Alan Kay, 2015: Power of Simplicity
Kenneth Friedman6 HN recommenders · recommended in 7 months, 2015–2025
talk · general · evergreen · 2015–2025 on HN
Alan Kay's 2015 talk on the power of simplicity, arguing that systems become simpler by building on more sophisticated fundamental building blocks and that big research horizons drove invention at Xerox PARC. It ranges across computing, tools and scaling soft…
HN repeatedly cites it as a thought-provoking talk on reducing software complexity and on the state of computing research.
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12 comments from Hacker News
Highly recommend his talk on the power of simplicity. This was one of those lightbulb moments for me when I was a younger programmer: ▶ this video
Completely unrelated: Alan Kay - the power of simplicity ▶ this video Easily over of the most thought provoking presentations I have seen recently.
In his "Power of Simplicity"[1] talk, Alan Kay had a great illustration of this specific phenomenon using astronomy: Before Johannes Kepler had the insight of describing the orbits of the planets with ellipsis, peoples were using the (conceptually simpler) circles which didn't completely match the observed movement of celestial body such as Mars, thus resulted in complicated circle-within-circles orbits to try to model reality. By introducing a more complex basic shape (ellipsis instead of circle) which happened to match the underlying reality more, the overall description of orbits got greatly simplified. It's a phenomenon I've seen a few time in my career so far: that while often there's complex code because there are actually complex hedge case to handle (essential complexity), sometime it's really because the data structure used to model the thing you're handling is slightly missing the mark, making things fit almost-but-not-quite, and many operation done around to handle data can be greatly simplified (if not avoided altogether) by changing the underlying data-structure. (Also, Alan Kay apparently did another talk called "Is it really complex, or did we just make it complicated"[2] that seems pertinent to the thread, though I haven't watch it yet) [1] ▶ this video [2] link
Not sure which generation you're in and which generation you'd (relatively) consider Alan Key in, but here is a much more principled approach to what the OP is trying to do: ▶ this video The TLDW is that Kay thinks we haven't discovered all the fundamental rules of computing, a la Maxwells Equations for physics. If you are able to figure these out, you can substantially cut down your accidental complexity. FWIW, my unscientific view is that achieving simplicity is really hard and doesn't scale people-wise. Instead of C99 without a bunch of stuff, I'd probably use Scheme to create very dense (lots of bespoke abstractions and idioms) but simple software. That approach works reasonably well, but try onboarding a new developer!
Bret Victor - Inventing on principle link Alan Kay - Power of Simplicity ▶ this video Steve Jobs - Marketing (unveiling Think Different) link Robert Cialdini - On Influence link Peter Thiel - On Zero to One (Notes on Starts Ups or How to Build the Future) link Naval Ravikant on Reading, Happiness, Systems for Decision Making, Habits, Honesty and More (Farnam Street podcast) link Josh Wolfe - On "This is who you are up against" podcast link Richard Feynman - Fun to Imagine link Paul Graham - Startup school (2008) link James Burke - Connections (BBC documentary) <No link> Jim Al-Khalili tells the story of the Atom (BBC) link Elon Musk's 2003 Stanford University Entrepreneurial Thought Leaders Lecture link Ken Robinson - Do schools kill creativity? link Paul Stamets on mycology, bioremediation and fungi- Joe Rogan Experience link
I've seen him give this great talk before, but IMO the delivery this time feels rushed and a bit disjointed. That said, the last few minutes summarize his powerful "Gretzky Game" idea so succinctly that they're worth the price of admission alone. I would recommend watching the last 18 seconds of this version (starting at link ), internalizing the Gretzky Game slide on the screen, backing it up and watching the fuller explanation in the preceding ~3 minutes (starting at 54:18, link ), and then finally watching a different, more expansive version of the talk like this one, given at Qualcomm: ▶ this video . Oddly specific advice, I know, but hopefully helpful to somebody.
I'm not Alan, but I saw one of his talks[1] about how they did invent all those things we're using now, which you are very much referring to. What he said was important was to have a big horizon, at least 10 years. Anything less would not do. Then envision what should be possible in that time. "It would be ridiculous if $X wasn't possible in $Y years" and then backtrack on what would technically be required to make that happen. Rinse repeat. He said that with good company support and a good team, you often found yourself delivering at half that time none the less (but again, you should never constrain yourself to that little, or else you will stress towards performing, instead of thinking properly about the problems needing to be solved). Alan: Hope I didn't butcher your message too much :) [1] I think it might be this one, but I honestly haven't checked. See it anyway. It's a good talk. ▶ this video
Yes. A relevant quote from Alan Kay in his talk “the power of simplicity”: > one of the things that's worked the best the last three, or four hundred years, is you get simplicity by finding a slightly more sophisticated building block to build your theories out of. its when you go for a simple building block that anybody understand through common sense, that is when you start screwing yourself right and left, because it just might not be able to ramify through the degrees of freedom and scaling you have to go through, and it's this inability to fix the building blocks that is one of the largest problems that computing has today in large organizations. people just won't do it ▶ this video
Xerox made a ROI of 20000% on the laser printer alone [1]. A better version lecture Alan did for Ycombinator startups [2] but doesn't focus on the return of investment. Xerox did shrink a bit since then. [1] ▶ this video [2] link
Do you think that software should be architected as autonomous agents for it to scale infinitely? I watched an Alan Kay video [1] some time back. In the video, he had an argument about how software systems cannot scale unless the basis is the most complex "computation" system that we know -- that system being our own biological system. [1]: ▶ this video
You’d probably like Bret Victor’s inventing on principle talk: link He demonstrates some good examples. I’m not quite sure it’s what you mean by visual, but it seems obviously valuable and tools that enabled some of what he shows would be really useful. I’m not sure why we don’t have these things - I think Alan Kay would say it’s because we stopped doing real research to improve what our tools can be. We’re just relying on old paradigms (I just watched this earlier today: ▶ this video )
On the other hand Alan Kay has made powerful arguments that systems can be made much simpler if only their building blocks were slightly less simple! It's a tough question. ▶ this video