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Richard Feynman Computer Science Lecture - Hardware, Software and Heuristics
54K subscribers • 1 video on Hallway
- Recommended by 12 people: 8 on Hacker News, 1 on Lobsters and 3 in engineering communities.
- A classic. People kept recommending it from 2012 to 2026.
- Presented by Richard Feynman, physicist
Beginner. No background in the topic needed.
978K views14 years ago12 recommendations
Computer scienceHistory and cultureCPUs and computer architectureAlgorithmsHistory of computing
Richard Feynman explains the fundamentals of how computers process data, using the analogy of a filing clerk to demystify hardware and heuristics.
Donate and Support this Channel: paypal.com/donate/?cmd=_s-xclick&hosted_button_id=BLJ283JMTM… Introduction Article to Heuristics and Metaheuristics: muonray.blogspot.ie/2016/04/meta-heuristics-and-universal-po… Richard Feynman, Winner of the 1965 Nobel Prize in Physics, gives us an insightful lecture about computer heuristics: how computers work, how they file information, how they handle data, how they use their information in allocated processing in a finite amount of time to solve problems and how they actually compute values of interest to human beings. These topics are essential in the study of what processes reduce the amount of work done in solving a particular problem in computers, giving them speeds of solving problems that can outmatch humans in certain fields but which have not yet reached the complexity of human driven intelligence. The question if human thought is a series of fixed processes that could be, in principle, imitated by a computer is a major theme of this lecture and, in Feynman's trademark style of teaching, gives us clear and yet very powerful answers for this field which has gone on to consume so much of our lives today. No doubt this lecture will be of crucial interest to anyone who has ever wondered about the process of human or machine thinking and if a synthesis between the two can be made without violating logic.Why it's here
12 people recommend thisWhat people say. Recommended as a classic, highly accessible explanation of computer fundamentals and heuristics using simple analogies.
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