Tags
Language
Tags
May 2025
Su Mo Tu We Th Fr Sa
27 28 29 30 1 2 3
4 5 6 7 8 9 10
11 12 13 14 15 16 17
18 19 20 21 22 23 24
25 26 27 28 29 30 31
    Attention❗ To save your time, in order to download anything on this site, you must be registered 👉 HERE. If you do not have a registration yet, it is better to do it right away. ✌

    ( • )( • ) ( ͡⚆ ͜ʖ ͡⚆ ) (‿ˠ‿)
    SpicyMags.xyz

    Feynman Lectures on Computation: Anniversary Edition (Frontiers in Physics), 2nd Edition

    Posted By: yoyoloit
    Feynman Lectures on Computation: Anniversary Edition (Frontiers in Physics), 2nd Edition

    Feynman Lectures on Computation: Anniversary Edition
    by Richard P. Feynman

    English | 2023 | ISBN: 1032415886 | 426 pages | True PDF | 52.52 MB


    The last lecture course that Nobel Prize winner Richard P. Feynman gave

    to students at Caltech from 1983 to 1986 was not on physics but on computer

    science. The first edition of the Feynman Lectures on Computation, published

    in 1996, provided an overview of standard and not-so-standard topics in

    computer science given in Feynman’s inimitable style. Although now

    over 20 years old, most of the material is still relevant and interesting, and

    Feynman’s unique philosophy of learning and discovery shines through.

    For this new edition, Tony Hey has updated the lectures with an invited

    chapter from Professor John Preskill on “Quantum Computing 40 Years

    Later”. This contribution captures the progress made toward building a

    quantum computer since Feynman’s original suggestions in 1981. The last

    25 years have also seen the “Moore’s law” roadmap for the IT industry

    coming to an end. To reflect this transition, John Shalf, Senior Scientist

    at Lawrence Berkeley National Laboratory, has contributed a chapter

    on “The Future of Computing beyond Moore’s Law”. The final update

    for this edition is an attempt to capture Feynman’s interest in artificial

    intelligence and artificial neural networks. Eric Mjolsness, now a Professor

    of Computer Science at the University of California Irvine, was a Teaching

    Assistant for Feynman’s original lecture course and his research interests

    are now the application of artificial intelligence and machine learning

    for multi-scale science. He has contributed a chapter called “Feynman

    on Artificial Intelligence and Machine Learning” that captures the early

    discussions with Feynman and also looks toward future developments.

    This exciting and important work provides key reading for students and

    scholars in the fields of computer science and computational physics.

    For more quality books vist My Blog.