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A Boltzmann machine, like a Sherrington–Kirkpatrick model, is a network of units with a total "energy" (Hamiltonian) defined for the overall network. Its units produce binary results. Boltzmann machine weights are stochastic. The global energy in a Boltzmann machine is identical in form to that of Hopfield networks and Ising models:
Geoffrey Everest Hinton (born 6 December 1947) is a British-Canadian computer scientist, cognitive scientist, cognitive psychologist, and Nobel Prize winner in Physics, known for his work on artificial neural networks which earned him the title as the "Godfather of AI". Hinton is University Professor Emeritus at the University of Toronto.
Diagram of a restricted Boltzmann machine with three visible units and four hidden units (no bias units) A restricted Boltzmann machine (RBM) (also called a restricted Sherrington–Kirkpatrick model with external field or restricted stochastic Ising–Lenz–Little model) is a generative stochastic artificial neural network that can learn a probability distribution over its set of inputs.
Geoffrey Hinton invented a method [the Boltzmann machine] that can autonomously find properties in data, and so perform tasks such as identifying specific elements in pictures.”
It's the first time that a Nobel Prize has been awarded to the field of AI.
Geoffrey Hinton and John J. Hopfield have been awarded the 2024 Nobel Prize in physics. The pair won for their inventions that enable machine learning with artificial neural networks.
During 1985–1995, inspired by statistical mechanics, several architectures and methods were developed by Terry Sejnowski, Peter Dayan, Geoffrey Hinton, etc., including the Boltzmann machine, [146] restricted Boltzmann machine, [147] Helmholtz machine, [148] and the wake-sleep algorithm. [149]
Geoffrey Hinton is known for his work developing artificial neural networks, the foundation for AI, and won the 2024 Nobel Prize in physics in October.