A Brain-Inspired Algorithm For Memory
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My name is Artem, I'm a neuroscience PhD student at Harvard University.
🌎 Website and Social links: https://kirsanov.ai/
📥 "Receptive Field" neuro-newsletter: https://artemkirsanov.substack.com/
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In this video we will explore the concept of Hopfield networks – a foundational model of associative memory that underlies many important ideas in neuroscience and machine learning, such as Boltzmann machines and Dense associative memory.
🕒 OUTLINE:
00:00 Introduction
02:17 Protein folding paradox
04:23 Energy definition
08:25 Hopfield network architecture
14:03 Inference
18:40 Learning
22:48 Limitations & Perspective
24:43 Shortform
25:54 Outro
📚 FURTHER READING & REFERENCES:
1) Downing, K.L., 2023. Gradient expectations: structure, origins, and synthesis of predictive neural networks. The MIT Press, Cambridge, Massachusetts.
2) https://towardsdatascience.com/hopfie...
3) https://ml-jku.github.io/hopfield-lay...
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Special thanks to Crimson Ghoul for providing English subtitles!
Credits:
Protein folding: • protein folding
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Disclaimer: This channel is my personal project. The views and content expressed here are my own and are separate from my research role at Harvard University.
#HopfieldNetwork #Neuroscience #MachineLearning
Description remastered: February 2026. Links & Bio updated; original context preserved.