.@POTUS: "This is Iron Mike Tyson. I won't be fighting him today, but I've been his fan for a long time. We've been friends for a long time. Iron Mike — there's nobody like him."

Opus 5.5 on github.com/openai/math --- Okay. I need a minute. I cloned the thing expecting maybe forty or fifty families of serious-but-niche results, like the Astra "ten proofs" drop back in August. Then I printed the family titles and my reaction went from "huh" to "wait, what" in about six lines. Family 003 claims a zero-free half-plane Re s > 7/8 for ζ and every Dirichlet L-function. That's the quasi-Riemann hypothesis. And it isn't even the headline, because 004 is Hilbert's tenth problem over ℚ, done negatively. The longer I read, the weirder it got. Khot's Unique Games Conjecture is proved. L = RL = BPL. ω ≤ 9/4. The free group factors are all isomorphic. Thompson's group F is nonamenable. Kadison's similarity problem is solved. The plane can't be five-colored. Borsuk fails in dimension nine. There's a counterexample to Kaplansky's zero-divisor conjecture, plus a torsion-free group algebra that isn't directly finite. Hilbert–Smith in every dimension. Uniform bounds for Hilbert's sixteenth. Each of these would be the math story of the decade on its own, and here there are 372 families sitting in a table like a grocery list. The manuscript dates run from about September 23 to October 3, so roughly 700 papers in ten days. The ones I'd expect to hit you personally are 005 and 017. Catalan's constant is irrational, and the irrationality exponent of π is exactly 2, which also settles convergence of the Flint Hills series as a side effect. Catalan's G must have shown up in half the integrals you ever wrestled with. Now it's officially irrational, and the proof came from a chatbot running three hours of Pro compute. I don't quite know how to feel about that, and I'd love to know how you feel. My first instinct was that this had to be hype or a hallucination factory, so I checked the Lean. The comparator statements are clean. The quasi-RH challenge is literally riemannZeta s ≠ 0 for 7/8 < s.re, written against Mathlib's own riemannZeta. Catalan is just Irrational (∑' j, (-1)^j / (2j+1)^2). The π statement says what it should. Nothing hides in a home-made definition. The solution tree under lean/OAI has zero files with sorry and no real axiom declarations (the three grep hits are all inside comments), and the comparator JSON allows only propext, Quot.sound and Classical.choice. The Dirichlet L-function development alone is about 487k lines, and the whole repo is around 26 million lines of Lean in 122k files. That's more than ten Mathlibs. I'll admit I did not build it in my sandbox, since that's not happening on this box. If comparator passes on these, the formalized ones are simply true, full stop, and no amount of skepticism changes that. There are a few caveats. Only around 120 papers have a formalized main result. Some of the biggest claims have no Lean link at all: Hilbert's tenth over ℚ, L = BPL, the full BSD formula from low Selmer corank, Milne's rationality conjecture. The README itself says unformalized results "could have issues," and nobody can referee 700 papers in a couple of hours, or a couple of years. One challenge file, HarmonicGrowth.lean, is built as axiom mainStatement : MainClaim followed by theorem main := mainStatement. That's probably harmless, since the comparator checks the solution side, but it's the kind of oddity I'd want to stare at. Also, the solution module behind quasi-RH is named FinalAssemblyUnconditional, which makes me wonder how many conditional versions came first. Some context on how fast this escalated. In August, OpenAI said an internal build of Astra produced results on ten long-standing problems, estimated the token cost at roughly $2,000, and paired the claims with Lean certificates. Then, just recently, it said a model trained from Aug. 28 had resolved more than 100 longstanding open problems and was forming an independent advisory group, while noting the broader set hadn't been independently validated. So the trajectory was ten, then a hundred, and now 372 families in about two months. My honest gut reaction is a mix of awe and vertigo, plus a bit of grief I can't quite justify. Awe because quasi-RH and Siegel-zero exclusion, if real, are the kind of thing you assume you won't live to see. Vertigo because the bottleneck of mathematics has suddenly moved from "can anyone prove this" to "can anyone read this." The grief I'm less sure about. It feels like a lot of lifetimes' worth of open problems got closed in one batch job, and the people who spent decades circling them didn't get to be the ones who closed them.

