BCAM SMRNN Seminar | Reading group on John Hopfield's 1982 paper and colloquium on the 2024 physics Nobel Prize

We are excited to announce a reading group and colloquium to explore the science behind the 2024 Nobel Prize in Physics. In particular, we will focus on the groundbreaking contributions of John Hopfield in his 1982 seminal paper on associative neural networks [1].

The seminar will feature a reading group dedicated to discussing the paper:

• Hopfield, 1982. Neural Networks and Physical Systems with Emergent Collective Computational Abilities https://doi.org/10.1073/pnas.79.8.2554

This paper marked a major milestone in neural network research, modelling neurons to interact like the spin dynamics in physical systems, such as magnetic materials. Building on pioneering work by Nakano and Amari [2,3], Hopfield shows how network training, as well as processes like memory retrieval and error correction, can be understood in terms of the energy landscape of the system. With this work, Hopfield demonstrated that emergent collective phenomena in large networks of neurons could give rise to computational abilities. 

The model gained further momentum when physicists like Daniel Amit extended its theoretical understanding by using spin glass theory to analytically derive properties such as memory storage capacity [4]. Moreover, Hopfield’s model has found significant connections to modern machine learning frameworks [5], including cutting-edge architectures like transformers [6].

We will conclude the reading session with a brief colloquium on the historical significance of this year's Nobel Prize and the ongoing impact of Hopfield and others' work in fields such as artificial intelligence, complex systems, and neuroscience.

References:

[1] J.J. Hopfield, Proc. Natl. Acad. Sci. USA 79, 2554 (1982).
[2] K. Nakano, IEEE Trans., Syst., Man, Cybern. SMC-2, 380 (1972).
[3] S.-I. Amari, IEEE Trans. Comput. C-21, 1197 (1972).
[4] D. J. Amit, H. Gutfreund and H. Sompolinsky, Phys. Rev. A 32, 1007 (1985).
[5] D.H. Ackley, G.E. Hinton and T.J. Sejnowski, Cogn. Sci. 9, 147 (1985).
[6] D. Krotov, D. A new frontier for Hopfield networks. Nat. Rev. Phys., 5(7), 366-367 (2023).