John Hopfield
Template:Short description Template:For Template:Use mdy dates Template:Infobox scientist
John Joseph Hopfield (born July 15, 1933)<ref name="history.aip.org">{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> 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. Previous to its invention, research in artificial intelligence (AI) was in a decay period or AI winter, Hopfield's work revitalized large-scale interest in this field.<ref name="Nobel.Physics.2024" /><ref>Template:Crevier 1993</ref>
In 2024 Hopfield, along with Geoffrey Hinton, was awarded the Nobel Prize in Physics for "foundational discoveries and inventions that enable machine learning with artificial neural networks."<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref name="Nobel.Physics.2024">Template:Citation</ref> He has been awarded various major physics awards for his work in multidisciplinary fields including condensed matter physics, statistical physics and biophysics.
BiographyEdit
Early life and educationEdit
John Joseph Hopfield was born in 1933 in Chicago<ref name="history.aip.org" /> to physicists John Joseph Hopfield (born in Poland as Jan Józef Chmielewski) and Helen Hopfield (née Staff).<ref name="Lindsay-2021">Template:Cite book</ref><ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
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.<ref name="history.aip.org" /> His doctoral dissertation was titled "A quantum-mechanical theory of the contribution of excitons to the complex dielectric constant of crystals".<ref>Template:Cite Q</ref> His doctoral advisor was Albert Overhauser.<ref name="history.aip.org" />
CareerEdit
He spent two years in the theory group at Bell Laboratories working on optical properties of semiconductors working with David Gilbert Thomas<ref>Template:Cite book</ref> and later on a quantitative model to describe the cooperative behavior of hemoglobin in collaboration with Robert G. Shulman.<ref name="history.aip.org" /><ref name="Lindsay-2021" /><ref name=":1">Template:Cite journal</ref> Subsequently he became a faculty member at University of California, Berkeley (physics, 1961–1964),<ref name=Nobel.Physics.2024/> Princeton University (physics, 1964–1980),<ref name=Nobel.Physics.2024/> California Institute of Technology (Caltech, chemistry and biology, 1980–1997)<ref name=Nobel.Physics.2024/> and again at Princeton (1997–),<ref name=Nobel.Physics.2024/><ref name="history.aip.org"/> where he is the Howard A. Prior Professor of Molecular Biology, emeritus.<ref name=":2">{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
In 1976, he participated in a science short film on the structure of the hemoglobin, featuring Linus Pauling.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
From 1981 to 1983 Richard Feynman, Carver Mead and Hopfield gave a one-year course at Caltech called "The Physics of Computation".<ref name=":0">Template:Cite book</ref><ref>Template:Cite journal</ref> This collaboration inspired the Computation and Neural Systems PhD program at Caltech in 1986, co-founded by Hopfield.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref name=":0" />
His former PhD students include Gerald Mahan (PhD in 1964),<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> Bertrand Halperin (1965),<ref name=":3">Template:MathGenealogy</ref> Steven Girvin (1977),<ref name=":3" /> Terry Sejnowski (1978),<ref name=":3" /> Erik Winfree (1998),<ref name=":3" /> José Onuchic (1987),<ref name=":3" /> Li Zhaoping (1990)<ref>Template:Cite thesis</ref> and David J. C. MacKay (1992).<ref name=":3" />
WorkEdit
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.<ref>Template:Cite journal</ref><ref name="Agranovich-2009">Template:Cite book</ref> He wrote: "The polarization field 'particles' analogous to photons will be called 'polaritons'."<ref name="Agranovich-2009" /> His polariton model is sometimes known as the Hopfield dielectric.<ref>Template:Cite journal</ref>
From 1959 to 1963, Hopfield and David G. Thomas investigated the exciton structure of cadmium sulfide from its reflection spectra. Their experiments and theoretical models allowed to understand the optical spectroscopy of II-VI semiconductor compounds.<ref>Template:Cite journal</ref>
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.<ref>Template:Cite book</ref>
William C. Topp and Hopfield introduced the concept of norm-conserving pseudopotentials in 1973.<ref>Template:Cite journal</ref><ref>Template:Cite book</ref><ref>Template:Cite book</ref>
In 1974 he introduced a mechanism for error correction in biochemical reactions known as kinetic proofreading to explain the accuracy of DNA replication.<ref>Template:Cite journal</ref><ref>Template:Cite book</ref>
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'.<ref>Template:Cite journal</ref><ref name="Lindsay-2021" /> He extended his formalism to continuous activation functions in 1984.<ref>Template:Cite journal</ref> The 1982 and 1984 papers represent his two most cited works.<ref name=":2" /> Hopfield has said that the inspiration came from his knowledge of spin glasses from his collaborations with P. W. Anderson.<ref>Template:Cite journal</ref>
Together with David W. Tank, Hopfield developed a method in 1985–1986<ref>Template:Cite journal</ref><ref>Template:Cite journal</ref> 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.<ref name="The Nobel Committee for Physics-2024">Template:Cite journal</ref>
