Please repost the crap out of this until @elonmusk or @Gwynne_Shotwell replies to it: Grokipedia is dead. I'd like to rescue it, starting with scientific data, which is critical to intelligence (artificial or not) ... 1. LLMs have a GIGO problem. They ingest tons of wrong information and spew it out with certainty. 2. Peer-reviewed research is a disaster. It's a $10 billion industry with bad incentives and terrible results. Feynman would not be happy. 3. Far too many global crises are caused by fake, weaponized, political, and simply incompetent science. I believe the ONLY way to fix it is not with programming and training, but with an open, two-sided market mechanism where you make money if you're right and you lose money if you're wrong. It's not a prediction market, it's a validation market. This skin-in-the-game approach will produce the world's most accurate science data, and much more. It's better than community notes. It could become the basis for an entirely new media company that complements X.com. DM me and I'll send you my deck. Sincerely, David Siegel @chamath @bgurley @hthieblot @jefielding @larjo280 @naval @pmarca @Jason @paulg @bhorowitz @balajis @fredwilson @msuster @Jeff @hunchventures @jasonmendelson @sether @jeremysliew @VCMike @ChristopherA @jeffnolan @ryanhoover @hstebbings @garrytan @alexf @jaltman @jasonlk @jessicalessin @joshua @khoslaventures @nicole @petersuciu @BillAckman @saranormous @JeffDean @kristianfreeman @alexwg @daveblundin @PeterDiamandis @kcoleman @matthew_pines @shaunmmaguire @dwarkesh_sp @C_Angermayer @RichardSSutton @deedydas @ID_AA_Carmack

Welcome to #RobotKindergarten 👀 First day at school 🏫 First‑person view from robot 🤖 #TASHAN #Robotics #TactileSensing #PhysicalAI #EmbodiedAI

"The most intelligent inhabitants of that future world won't be men or monkeys. They'll be machines—the remote descendants of today's computers. Now the present-day electronic brains are complete morons, but this will not be true in another generation. They will start to think, and eventually they will completely outthink their makers. Is this depressing? I don't see why it should be. We superseded the Cro-Magnon and Neanderthal men, and we presume we're an improvement. I think we should regard it as a privilege to be stepping stones to higher things. I suspect that organic, or biological, evolution has about come to its end, and we're now at the beginning of inorganic, or mechanical, evolution, which will be thousands of times swifter." — Arthur C. Clark 1964

Beautiful and haunting prescience. Give it a read in full and sit with it for some time. "we find ourselves almost awestruck at the vast development of the mechanical world, at the gigantic strides with which it has advanced in comparison with the slow progress of the animal and vegetable kingdom. We shall fi nd it impossible to refrain from asking ourselves what the end of this mighty movement is to be. In what direction is it tending? What will be its upshot? To give a few imperfect hints towards a solution of these questions is the object of the present letter. We have used the words »mechanical life,« »the mechanical kingdom,« »the mechanical world« and so forth, and we have done so advisedly, for as the vegetable kingdom was slowly developed from the mineral, and as in like manner the animal supervened upon the vegetable, so now in these last few ages an entirely new kingdom has sprung up, of which we as yet have only seen what will one day be considered the antediluvian prototypes of the race." "We refer to the question: What sort of creature man’s next successor in the supremacy of the earth is likely to be. We have often heard this debated; but it appears to us that we are ourselves creating our own successors; we are daily adding to the beauty and delicacy of their physical organisation; we are daily giving them greater power and supplying by all sorts of ingenious contrivances that self-regulating, self-acting power which will be to them what intellect has been to the human race."

Fantastic initiative my dream came true (see my article here paoloai.substack.com/p/stop-…) Now I just have to move to China!

