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AIMA gives detailed information about the working of algorithms in AI. The book's chapters span from classical AI topics like searching algorithms and first-order logic, propositional logic and probabilistic reasoning to advanced topics such as multi-agent systems, constraint satisfaction problems, optimization problems, artificial neural networks, deep learning, reinforcement learning, and ...
The book received positive reviews from critics, who singled out its exploration of issues like exploitation of labour and the environment, algorithmic bias, and false claims about AI's ability to recognize human emotion. [1] [2] The book was considered a seminal work by Anais Resseguier of Ethics and AI. [3]
Artificial Intelligence: A Guide for Thinking Humans is a 2019 nonfiction book by Santa Fe Institute professor Melanie Mitchell. [1] The book provides an overview of artificial intelligence (AI) technology, and argues that people tend to overestimate the abilities of artificial intelligence.
'AI winter' caused by pessimism about machine learning effectiveness. 1980s: Rediscovery of backpropagation causes a resurgence in machine learning research. 1990s: Work on Machine learning shifts from a knowledge-driven approach to a data-driven approach.
The history of artificial intelligence (AI) began in antiquity, with myths, stories, and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The study of logic and formal reasoning from antiquity to the present led directly to the invention of the programmable digital computer in the 1940s, a machine ...
Throughout the book, it is suggested that each different tribe has the potential to contribute to a unifying "master algorithm". Towards the end of the book the author pictures a "master algorithm " in the near future, where machine learning algorithms asymptotically grow to a perfect understanding of how the world and people in it work. [ 1 ]
This book is considered by some to mark the beginning of the AI winter of the 1970s, a failure of confidence and funding for AI. However, by the time the book came out, methods for training multilayer perceptrons by deep learning were already known ( Alexey Ivakhnenko and Valentin Lapa, 1965; Shun'ichi Amari , 1967). [ 9 ]
Human Compatible: Artificial Intelligence and the Problem of Control is a 2019 non-fiction book by computer scientist Stuart J. Russell. It asserts that the risk to humanity from advanced artificial intelligence (AI) is a serious concern despite the uncertainty surrounding future progress in AI.