"We Really Don't Know How to Compute!" - Gerald Sussman (2011)
Why Hacker News recommends it
HN commenters recommend it as a mind-expanding talk on rethinking programming, and cite it in threads on propagators, constraints and brittleness.
What it is
Gerald Sussman's 2011 Strange Loop keynote argues we still do not know how to compute, comparing biological systems with how we program machines. It touches on propagators, constraint programming and robustness.
Recommended by 5 HN commenters across 5 different months, 2022 to 2026.
What Hacker News said
Recommends pfarrell · 2022-11 · on “Fred Brooks has died”
Not writing, but I have found all of Brett Victor's speeches to be incredibly inspiring on how I think about what I want to work on and where we're going. Inventing on Principle by Brett Victor: [LINK] Growing a Language by Guy Steele: [LINK] We Really Don't Know How to Compute! by Gerald Sussman: [this video]
Recommends pvillano · 2023-02 · on “The program is the database is the interface”
you might be interested in [this video] "We Really Don't Know How to Compute!"- Gerald Sussman (2011) [1:04:18]
Recommends throwaway71271 · 2023-09 · on “Programming Is Hard”
For some reason programming is not getting any easier, I can even make an argument its getting worse despite all the improved tooling and andragogy investments we have done. Programming is in some sort of local minimum and we keep going in circles. Few years ago I watched this talk by Gerald Sussman: "We really don't know how to compute" - [this video] and it made me question my views on what I think programming is. I dont know if its because people are afraid to try new things, or there is no funding to try new things, we are kind of stuck. People thinking "don't reinvent the wheel" and for some reason think we have built a wheel (as Casey Muratori says: [LINK] ). We have a square at best. There
Recommends teleforce · 2025-04 · on “Prof. Sussman's Reading List (2016)”
I highly recommend Prof. Sussman talk at the Strange Loop conference 2011 [1]. It's not his inaugural lecture but it's pretty close where he talk about his research work with his former students. It's also paved the way to modern constraint programming based on logic and optimization which are the machine intelligence that's complementary to the conventional data driven and learning bases AI. [1] "We Really Don't Know How to Compute!" - Gerald Sussman - MIT (2011) [video]: [this video]
Recommends gobdovan · 2026-06 · on “My Software North Star”
Grandparent is onto something. You can't define correctness without a spec. And since most business-oriented software, which most of us work with, isn't made against a comprehensive spec, you can argue that anything falling outside it is either a bug or a feature. 'If your disk backup software corrupts backups' has behind it a clean definition that's (pretty) unambiguous and you don't care about, since it's already outsourced to some cloud solution. But 'User finds it easy to buy more stuff' does not. Also, mandatory Sussman reference [0], where he talks about correctness not being that important and gives Google as example, that just needs to be close enough and not disastrously incorrect +
Cites Mathnerd314 · 2022-05 · on “Thinking in an array language”
I think he says that in every talk he gives. [this video] , [LINK] , [LINK] , etc. There's a 2002 paper where he uses the term: [LINK]
Cites ryukafalz · 2022-06 · on “Permacomputing Wiki”
This also reminds me of Gerry Sussman’s talk “We Really Don’t Know How to Compute!”: [this video] Granted, the assumption he made is that computing power would grow increasingly cheap (which is basically the opposite of the point here), but I also wonder if techniques like those shown in that talk could be used effectively with a network of smaller, lower-power computers. (I mean, the talk does mention the use of small low-power computers specifically, but more in the context of e.g. sensor networks.)
Cites crdrost · 2022-11 · on “Lisp-stick on a Python”
Oh what a fun question! So, the first thing is, what's the essential difficulty versus the noise: Lisp has two features which enable the evaluator to work. The first is quotation, which means that you can put a little apostrophe before some code and then it saves that code as a data structure, rather than implicitly evaluating it. The second goes by the overfancy name “homoiconicity”, that data structure is actually just singly linked list consumed by “car” (“first”) and “cdr” (“rest”) operations. You can focus on understanding those two aspects pretty quickly, and then there are many tutorials about building your own Lisp that will get you there in an afternoon, if you'd like. Or, you can t