Turing anticipated all major arguments coming in the

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Turing anticipated all major arguments coming in the next 65 years! He suggested major components of AI! NLU - Natural Language understanding KR – Knowledge reasoning AR – Automated reasoning ML – Machine Learning “Total Turing test” also adds: Computer vision Robotics Turing test
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8/3/2018 4 Cleverbot Eliza Loebner Prize (The Turing test has not been passed) The Turing Test – Chatbots • Links: Cleverbot Eliza Loebner Prize • Mitsuku The Turing Test – Chatbots What can the Turing test determine?... And arguments and questions that follow from it. Horn Map 1 : Can computers think? Map 2 : Can the Turing test determine whether computers can think? Map 3 : Can physical symbol systems think? Map 4 : Can Chinese Rooms think? Map 5a : Can connectionist networks think? Map 5b : Can computers think in images? Map 6 : Do computers have to be conscious to think? Map 7 : Are thinking computers mathematically possible? Artificial Intelligence Debate Maps
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8/3/2018 5 Searle: Consciousness in AI (Dec 2015) - Video Start - Chinese room: 11:20 – 20:36 - 22:05 38:30 - Terminology (start) in his video Epistemic – related to knowledge Ontologic – related to being, existence, reality Objective vs. subjective Observer dependent vs. Observer independent Chinese room. Searle. Consciousness in AI Paper by McCulloch and Pitts (1943) Model of Artificial Neurons. Turing (1950), Computing Machinery and Intelligence Conference at Dartmouth (1956) McCarthy J, Minsky M, Shannon C, Nathaniel, Samuel (IBM), Solomonoff, Newell and Simon. Labs: Carnegie Mellon (Newell, Simon), Stanford (McCarthy), MIT (Minsky) Edinburgh (Turing, Michie) Fathers of AI Founding statement. The project lasted a month, and it was essentially an extended brainstorming session. The introduction states: We propose that a 2 month, 10 man study of artificial intelligence be carried out during the summer of 1956 at Dartmouth College in Hanover, New Hampshire. The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer. (McCarthy et al. 1955) Dartmouth conference, 1956 1930 1940 1950 1960 1970 1980 1990 2000 neuro- hardware Minsky/Papert book power of representation Gödel Turing first-order logic LISP GPS PROLOG Jaynes probabilistic reasoning numeric C4.5 Zadeh fuzzy logic propositional logic Davis/Putnam
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