A new approach to the development of artificial intelligence similar to human intelligence

Abstract

The article discusses a new approach to the creation of artificial neurons and neural networks as a means of developing artificial intelligence similar to natural. Based on the consideration and analysis of the works of physiologists on the structure and functions of a biological neuron, it was found that the information perceived by a person is stored in the neurons of the brain at the molecular level, it also suggested that the nucleus and endoplasmic reticulum are elements of processing, transformation and storage of temporary and long temporary memory. In addition, it was suggested that the nerve cell of the brain is molecular, using signals or information represented by a continuously variable physical quantity, a supercomputer, that performs the analysis, synthesis, processing and storage of information. Huge amounts of information perceived by a person from the moment of his birth and throughout his life are stored in the endoplasmic reticulum of the neuron. There are about 100 billion neurons in the human brain, and each neuron contains millions of membrane-bound ribosomes that biosynthesize and modify protein molecules that are transferred to the secretory vesicles. When one synaptic vesicle is emptied, a portion of the mediator is ejected into the synaptic cleft, including about 10,000 molecules. If we assume that one molecule corresponds to one unit of information, then human memory is unlimited. A detailed consideration of the fundamentals of the functioning of a biological neuron from the standpoint of a cybernetic system approach led to the understanding that it is necessary to develop an artificial neuron of a new type. This made it possible to develop the most approximate analog of a biological neuron - a neural-like element and a neural-like growing network. A description of the neural-like element is given. The process of perception and memorization of information in a neural-like element with the simultaneous formation of a neural-like growing network and their application in models of intelligent systems is shown.