led to the adoption of a variety of concepts and methods from statistical mechanics. The various proposals to use simulated annealing for inference were apparently independent. Ising models became considered to be a special case of Markov random fields, which find widespread application in linguistics, robotics, computer vision and artificial intelligence. See also Restricted Boltzmann machine Helmholtz machine Markov Random Field Ising Model Hopfield network Learning rule that uses conditional "local" information can be derived from the reversed form of , . References https://www.mis.mpg.de/preprints/2018/preprint2018_87.pdf Further reading Kothari P (2020): https://www.forbes.com/sites/tomtaulli/2020/02/02/coronavirus-can-ai-artificial-intelligence-make-a-difference/?sh=1eca51e55817 External links Scholarpedia article by Hinton about Boltzmann machines Talk at Google by Geoffrey Hinton Neural network architectures Machine