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    Cover of Feynman lectures on computation

    Feynman lectures on computation

    Richard Phillips Feynman · 1996

    From 1983 to 1986, the legendary physicist and teacher Richard Feynman gave a course at Caltech called "Potentialities and Limitations of Computing Machines.". Although the lectures are over ten years old, most of the material is timeless and presents a "Feynmanesque" overview of many standard and some not-so-standard topics in computer science. These include compatibility, Turing machines (or as Feynman said, "Mr. Turing's machines"), information theory, Shannon's Theorem, reversible computation, the thermodynamics of computation, the quantum limits to computation, and the physics of VLSI devices. Taken together, these lectures represent a unique exploration of the fundamental limitations of digital computers. Feynman's philosophy of learning and discovery comes through strongly in these lectures. He constantly points out the benefits of playing around with concepts and working out solutions to problems on your own - before looking at the back of the book for the answers. As Feynman says in the lectures: "If you keep proving stuff that others have done, getting confidence, increasing the complexities of your solutions - for the fun of it - then one day you'll turn around and discover that nobody actually did that one! And that's the way to become a computer scientist."

    Computer ScienceProgramming
    Open LibraryAmazon
    Stats for nerds
    17recommend
    29mentions
    24people
    2008–2024years
    69% recommend28% neutral3% critical

    Mentions per year

    200820102012201420162018202020222024

    What Hacker News says

    1. fintlerJul 2024
      If you'd like something more technical, these two are fun (especially if you read them in order):

        • Feynman Lectures On Computation
        • QED: The Strange Theory of Light and Matter
      
      The first book is a nice way to get started with reversible computation and quantum computing.
      thread
    2. User23May 2022
      An enjoyable and approachable text with more detail on reversible computing and energy expenditure from the perspective of physics is the Feynman Lectures on Computation[1].

      [1] https://www.goodreads.com/book/show/17274.Feynman_Lectures_O...

      thread
    3. beefmanFeb 2022
      I learned programming and math mostly by self-driven exploration. But for computer science there was a book that hit at the right place and time: Feynman Lectures on Computation.

      It's bounced around between publishers over the years and is generally a pain to get. I have the 1996 edition[1] which is out of print. Then there's a 2002 edition[2] and a 2000 edition[3].

      [1] https://www.amazon.com/Feynman-Lectures-Computation-Richard-...

      [2] https://www.amazon.com/Feynman-Computation-Frontiers-Physics...

      [3] https://www.amazon.com/Feynman-Lectures-Computation-Frontier...

      thread
    4. guilhermeasgNov 2021
      The Feynman Lectures on Computation, Goedel's Proof, maybe Crafting Interpreters?

      I've been following the development of http://browser.engineering/ and it's so much fun to go through. Highly recommended!

      Mazes for Programmers is on my bookshelf. I've gone through the first few chapters coding along in Go and going on weird diversions. It's totally pointless, and I love it. There's also "The Ray Tracer Challenge" by the same author, which looks phenomenal.

      thread
    5. User23Feb 2021
      Same. I was introduced to the concept in the book Feynman Lectures on Computation. It's an excellent read. He was a brilliant man and it's fun seeing someone coming at computation from the physical direction.
      thread
    6. Anon84Oct 2019
      I'm going to go a bit against the grain here and suggest the

      Feynman Lectures on Computation: https://www.amazon.com/Feynman-Lectures-Computation-Frontier...

      In pure Feynman style he builds up a the theory of computation from first principles. YMMV but it really helped me put many of the ideas and concepts from my CS MS into context and find new ways in which they relate with each other.

      thread

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