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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. [2] [3]
Book cover of the 1979 paperback edition. Hubert Dreyfus was a critic of artificial intelligence research. In a series of papers and books, including Alchemy and AI, What Computers Can't Do (1972; 1979; 1992) and Mind over Machine, he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field.
The book was released on June 25, 2024. Kurzweil reiterates two key dates from his previous book, which predicted that artificial intelligence (AI) would reach human intelligence by 2029 and that people would merge with machines by 2045, an event he calls "The Singularity." [1] [2] [3] [4]
Nearly 200,000 books written by a wide range of authors, including Nora Roberts, are being used to train artificial intelligence systems, according to a recent report. No one asked for the writers ...
Ford predicted in his 2009 book that "artificial intelligence will be the next Killer App" [2] and would become a central focus of Silicon Valley. By 2016, major firms like Google, Microsoft, Facebook and Apple were in an intense talent war [ 3 ] for AI experts, and Google's CEO had proclaimed that artificial intelligence represented an ...
The Singularity Is Near: When Humans Transcend Biology is a 2005 non-fiction book about artificial intelligence and the future of humanity by inventor and futurist Ray Kurzweil. A sequel book, The Singularity Is Nearer, was released on June 25, 2024. [1]
Instead, Gates has predicted AI will make the world a more equitable place, where “machines can make all the food” and we only have to work three days a week. This story was originally ...
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 ...