On the evolution of neural network

Abstract

The review considers a brief history of the creation of modern neural networks - language models and the emergence of networks capable of solving problems and supporting scientific activity. It is shown that the main drivers of the evolution of artificial intelligence, in addition to the ability to use knowledge from the Internet and large-scale communication-training with users - have become scaling processes. The features of the application of language models in a variety of human activities and in the communication of billions of people who are trying to solve their particular problems with the help of available models are discussed. Special networks began to actively develop, using many developed technologies for solving problems and forecasting. They returned to the formation of models in the form of computation graphs using numerical methods and continual description. Examples are given and approaches to modeling various dynamic systems in natural science and various fields of human activity are discussed.