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John Hopfield

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This is an old revision of this page, as edited by Inotti twitter (talk | contribs) at 12:31, 10 October 2024 (→Awards and honors: Corrected the parameter date of Template:Cite AV media). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

For his father, the Polish-American spectroscopist, see John J. Hopfield (spectroscopist).

John Hopfield
Hopfield in 2016
Born
John Joseph Hopfield

(1933-07-15) July 15, 1933 (age 91)
Chicago, Illinois, U.S.
EducationSwarthmore College (AB)
Cornell University (PhD)
Known forHopfield network
Modern Hopfield network
Hopfield dielectric
Polariton
Kinetic proofreading
Awards
Scientific career
FieldsPhysics
Molecular biology
Complex systems
Neuroscience
InstitutionsBell Labs
Princeton University
University of California, Berkeley
California Institute of Technology
ThesisA quantum-mechanical theory of the contribution of excitons to the complex dielectric constant of crystals (1958)
Doctoral advisorAlbert Overhauser
Doctoral studentsSteven Girvin
Bertrand Halperin
David J. C. MacKay
José Onuchic
Terry Sejnowski
Erik Winfree

John Joseph Hopfield (born July 15, 1933)[1] is an American physicist and emeritus professor of Princeton University, most widely known for his study of associative neural networks in 1982. He is known for the development of the Hopfield network.

In 2024 Hopfield, along with Geoffrey Hinton, was awarded the Nobel Prize in Physics for their foundational contributions to machine learning, particularly through their work on artificial neural networks.[2][3] He has been awarded various major physics awards for his work in multidisciplinary fields including condensed matter physics, statistical physics and biophysics.

Biography

Early life and education

John Joseph Hopfield was born in 1933 in Chicago[1] to physicists John Joseph Hopfield (born Jan Józef Chmielewski) and Helen Hopfield (née Staff).[4][5]

Hopfield received a Bachelor of Arts with a major in physics from Swarthmore College in Pennsylvania in 1954 and a Doctor of Philosophy in physics from Cornell University in 1958.[1] His doctoral dissertation was titled "A quantum-mechanical theory of the contribution of excitons to the complex dielectric constant of crystals".[6] His doctoral advisor was Albert Overhauser.[1]

Career

He spent two years in the theory group at Bell Laboratories working on optical properties of semiconductors working with David Gilbert Thomas[7] and later on a quantitative model to describe the cooperative behavior of hemoglobin in collaboration with Robert G. Shulman.[1][4][8] Subsequently he became a faculty member at University of California, Berkeley (physics, 1961–1964),[3] Princeton University (physics, 1964–1980),[3] California Institute of Technology (Caltech, chemistry and biology, 1980–1997)[3] and again at Princeton (1997–),[3][1] where he is the Howard A. Prior Professor of Molecular Biology, emeritus.[9]

In 1976, he participated in a science short film on the structure of the hemoglobin, featuring Linus Pauling.[10]

From 1981–1983 Richard Feynman, Carver Mead and Hopfield gave a one-year course at Caltech called the "The Physics of Computation".[11] Hopfield was invited by Feynman to teach on associative neural networks.[11][12] This collaboration inspired the Computation and Neural Systems PhD program at Caltech in 1986, co-founded by Hopfield.[13][11]

Work

In his doctoral work of 1958, he wrote on the interaction of excitons in crystals, coining the term polariton for a quasiparticle that appears in solid-state physics.[14][15] He wrote: "The polarization field 'particles' analogous to photons will be called 'polaritons'."[15] His polariton model is sometimes known as the Hopfield dielectric.[16]

Condensed matter physicist Philip W. Anderson reported that John Hopfield was his "hidden collaborator" for his 1961–1970 works on the Anderson impurity model which explained the Kondo effect. Hopfield was not included as a co-author in the papers but Anderson admitted the importance of Hopfield's contribution in various of his writings.[17]

In 1974 he introduced a mechanism for error correction in biochemical reactions known as kinetic proofreading to explain the accuracy of DNA replication.[18][19]

Hopfield published his first paper in neuroscience in 1982, titled "Neural networks and physical systems with emergent collective computational abilities" where he introduced what is now known as Hopfield network, a type of artificial network that can serve as a content-addressable memory, made of binary neurons that can be 'on' or 'off'.[20][4] Hopfield has said that the inspiration came from his knowledge of spin glasses from his collaborations with P. W. Anderson.[21]

