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Part 1 is titled Introduction and has 2 sub-headings, "Symbiosis" (part 1.1) and "Between 'Mechanically Extended Man' and 'Artificial Intelligence'" (part 1.2). Part 1.1 begins by showing a definition of the term symbiosis using the illustration of the relationship between two organisms, a fig-tree, and its pollinator, a type of fig-wasp.
Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), is a field of research within artificial intelligence (AI) that explores methods that provide humans with the ability of intellectual oversight over AI algorithms. [1] [2] The main focus is on the reasoning behind the decisions or predictions ...
A conversation with Eliza. ELIZA is an early natural language processing computer program developed from 1964 to 1967 [1] at MIT by Joseph Weizenbaum. [2] [3] Created to explore communication between humans and machines, ELIZA simulated conversation by using a pattern matching and substitution methodology that gave users an illusion of understanding on the part of the program, but had no ...
During the AI vs AI race on the morning before the AI vs human contest, the cars were reaching speeds of 200kph. And if it weren’t for the lack of helmets bobbing around the cockpit, they could ...
[4] Researchers in the United Kingdom had been exploring "machine intelligence" for up to ten years prior to the founding of the field of artificial intelligence research in 1956. [5] It was a common topic among the members of the Ratio Club, an informal group of British cybernetics and electronics researchers that included Alan Turing. Turing ...
The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner.
where is a training sample with target value . The inner product plus intercept w , x i + b {\displaystyle \langle w,x_{i}\rangle +b} is the prediction for that sample, and ε {\displaystyle \varepsilon } is a free parameter that serves as a threshold: all predictions have to be within an ε {\displaystyle \varepsilon } range of the true ...
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