Hopfield is one of the pioneers of the critical brain hypothesis, he was the first to link neural networks with self-organized criticality in reference to the Olami–Feder–Christensen model for earthquakes in 1994.<ref>Template:Cite book</ref><ref>Template:Cite journal</ref> In 1995, Hopfield and Andreas V. Herz showed that avalanches in neural activity follow power law distribution associated to earthquakes.<ref>Template:Cite journal</ref><ref>Template:Cite journal</ref>
The original Hopfield networks had a limited memory, this problem was addressed by Hopfield and Dimitry Krotov in 2016.<ref name="The Nobel Committee for Physics-2024" /><ref>Template:Cite journal</ref> Large memory storage Hopfield networks are now known as modern Hopfield networks.<ref>Template:Cite book</ref>
Views on artificial intelligenceEdit
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.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
Upon being jointly awarded the 2024 Nobel Prize in Physics, 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".<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> In a followup press conference in Princeton University, Hopfield compared AI with discovery of nuclear fission, which led to nuclear weapons and nuclear power.<ref name="Nobel.Physics.2024" />
Awards and honorsEdit
Hopfield received a Sloan Research Fellowship<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> in 1962 and as his father, he received a Guggenheim Fellowship (1968).<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> Hopfield was elected as a member of the American Physical Society (APS) in 1969,<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> 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.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> He was the President of the APS in 2006.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
In 1969 Hopfield and David Gilbert Thomas were awarded the Oliver E. Buckley Prize of condensed matter physics by the APS "for their joint work combining theory and experiment which has advanced the understanding of the interaction of light with solids".<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
In 1983 he was awarded the MacArthur Foundational Prize by the MacArthur Fellows Program.<ref>Template:Cite journal</ref> In 1985, Hopfield received the Golden Plate Award of the American Academy of Achievement<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> and the Max Delbruck Prize in Biophysics by the APS.<ref name=":1" /> In 1988, he received the Michelson–Morley Award by Case Western Reserve University.<ref>Template:Cite journal</ref> Hopfield received the Neural Networks Pioneer Award in 1997 by the Institute of Electrical and Electronics Engineers (IEEE).<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
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"<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref name="Physics Today-2001">Template:Cite journal</ref> 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".<ref name="Physics Today-2001" />
Hopfield received the Harold Pender Award in 2002 for his accomplishments in computational neuroscience and neural engineering from the Moore School of Electrical Engineering, University of Pennsylvania.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> He received the Albert Einstein World Award of Science in 2005 in the field of life sciences.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> In 2007, he gave the Fritz London Memorial Lecture at Duke University, titled "How Do We Think So Fast? From Neurons to Brain Computation".<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> Hopfield received the IEEE Frank Rosenblatt Award in 2009 for his contributions in understanding information processing in biological systems.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> In 2012 he was awarded the Swartz Prize by the Society for Neuroscience.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> In 2019 he was awarded the Benjamin Franklin Medal in Physics by the Franklin Institute,<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref> and in 2022 he shared the Boltzmann Medal award in statistical physics with Deepak Dhar.<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref>
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".<ref>{{#invoke:citation/CS1|citation |CitationClass=web }}</ref><ref>Template:Cite AV media</ref><ref>Template:Cite journal</ref>
In 2025 he was awarded the Queen Elizabeth Prize for Engineering jointly with Yoshua Bengio, Bill Dally, Geoffrey E. Hinton, Yann LeCun, Jen-Hsun Huang and Fei-Fei Li for the development of modern machine learning.<ref>Queen Elizabeth Prize for Engineering 2025</ref>
ReferencesEdit
External linksEdit
- Homepage at Princeton Template:Webarchive
- User:John J. Hopfield – Scholarpedia
- Template:Cite journal. This review traces the trajectory of solid state physics through Hopfield's own experiences.
- {{#invoke:citation/CS1|citation
|CitationClass=web }} (Auto-biographical essay)
- P. Charbonneau, History of RSB Interview: John J. Hopfield, transcript of an oral history conducted 2020 by Patrick Charbonneau and Francesco Zamponi, History of RSB Project, CAPHÉS, École normale supérieure, Paris, 2020, 21 p. https://doi.org/11280/5fd45598
Template:Albert Einstein World Award of Science Laureates Template:Presidents of the American Physical Society Template:Nobel Prize in Physics Template:2024 Nobel Prize winners Template:Authority control