At #WAIC2026, Turing Award winner Prof. @RichardSSutton shared his thoughts on #RobotKindergarten, our joint project with Openmind — a place where robots can learn through trial and error. Robot Kindergarten opens in Beijing this September. 🚀 #TASHAN #EmbodiedAI #TactileSensing

Today we release my favorite episode of Training Data yet: the great Rich Sutton. @RichardSSutton wrote the textbook, wrote The Bitter Lesson (and many other on-point essays like "Self-Verification, The Key to AI"), and trained a mafia of talented students who went on to change the AI landscape forever including David Silver, inventor of built AlphaGo. @kjaved_ was Rich's PhD student at Alberta and wrote The Big World Hypothesis. They just left academia to start @oaklab_ai Their core argument: (1) The Bitter Lesson: the world is massively more complex than any model of it, so anything trained on human-curated data has a ceiling (2) Continual Learning: intelligence is continual by definition, and today's models stop learning the moment they ship. The conversation covers: — what The Bitter Lesson actually says, and what people get wrong — why synthetic data is "just a big mistake," and the Big World Hypothesis behind it — how LLMs are both a positive and a negative example of his own essay — why no animal learns by supervised learning, and what squirrels can do that we can't — the cure for catastrophic forgetting: per-weight step sizes and continual backprop — why the biggest labs can't take a path where performance gets worse before it gets better — a trillion parameters on 20 watts, and the Moore's Law math that makes it plausible — why the endpoint isn't one mind but one design, running as many minds It was both a fun generative idea- and debate-filled conversation, and a surprisingly human one too. Rich, thank you for beating cancer and changing the trajectory of AI. 💙 00:00 Introduction 02:10 An AI winter, a cancer diagnosis, and the move to Alberta 07:07 Writing "The Bitter Lesson," and what people get wrong 09:53 Are LLMs a positive or a negative example of it? 11:03 Synthetic data is "just a big mistake," and the Big World Hypothesis 18:01 AlphaGo, human priors, and why prior knowledge and learning should be friends 22:37 "Their weights never change": do LLM assistants actually learn? 26:09 Babies, squirrels, and why no animal learns by supervised learning 32:02 Rockets, imagination, and where paradigm shifts come from 36:42 The Alberta Plan and its 12 steps 38:53 Catastrophic forgetting and the cure 43:43 Oak's biggest ambition: a self-maintaining mind 47:56 Why the big labs are stuck in a local minimum 49:13 If everything goes right: LLMs, many minds, and hiring The man who pioneered reinforcement learning thinks the rest of the field is weird, and lays it all out in today's episode. Together w/ @Alfred_Lin @sequoia

Full episode: piped.video/watch?v=xH7U7w9Q…

The biggest engineering mistake I made at Figure was building a tendon-based hand Our first hand design in 2022 was a tendon hand for our F.01 robot. At a high level, the tendon approach sounds appealing, which is why I chose it: you get more space for packaging actuators since the forearm is larger, potentially higher degrees of freedom, and it's biologically inspired We built and manufactured this entire hand and tested it in early 2023. If you saw it in person, it was truly an engineering work of art. It turned out to be one of the worst engineering decisions I've made, maybe the worst in four years. Tendons are a complete local maximum, and that only becomes clear in hindsight, after exploring every other possible hand design. Figure is unique in that we've now built and tested several hand architectures, which gave us a clear sense of where to head Figure is working on our next generation hand, and it's so much better than anything you can do with tendons, it's not even funny

Free Palestine.

I can’t say enough good things about John Carmack @ID_AA_Carmack and his Keen Technologies. But now Khurram Javed @kjaved_ and I have broken away to start our own startup and pursue a slightly different path toward understanding intelligence. Like Keen (and like Ineffable) we at Oak Lab @oaklab_ai believe in reinforcement learning and that intelligence is created and maintained from run-time experience. But we think current deep learning methods are weak and inefficient, and need not more tweaks, but fundamentally new ideas and a thorough reworking before they can provide a solid foundation for achieving the more ambitious goals of AI.

I can’t say enough good things about John Carmack @ID_AA_Carmack and his Keen Technologies. But now Khurram Javed @kjaved_ and I have broken away to start our own startup and pursue a slightly different path toward understanding intelligence. Like Keen (and like Ineffable) we at Oak Lab @oaklab_ai believe in reinforcement learning and that intelligence is created and maintained from run-time experience. But we think current deep learning methods are weak and inefficient, and need not more tweaks, but fundamentally new ideas and a thorough reworking before they can provide a solid foundation for achieving the more ambitious goals of AI.