetic intelligence.

<span class="mw-page-title-main">Udacity</span> For-profit educational organization

Udacity, Inc. is an American for-profit educational organization founded by Sebastian Thrun, David Stavens, and Mike Sokolsky offering massive open online courses.

In the philosophy of artificial intelligence, GOFAI is classical symbolic AI, as opposed to other approaches, such as neural networks, situated robotics, narrow symbolic AI or neuro-symbolic AI. The term was coined by philosopher John Haugeland in his 1985 book Artificial Intelligence: The Very Idea.

Robert Wilensky was an American computer scientist and emeritus professor at the UC Berkeley School of Information, with his main focus of research in artificial intelligence.

David Stavens is an American entrepreneur and scientist. He has made significant contributions to the field of AI, co-founding the team that developed Stanley, the self-driving car that led to Google's Waymo, as well as Udacity, an online education platform for technology and AI that has educated millions globally. He also co-founded Nines, a company that built AI-enabled, FDA-approved medical devices. Stavens has published in the fields of robotics, machine learning, and artificial intelligence, and has contributed to starting companies with an aggregate market value of over $30 billion.

References

  1. ↑ "Elected AAAI Fellows". Association for the Advancement of Artificial Intelligence. Retrieved 23 September 2024.
  2. 1 2 Peter Norvig publications indexed by Google Scholar OOjs UI icon edit-ltr-progressive.svg
  3. 1 2 Norvig, Peter (1986). A Unified Theory of Inference for Text Understanding (PhD thesis). University of California, Berkeley. OCLC   901967025. ProQuest   303443749.
  4. ↑ Lynch, Shana (2021). "Peter Norvig: Today's Most Pressing Questions in AI Are Human-Centered". Stanford University.
  5. ↑ "Peter Norvig's home page". Norvig.com. Retrieved 1 April 2020.
  6. ↑ Peter Norvig at DBLP Bibliography Server OOjs UI icon edit-ltr-progressive.svg
  7. 1 2 "1464 Schools Worldwide That Have Adopted AIMA". Computer Science Division at UC Berkeley. Artificial Intelligence: A Modern Approach. 22 August 2022. Retrieved 29 February 2020.
  8. 1 2 3 4 5 Halevy, Alon; Norvig, P.; Pereira, Fernando (2009). Brannon, Brian (ed.). "The Unreasonable Effectiveness of Data" (PDF). IEEE Intelligent Systems. 24 (2): 8–12. doi:10.1109/MIS.2009.36. S2CID   14300215 . Retrieved 21 September 2022.
  9. 1 2 Russell, Stuart J.; Norvig, Peter (2020) [1995]. Artificial Intelligence: A Modern Approach (4 ed.). Prentice Hall. p. 1136. ISBN   978-0-13-461099-3. OCLC   359890490.
  10. ↑ Michel, J. -B.; Shen, Y. K.; Aiden, A. P.; Veres, A.; Gray, M. K.; Google Books Team; Pickett, D.; Hoiberg, D.; Clancy, P.; Norvig, J.; Orwant, S.; Pinker, M. A.; Nowak, E. L.; Aiden, E. L. (2011). "Quantitative Analysis of Culture Using Millions of Digitized Books" (PDF). Science. 331 (6014): 176–182. Bibcode:2011Sci...331..176M. doi:10.1126/science.1199644. PMC   3279742 . PMID   21163965.
  11. ↑ 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
  12. ↑ Norvig, Peter (1992), Paradigms of artificial intelligence programming: case studies in common LISP, Amsterdam: Morgan Kaufmann Publishers, ISBN   1-55860-191-0
  13. ↑ Hegner, Stephen J.; Kevitt, Paul Mc; Norvig, Peter; Wilensky, Robert L. (6 December 2012). Intelligent Help Systems for UNIX. Springer Science & Business Media. ISBN   978-94-010-0874-7.
  14. ↑ "Singularity University list of Faculty and Advisors". Singularityu.org. Archived from the original on 13 October 2009. Retrieved 8 October 2009.
  15. ↑ "Intro to AI - Introduction to Artificial Intelligence - Oct-Dec 2011". Ai-class.com. Archived from the original on 17 October 2012. Retrieved 5 February 2012.
  16. ↑ Naughton, John (5 February 2012). "Welcome to the desktop degree". The Guardian via The Observer. Retrieved 5 February 2012.
  17. ↑ "Udacity - Design of Computer Programs". Udacity.com. Archived from the original on 13 April 2012. Retrieved 26 October 2012.
  18. 1 2 "Teach Yourself Programming in Ten Years". Norvig.com. Retrieved 6 June 2017.
  19. ↑ "The Gettysburg Powerpoint Presentation". Norvig.com. Retrieved 26 October 2012.
  20. ↑ Norvig, P. (2003). "PowerPoint: Shot with its own bullets". The Lancet. 362 (9381): 343–344. doi:10.1016/S0140-6736(03)14056-1. PMID   12907004. S2CID   34835018.
  21. ↑ Wigner, Eugene P. (1960). "The unreasonable effectiveness of mathematics in the natural sciences". Communications on Pure and Applied Mathematics. 13 (1): 1–14. Bibcode:1960CPAM...13....1W. doi:10.1002/cpa.3160130102. S2CID   6112252. Archived from the original on 12 February 2021. The Richard Courant lecture in mathematical sciences delivered at New York University, May 11, 1959
  22. ↑ Peter Norvig (guest), UBC Computer Science (Host) (11 October 2011) [2010]. How Billions of Trivial Data Points can Lead to Understanding. Event occurs at 1:02:56. Retrieved 21 September 2022– via YouTube.
  23. ↑ Norvig, Peter (June 2012). "A classroom with 100 000 students". TED Talk . Retrieved 21 September 2022.
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