Together with David W. Tank, Hopfield developed a method in 1985–1986[22][23] for solving discrete optimization problems based on the continuous-time dynamics using a Hopfield network with continuous activation function. The optimization problem was encoded in the interaction parameters (weights) of the network. The effective temperature of the analog system was gradually decreased, as in global optimization with simulated annealing.[24]

The original Hopfield networks had a limited memory, this problem was addressed by Hopfield and Dimitry Krotov in 2016.[24][25] Large memory storage Hopfield networks are now known as modern Hopfield networks.[26]

Views on artificial intelligence

In March 2023, Hopfield signed an open letter titled "Pause Giant AI Experiments", calling for a pause on the training of artificial intelligence (AI) systems more powerful than GPT-4. The letter, signed by over 30,000 individuals including AI researchers Yoshua Bengio and Stuart Russell, cited risks such as human obsolescence and society-wide loss of control.[27][28]

Upon being jointly awarded the 2024 Nobel Prize in Physics along with AI researcher Geoffrey Hinton, Hopfield revealed he was very unnerved by recent advances in AI capabilities, and said "as a physicist, I'm very unnerved by something which has no control".[29]

Awards and honors

Hopfield received a Sloan Research Fellowship[30] in 1962 and as his father, he received a Guggenheim Fellowship (1968).[31] Hopfield was elected as a member of the National Academy of Sciences in 1973, a member of the American Academy of Arts and Sciences in 1975, and a member of the American Philosophical Society in 1988.[32][33][34]

In 1969 Hopfield and David Gilbert Thomas were awarded the Oliver E. Buckley Prize of condensed matter physics "for their joint work combining theory and experiment which has advanced the understanding of the interaction of light with solids".[35]

In 1983 he was awarded the MacArthur Foundational Prize by the MacArthur Fellows Program.[36] In 1985, Hopfield received the Golden Plate Award of the American Academy of Achievement[37] and the Max Delbruck Prize in Biophysics by American Physical Society.[8] Hopfield received the Neural Networks Pioneer Award in 1997 by the Institute of Electrical and Electronics Engineers (IEEE).[38]

He was awarded the Dirac Medal of the International Centre for Theoretical Physics in 2001 "for important contributions in an impressively broad spectrum of scientific subjects"[39][40] including "an entirely different [collective] organizing principle in olfaction" and "a new principle in which neural function can take advantage of the temporal structure of the 'spiking' interneural communication".[40]

He received the Albert Einstein World Award of Science in 2005 in the field of life sciences.[41] He was the President of the American Physical Society in 2006.[42] Hopfield received the IEEE Frank Rosenblatt Award in 2009 for his contributions in understanding information processing in biological systems.[43] In 2012 he was awarded the Swartz Prize by the Society for Neuroscience.[44] In 2019 he was awarded the Benjamin Franklin Medal in Physics by the Franklin Institute,[45] and in 2022 he shared the Boltzmann Medal award in statistical physics with Deepak Dhar.[46] In 2023, he was named a Highly Ranked Scholar by ScholarGPS for lifetime. [47]

He was jointly awarded the 2024 Nobel Prize in Physics with Geoffrey E. Hinton for "foundational discoveries and inventions that enable machine learning with artificial neural networks".[48][49]

Doctoral students

His former PhD students include Bertrand Halperin (PhD in 1965), Steven Girvin (1977), Terry Sejnowski (1978), Erik Winfree (1998), José Onuchic (1987) and David J. C. MacKay (1992).[50]

