Stephen Wolfram: Cellular Automata, Computation, and Physics | Lex Fridman Podcast #89
Why Hacker News recommends it
HN points to it as an accessible long-form introduction to Wolfram's ideas and a window into his passion, though some are critical of his claims.
What it is
Lex Fridman interviews Stephen Wolfram for about three hours on cellular automata, computation, the Wolfram Physics Project and his career with Mathematica and Wolfram Alpha.
Recommended by 4 HN commenters across 4 different months, 2020 to 2023.
What Hacker News said
Strong rec Pilottwave · 2022-04 · on “We’ve got a science opportunity overload: Launching the Wolfram Institute”
Lots of comments about his "arrogance" but i just see someone passionate, judge for yourself! He has three long interviews on Lex Fridmans youtube channel! I greatly enjoyed watching those those. 1:[Stephen Wolfram: Cellular Automata, Computation, and Physics]( [this video] ) 2:[Stephen Wolfram: Fundamental Theory of Physics, Life, and the Universe]( [LINK] ) 3: [Stephen Wolfram: Complexity and the Fabric of Reality ]( [LINK] )
Recommends __s · 2020-06 · on “Odds of communicating with 36 other possible intelligent civilizations are small”
Random math doesn't imply intelligence: [LINK] is that shell intelligent? Wolfram has an alright interview where he considers this: [this video] My own thoughts: intelligence is something which you need to observe predicting the future, ie something proactively reacting to the future in order to achieve a goal. This means ideally you have a bit of interaction so that you can see that you're interacting with is capable of learning in response to you
Recommends erikig · 2021-11 · on “Ask HN: Whatever happened to Wolfram Alpha?”
I still use it regularly too - even more so after listening to Stephen Wolfram’s 3 part podcast [1] with Lex Fridman where he discussed the latest developments in Wolfram, Mathematica etc [1] [this video]
Recommends SuoDuanDao · 2022-11 · on “What You (Want to)* Want”
Regarding reading suggestions, you'd probably like Wolfram's cellular Automata theory. accessible intro: [this video]
Cites DonHopkins · 2022-11 · on “Ask HN: What weird technical scene are you fond/part of?”
That's one of my long time interests and hobbies, which I write about on HN and discuss with other people frequently. I'm supposed to be doing something else right now so I'll quickly drop a few disorganized quotes and links here. (Sorry I didn't have time to be more concise!) A few years ago I ran across Max Bittker's beautiful "Sandspiel", which is a delightful cellular automata toy that simulates sand and other rules: [LINK] A few days ago I saw him tweet some amazing stuff that resonated with me, which then led me to discover what he's been working with Lu Wilson (TodePond): Sandspiel Studio -- user definable rules using a block based visual programming language. [LINK] "working on goth
Cites DonHopkins · 2023-01 · on “Making Sandspiel”
I am a huge fan of Sandspiel, which Max described in this article from 2019, and recently I was delighted to discover that he and TodePond have been doing a huge amount of wonderful work since then. What happens when you combine Sandspiel with a Scratch-like blocks based visual programming language that lets you look inside and see how rules work, tweak and modify them, and even define your own rules for different types of particles? And then form a community around it for sharing Here is Max's and TodePond's brilliantly ambitious visually programmable sequel, Sandspiel Studio! [LINK] Here's my profile, where you can play with the version of Max's flower growing rule that he shows here: [LIN
Critical rubber_duck · 2020-06 · on “An understanding of AI’s limitations is starting to sink in”
I recently watched a podcast with Stephen Wolfram (few months old) where he runs a photo of himself through Wolfram Alpha "ImageIdentify" and it classifies him as a plunger with 50% probability and 8% probability it's a human [1]. He then goes on saying how he's working on systems that would allow a self driving system decide what to do based on if the collision detected is a human or inanimate object, etc. This was just one particularly ironic example of what I'm seeing with ML - we saw this level of accuracy in classification years ago - where is the enormous progress ? There have been pockets where ML shows it's applicable with encouraging initial results but after that it seems to me tha