So we all may know that this year's Physics Nobel was given to
And it has sparks a great deal of controversy. So let's understand what they have done? Do they really fall into physics Nobel?
To understand their work we have to go back to 1980's to understand the paper that inspires this Nobel.
Hopfield Network
A Hopfield network is a type of artificial neural network inspired by the human brain. It's designed to store and recall patterns.
Let me give you some simple analogies and examples for Hopfield Network:
Analogy: The Beach Sand
Imagine a beach with small holes scattered across the sand. Each hole represents a specific pattern or memory stored in the network. When you drop a marble onto the beach, it will roll down the slope of the sand until it settles into the nearest hole.
- Marble: This represents the input data or query to the network.
- Holes: These are the stored patterns or memories.
- Rolling Process: This simulates the network's process of finding the closest match to the input data. As the marble rolls, it's essentially exploring the energy landscape of the network, seeking the lowest energy state, which corresponds to the most similar stored pattern.
Algorithm:
D Marr. Simple memory: a theory for archicortex. Philos Trans R Soc Lond B Biol Sci, 262(841):23–81, July 1971.
Kaoru Nakano. Associatron-a model of associative memory. IEEE Transactions on Systems, Man, and Cybernetics, SMC-2(3):380–388, 1972. doi: 10.1109/TSMC.1972.4309133.
S.-I. Amari. Learning patterns and pattern sequences by self-organizing nets of threshold elements. IEEE Transactions on Computers, C-21(11):1197–1206, 1972. doi: 10.1109/T-C.1972.223477.
W.A. Little. The existence of persistent states in the brain. Mathematical Biosciences, 19(1):101–120, 1974. ISSN 0025-5564. doi: https://doi.org/10.1016/0025-5564(74)90031-5.
J. C. Stanley. Simulation studies of a temporal sequence memory model. Biological Cybernetics, 24(3):121–137, Sep 1976. ISSN 1432-0770. doi: 10.1007/BF00364115.
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