Artificial intelligence, machine learning, deep learning and generative artificial intelligence

Abstract

The terms ‘artificial intelligence (AI)’, ‘machine learning (ML)’, ‘deep learning’ and ‘generative AI (Gen AI)’ are introduced. Their specific domains and usage areas are mentioned. Different types of ML, namely, supervised, unsupervised, semisupervised and reinforcement learning are defined. Amongst artificial neural networks, the perceptron, multilayer perceptron, liquid state machine, feed-forward, recurrent, long short-term memory, convolutional, modular, radial basis function, residual and generative adversarial neural networks are briefly touched upon. Procedures and applications of AI computing are examined. AI focused processor design considerations are pointed out. The state-of-the-art scenario of AI processors is sketched by discussion of salient features of a few of the vast variety of AI chips in the market or new chip announcements. Aims, scope and organization of the book are laid out. The contents of the different chapters are summarized.

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