References

  1. ^ a b c d e f "Hopfield, John J." Physics History Network American Institute of Physics. Retrieved October 8, 2024.
  2. ^ "Press release: The Nobel Prize in Physics 2024". NobelPrize.org. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  3. ^ a b c d e Taylor, D.B.; et al. (October 8, 2024), "Nobel Physics Prize Awarded for Pioneering A.I. Research by 2 Scientists", The New York Times, archived from the original on October 8, 2024, retrieved October 8, 2024
  4. ^ a b c Lindsay, Grace (March 4, 2021). Models of the Mind: How Physics, Engineering and Mathematics Have Shaped Our Understanding of the Brain. Bloomsbury Publishing. ISBN 978-1-4729-6645-2. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  5. ^ "American Men of Science: A Biographical Directory". Science Press. 1966.
  6. ^ John Hopfield (1958). A Quantum-Mechanical Theory of the Contribution of Excitons to the Complex Dielectric Constant of Crystals. ISBN 979-8-6578-5817-4. OCLC 63226906. Wikidata Q130468423.
  7. ^ Orton, John W. (December 11, 2008). The Story of Semiconductors. OUP Oxford. ISBN 978-0-19-156544-1.
  8. ^ a b "American Physical Society Meets in Baltimore". Physics Today. 38 (3): 87–93. March 1, 1985. Bibcode:1985PhT....38c..87.. doi:10.1063/1.2814495. ISSN 0031-9228.
  9. ^ Office of Communications (October 8, 2024). "Princeton's John Hopfield receives Nobel Prize in physics". Princeton University. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  10. ^ "The Life and the Structure of Hemoglobin, American Institute of Physics". Orego State Documentary History of Linus Pauling. 1976. Retrieved October 9, 2024.
  11. ^ a b c Hey, Anthony (March 8, 2018). Feynman And Computation. CRC Press. ISBN 978-0-429-96900-3.
  12. ^ Hillis, W. Daniel (February 1, 1989). "Richard Feynman and the Connection Machine". Physics Today. 42 (2): 78–83. Bibcode:1989PhT....42b..78H. doi:10.1063/1.881196. ISSN 0031-9228.
  13. ^ "Caltech Celebrates 30 Years of its Computation and Neural Systems Option | Caltech Alumni". Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  14. ^ Hopfield, J. J. (December 1, 1958). "Theory of the Contribution of Excitons to the Complex Dielectric Constant of Crystals". Physical Review. 112 (5): 1555–1567. Bibcode:1958PhRv..112.1555H. doi:10.1103/PhysRev.112.1555. ISSN 0031-899X.
  15. ^ a b Agranovich, Vladimir M. (February 12, 2009). Excitations in Organic Solids. OUP Oxford. ISBN 978-0-19-155291-5. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  16. ^ Huttner, B.; Barnett, S. M. (1992). "Dispersion and Loss in a Hopfield Dielectric". Europhysics Letters. 18 (6): 487. Bibcode:1992EL.....18..487H. doi:10.1209/0295-5075/18/6/003. ISSN 0295-5075. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  17. ^ Zangwill, Andrew (January 8, 2021). A Mind Over Matter: Philip Anderson and the Physics of the Very Many. Oxford University Press. ISBN 978-0-19-264055-0.
  18. ^ Hopfield, J. J. (1974). "Kinetic Proofreading: A New Mechanism for Reducing Errors in Biosynthetic Processes Requiring High Specificity". Proceedings of the National Academy of Sciences. 71 (10): 4135–4139. Bibcode:1974PNAS...71.4135H. doi:10.1073/pnas.71.10.4135. ISSN 0027-8424. PMC 434344. PMID 4530290.
  19. ^ Flyvbjerg, Henrik; Jülicher, Frank; Ormos, Pal; David, Francois (July 1, 2003). Physics of Bio-Molecules and Cells: Les Houches Session LXXV, 2–27 July 2001. Springer Science & Business Media. ISBN 978-3-540-45701-5. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  20. ^ Hopfield, J J (April 1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences of the United States of America. 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554. ISSN 0027-8424. PMC 346238. PMID 6953413.
  21. ^ Hopfield, John J. (March 1, 2014). "Whatever Happened to Solid State Physics?". Annual Review of Condensed Matter Physics. 5 (1): 1–13. Bibcode:2014ARCMP...5....1H. doi:10.1146/annurev-conmatphys-031113-133924. ISSN 1947-5454.
