Joe Armstrong - Keynote: The Forgotten Ideas in Computer Science - Code BEAM SF 2018

Definitely! I also like "How we program multicores" [0], it made "iff you want the same guarantees Erlang gives you, you'll be in the same performance ballpark in any language, yes, C++ also" click for me. Joe could explain the basic ideas and where they came from so concise and humble [1], you can probably just binge watch this whole list, one other gem being "The forgotten ideas in computer science" [2]... [0] link [1] link [2] ▶ this video

This is so sad. RIP Joe. I'll miss him so much. Erlang is one of the most Perlis languages for me. I'm always a little bit cynical and think Erlang deserve more attention. Several months ago Joe post this tweet about a game company refused to tell other people they are using Erlang. link I just watched his great talk last year not long ago - The Forgotten Ideas in Computer Science: ▶ this video

I love any talk with Joe Armstrong or Alan Kay in it. Joe Armstrong - Keynote: The Forgotten Ideas in Computer Science - Code BEAM SF 2018 ▶ this video

Ted Nelson's Computers for Cynics probably doesn't contain technical information that's new to any of you, but Ted has a knack for reframing things in ways that make the arbitrariness of certain historical decisions clear: link On the subject of hypertext, The Web That Wasn't gives a nice history of the idea (for anybody who thinks it starts with TBL -- surprisingly many people!): link Another reframing-oriented talk is Clay Shirky's "It's not information overload, it's filter failure", which ultimately leads to Shirky suggesting the kinds of user-oriented filtering features that Mastodon has implemented: link At the intersection of neurology and information science, Peter Watts always has something interesting to say, and as a former marine biologist focusing on the nervous system of starfish, this is absolutely in his wheelhouse: link This one ("moving away from defensive programming") justified strong typing in a pretty clear way: link Dan Dennett is just as relevant as Doug Hofstadter when it comes to metacognition: link Forgotten Ideas in Computer Science starts slow, but if you don't have much of a historical background (like, if you're only vaguely aware of what happened in CS in the 70s), it's a laundry list of things you should look up and be aware of before you start your next project: ▶ this video Everybody should understand procedural generation: link Likewise, since AI is hyped up right now, we should all remind ourselves that IA is a thing too: link M

"[Read] everything from Ted Nelson" – Joe Armstrong Keynote: The Forgotten Ideas in Computer Science - Code BEAM SF 2018: ▶ this video

Devastating. I'd like to point out a recent tweet @joeerl shared [0][1] that contained things he felt were good wisdom but lost over time: -- Ideas that we forgot: 1. Flow based programming. 2. Pipes. 3. Linda Tuple Spaces. 4. Hypertext (=/= HTML). Computer Science 101: 1. Observational equivalence. 2. Isolation. 3. Composition. 4. Causality. 5. Physics. Two papers to read: 1. The Emperor's Old Clothes - ACM. 2. A Plea for Lean Software - Nikalus Wirth. Two videos to watch: 1. The Computer Revolution Hasn't Happened Yet - Alan Kay. 2. Computers for Cynics - Ted Nelson. Four old tools to learn: Emacs, Bash, Make, Shell. Three books to read: 1. Algorithms + Data Structure = Programs. 2. The Mythical Man Month. 3. How to Win Friends and Influence People. Correct a typo: ?? Learn git -> locate program that creates page -> locate typo -> correct -> send push [sic] request. !! Select text -> type in correction -> people see change. Two projects: 1. Link to content hash not a name (request content by sha256, immune to pepole in the middle). 2. Elastic Links (links should not break if you move an endpoint). -- Easily one of the best thinkers of his generation [2]. RIP. [0] link [1] ▶ this video [2] link

It seems like what Paul is describing, is the niche filled by libraries/frameworks. When you have a website to build, you reach for an existing web framework, because it has already done the bottom-up steps for you. The same could be said of choosing a language, OS, hardware, etc. Existing technologies allow for increased productivity, at the cost of it becoming increasingly difficult to understand the bigger picture. The 'bottom-up' part at this point, is choosing which Ruby/Java/Python/etc libraries to use. The productivity bar has been set high, leaving little time for bottom-up decision making or education. Hence MongoDB and the never-ending tales of mediocre solutions gaining adoption due to marketing hype. Curiously enough - academia isn't able to solve this problem well, because they're encouraged to produce 'novelty', rather than sit down and digest the mess we're in, to help clarify matters a little. They're in the same rat-race, of getting things done on a 6-12 month schedule. There's a quote that I really like - "Prolific programmers contribute to certain disaster." [0] Ah well :) [0] ▶ this video