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Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
Life 3.0: Being Human in the Age of Artificial Intelligence [1] is a 2017 non-fiction book by Swedish-American cosmologist Max Tegmark. Life 3.0 discusses artificial intelligence (AI) and its impact on the future of life on Earth and beyond. The book discusses a variety of societal implications, what can be done to maximize the chances of a ...
The problem of attaining human-level competency at "commonsense knowledge" tasks is considered to probably be "AI complete" (that is, solving it would require the ability to synthesize a fully human-level intelligence), [4] [5] although some oppose this notion and believe compassionate intelligence is also required for human-level AI. [6]
The Samuel Checkers-playing Program (1959) was among the world's first successful self-learning programs, and as such a very early demonstration of the fundamental concept of artificial intelligence (AI). [28] Stockfish AI, an open source chess engine currently ranked the highest in many computer chess rankings. [29]
A decade later, with AI more prevalent than ever, Professor Bostrom has decided to explore what will happen if things go right; if AI is beneficial and succeeds in improving our lives without ...
Many of the early approaches to knowledge represention in Artificial Intelligence (AI) used graph representations and semantic networks, similar to knowledge graphs today. In such approaches, problem solving was a form of graph traversal [2] or path-finding, as in the A* search algorithm. Typical applications included robot plan-formation and ...
Artificial intelligence utilises massive amounts of data to help with predicting illness, prevention, and diagnosis, as well as patient monitoring. In obstetrics, artificial intelligence is utilized in magnetic resonance imaging, ultrasound, and foetal cardiotocography. AI contributes in the resolution of a variety of obstetrical diagnostic issues.
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 ...
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