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    Ideas That Created the FutureLewis, Harry

    Ideas That Created the Future

    Lewis, Harry · 2021

    Classic papers by thinkers ranging from from Aristotle and Leibniz to Norbert Wiener and Gordon Moore that chart the evolution of computer science. Ideas That Created the Future collects forty-six classic papers in computer science that map the evolution of the field. It covers all aspects of computer science: theory and practice, architectures and algorithms, and logic and software systems, with an emphasis on the period of 1936-1980 but also including important early work. Offering papers by thinkers ranging from Aristotle and Leibniz to Alan Turing and Nobert Wiener, the book documents the discoveries and inventions that created today's digital world. Each paper is accompanied by a brief essay by Harry Lewis, the volume's editor, offering historical and intellectual context.

    MathematicsComputer Science
    Open LibraryAmazon
    Stats for nerds
    9recommend
    17mentions
    14people
    2021–2026years
    71% recommend29% neutral

    Mentions per year

    202120222023202420252026

    What Hacker News says

    1. jlduggerJan 2025
      If this is up your alley, Ideas That Created the Future[1] has like 40 more, decent introductions to their ideas, and provides a sort of thematic throughline from Aristotle to the modern computer science.

      [1]: https://mitpress.mit.edu/9780262045308/ideas-that-created-th...

      thread
    2. turingbookJan 2025
      See also the book or the course by Harry R. Lewis at Harvard:

      - Ideas That Created the Future https://www.amazon.com/Ideas-That-Created-Future-Computer/dp...

      - "Classics of CS" https://canvas.harvard.edu/courses/34992/assignments/syllabu...

      thread
    3. syndicatedjellyJun 2024
      Check out Harry Lewis’s “Ideas that Created the Future”
      thread
    4. syndicatedjellyJun 2024
      Ideas that Created the Future by Harry Lewis has been a great read, I highly recommend it. It is a book full of the most influential papers for the field of computer science, according to the author. The author is a professor of computer science. He does a great job placing each paper in context and history, as well as explaining any dated concepts that modern developers aren't necessarily familiar with.
      thread
    5. jlduggerAug 2023
      For just getting started I recommend collections:

      1. Ideas That Created The Future[1]. It's a collection of fiftyish classic CS papers, with some commentary.

      2. Wikipedia's list[2].

      3. Test of Time awards[3]. These are papers that have been around for a while and people still think are important.

      4. Best paper awards[4]. Less useful than ToT as not every best paper is actually that good or important, and sometimes the award committees can't see past names or brands for novel research.

      5. Survey Journals[5]. Students often get their research started with a literature review and some go the extra step to collect dozens of papers into a summary paper. I subscribe to the RSS feed for that one, and usually one or two are interesting enough to read.

      6. Citation mining -- As you read all these, consider their citation list as potential new reading material, or if an old paper leaves you wanting more, use Google Scholar to find a papers that cited what you just read.

      [1]: https://www.amazon.com/Ideas-That-Created-Future-Computer/dp...

      [2]: https://en.wikipedia.org/wiki/List_of_important_publications...

      [3]: https://www.usenix.org/conferences/test-of-time-awards

      [4]: https://jeffhuang.com/best_paper_awards/

      [5]: https://dl.acm.org/journal/csur

      thread
    6. jlduggerJul 2023
      Oh, and one book I rather enjoyed was Ideas That Created the Future, which is not exactly a textbook (but is probably used by the author as such) so much as a survey on the history of computer science via primary sources. Each source has a 1-2 page summary providing context, but the meat is reading the original papers on computer design, Complexity Theory, various papers on logic and proofs and proofs of software properties, theorem provers, NP completeness, neural networks, etc.

      One thing I learned is that the idea of a computational neural network predates actual working general purpose computers by a few years, and is actually cited in the construction of computers as an inspiration.

      https://direct.mit.edu/books/edited-volume/5003/Ideas-That-C...

      thread

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