AI History and Basics: From Symbolism to Neural Networks

Abstract

This chapter introduces the basic concepts of Artificial Intelligence. A brief historical context is necessary to put into perspective what artificial intelligence is and what artificial intelligence is not, and where the most important developments, like symbolic artificial intelligence, machine learning, deep learning and artificial neural networks come from. Short explanations of convolutional neural networks, genetic adversarial networks and other important concepts are also presented. The chapter finishes with a revision of the literature on the most common terms that appear in the title and abstract of the entries of the National Library of Medicine and are mined through PubMed. The relative occurrence of the terms ‘Artificial intelligence’, ‘ChatGPT’, ‘Computer vision’, ‘Convolutional neural’, ‘Deep learning’, ‘Expert systems’, ‘Generative adversarial’, ‘Machine learning’ and ‘Natural language processing’ over the last three decades is presented graphically.