  22. ^ Hopfield, J. J.; Tank, D. W. (July 1, 1985). ""Neural" computation of decisions in optimization problems". Biological Cybernetics. 52 (3): 141–152. doi:10.1007/BF00339943. ISSN 1432-0770. PMID 4027280. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  23. ^ Hopfield, John J.; Tank, David W. (August 8, 1986). "Computing with Neural Circuits: A Model". Science. 233 (4764): 625–633. Bibcode:1986Sci...233..625H. doi:10.1126/science.3755256. ISSN 0036-8075. PMID 3755256. Archived from the original on April 14, 2024. Retrieved October 8, 2024.
  24. ^ a b The Nobel Committee for Physics (October 8, 2024). "Scientifc Background to the Nobel Prize in Physics 2024" (PDF). The Royal Swedish Academy of Sciences. Archived (PDF) from the original on October 8, 2024. Retrieved October 8, 2024.
  25. ^ Krotov, Dmitry; Hopfield, John J. (2016). "Dense Associative Memory for Pattern Recognition". Advances in Neural Information Processing Systems. 29. Curran Associates, Inc. arXiv:1606.01164. Archived from the original on June 19, 2024. Retrieved October 8, 2024.
  26. ^ Kahana, Michael J.; Wagner, Anthony D. (2024). The Oxford Handbook of Human Memory, Two Volume Pack: Foundations and Applications. Oxford University Press. ISBN 978-0-19-774614-1.
  27. ^ Feathers, Todd (October 8, 2024). "Nobel Prize Goes to 'Godfathers of AI' Who Now Fear Their Work Is Growing Too Powerful". Gizmodo. Retrieved October 9, 2024.
  28. ^ "Pause Giant AI Experiments: An Open Letter". Future of Life Institute. Retrieved October 9, 2024.
  29. ^ "Nobel winner John Hopfield warns of 'catastrophe' if AI advances are not 'controlled'". Hindustan Times. October 9, 2024.
  30. ^ "Fellows Database | Alfred P. Sloan Foundation". sloan.org. Retrieved October 10, 2024.
  31. ^ "John J. Hopfield – John Simon Guggenheim Memorial Foundation…". Retrieved October 10, 2024.
  32. ^ "John J. Hopfield". www.nasonline.org. Archived from the original on March 24, 2019. Retrieved May 24, 2020.
  33. ^ "John Joseph Hopfield". American Academy of Arts & Sciences. October 12, 2023. Archived from the original on October 8, 2024. Retrieved May 24, 2020.
  34. ^ "APS Member History". search.amphilsoc.org. Archived from the original on October 18, 2023. Retrieved May 24, 2020.
  35. ^ "Honors and Award Winners". American Physical Society. Retrieved October 8, 2024.
  36. ^ "Biologist awarded $224,000 - tax free, no strings attached" (PDF). CalTech News. 17 (5): 6. October 5, 1983.
  37. ^ "Golden Plate Awardees of the American Academy of Achievement". www.achievement.org. American Academy of Achievement. Archived from the original on December 15, 2016. Retrieved June 26, 2020.
  38. ^ "Past Recipients - IEEE Computational Intelligence Society". cis.ieee.org. Retrieved October 10, 2024.
  39. ^ "Dirac Medallist 2001 | ICTP". www.ictp.it. Archived from the original on October 8, 2024. Retrieved October 20, 2023.
  40. ^ a b "Princeton Physicist Garners Dirac Medal". Physics Today. 54 (10): 85. October 1, 2001. Bibcode:2001PhT....54S..85.. doi:10.1063/1.1420565. ISSN 0031-9228. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  41. ^ "Albert Einstein World Award of Science 2005". Archived from the original on October 23, 2013. Retrieved August 13, 2013.
  42. ^ "John Hopfield, Array of Contemporary Physicists". Archived from the original on October 19, 2013. Retrieved October 19, 2013.
  43. ^ MacPherson, Kitta (May 8, 2009). "Hopfield wins IEEE's Rosenblatt Award". Princeton University. Retrieved October 10, 2024.
  44. ^ "Swartz Prize awarded to John Hopfield for contributions to computational neuroscience". Office of the Dean for Research. Retrieved October 10, 2024.
  45. ^ "John J. Hopfield Named Winner of 2019 Benjamin Franklin Medal in Physics - IAS News | Institute for Advanced Study". www.ias.edu. December 10, 2018. Retrieved October 9, 2024.
  46. ^ "STATPHYS28". statphys28.org. Archived from the original on April 14, 2024. Retrieved October 8, 2024.
  47. ^ ScholarGPS Profile: John J. Hopfield
  48. ^ "The Nobel Prize in Physics 2024". Nobel Media AB. Archived from the original on October 8, 2024. Retrieved October 8, 2024.
  49. ^ Nobel Prize (October 8, 2024). Announcement of the 2024 Nobel Prize in Physics. Archived from the original on October 8, 2024. Retrieved October 8, 2024 – via YouTube.
  50. ^ John Joseph Hopfield at the Mathematics Genealogy Project
Scholia has a profile for John Hopfield (Q391237).


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