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THE VIDEO SHELF · history of computer science

Computer Science - A Guide for the Perplexed • Joe Armstrong • GOTO 2018

Joe Armstrong's GOTO 2018 talk contrasts the problems computer scientists study with the problems users have. He revisits forgotten great ideas such as tuple spaces, flow-based programming, Xanadu and Unix pipes, with anecdotes.

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Why HN readers recommended it

HN calls it a superb, funny and engaging talk, and links it often after Armstrong's death as one of his best.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
GOTO Conferences
Topic
history of computer science
Format
talk
Level
intermediate
HN recommenders in dataset
3
HN mentions in dataset
4
Recommendation years in dataset
2019–2021

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • This is devastating, RIP. I watched this talk a few months ago [VIDEO] called "Computer Science - A Guide for the Perplexed" It was superb, I think it's unfortunate that he had to rush through it because of time constraints, his anecdotes and delivery were …

    djhworld on Hacker News · 2019-04
    In Joe Armstrong has died

  • One of my favorite talks by Joe Armstrong -- computer science, a guide for the perplexed. He talks through what he feels are some important but forgotten ideas in CS [VIDEO]

    vector_spaces on Hacker News · 2021-01
    In Let's Not Dumb Down the History of Computer Science (2014)

  • That is so sad, he was in his late 60s and it seemed like he had a lot of life left in him, talking about how software can get better and having a great (and sometimes snarky) outlook on the profession. Highly recommend his thesis …

    dpeck on Hacker News · 2019-04
    In Joe Armstrong has died

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.