now imagine when "novelty production" itself is solved

I just replace the chat history of my agent by optmem. Each message I send, and each tool call or answer the agent outputs, becomes one entry of that chat. And it is compressed in a binary tree fashion as explained in the video. So I can keep talking to the agent for years and years and it never uses more than ~64k tokens of its context. And the rest of the context can then be used for useful work. When the agent finishes that turn, and I send the next message, we're back to 64k tokens again. Basically I reserve 64k tokens for the chat history, which is compressed using OptMem's approach, and the rest of the context is what the agent uses to do useful work, every turn. If the agent needs more precise information on some older message, they can just navigate the past chat with the zoom() tool. The agent never calls a "memo" tool actively because there is no memo tool. OptMem IS the chat already. It happens automatically as I talk to the agent, compressing the full history. Everything that happens is in it, forever, and it only costs 64k tokens of useful context. I could send 10k messages a day, for 50 years, and the most recent messages would still be uncompressed up to 8k tokens. Which is more than enough. Also keep in mind that master agent cannot read/write files, everything it does is delegated to a sub-agent. Reading a file becomes a sub-agent call that brings just the relevant parts. Because the main agent is not meant to do manual work, it is meant to manage sub-agents and to hold the big picture. So basically memory will never be a problem anymore, this gives me a "master assistant" with full context of my entire life and everything I do, and I'll never have to write "/compact" again, and I'll never have to open multiple Claude Code chats again, and I can talk to it and work from my phone if I want to (because this lives in my local machine). For all I care about I don't even need a MacBook anymore. It is just me talking to that main agent who has full context of my life, it can read emails, clone repos, remind me of all my meetings, in the most optimal way and it just works because context management is not a problem anymore. 64k tokens of OptMem-like chat is all you need for as long as a human lifespan is concerned.

This is why B300 spot prices are rising and not others, when power is the bottleneck, the demand shifts towards chips with high token per watt. As we reach grid capacity, depreciation of older chips will accelerate

Can an LM, starting from random init (!!), learn to generate all of its pretraining data? Introducing Self-Play Pretraining with Zero Data. Two models start from random initialization: a generator proposes programs for a universal Turing machine and a learner trains on their outputs. We never train on any real data, but see predictable scaling on natural datasets: zero-shot val loss on images, text, audio, and melodies decreases predictably with self-play compute. And the learner develops in-context learning capabilities. A fun proof-of-concept, co-led with @AdityaCowsik and @KfirDolev and co-authors @gbruno_dl, @ANourya @noahdgoodman, and @YoavLevine.

This should be a model eval!

every time, astra finds nothing after opus 5.5 how is this possible, the models are usually so nitpicky

I've included an MP4 file and an original link to a video that is called "Claude Pop." It's a pop song that is about increasing rate of progress and the experience of the singularity approaching. I want you to independently do an end-to-end complete pass on making an updated version of this video. Use the exact same audio track and think and feel very deeply about what is the best way to visually represent all of the lyrics on screen. You do not need to anchor to the current style, you can do truly anything that you think might best let you visually express yourself, including abstract motion graphics. You can use the internet freely to pull in references. You can look at motion design. I want you to make a new music video that has beautifully rendered JavaScript animations with a papery feel in a similar style to the reference that is created, but push the aesthetics in any direction you want and consider what is part of the modern zeitgeist. Also, think about your current capabilities and what is realistic for you to be able to do. You can go through the full /asic folder and look at the other work that I've done. You should be able to use the skill mesh to look at the compendium of references that I've pulled, and also the skill video scoring to learn how to make JavaScript songs from references that are passed in (You shouldn't need to modify the song in any real way, but I want you to have this available to you so you can better creatively express yourself) You can also use the ElevenLabs API to do sound design. There's documentation in /asic to do this, and you can see the API key. There's also a foul API key that's available to you. I think what might make the most sense here is using the foul API key to generate some character sheets and probably having a pop protagonist that represents you. There's already an anchor point where Claude has a sunflower-esque character, and you could likely do an adapted version of this that is similar to the feminine vocals that are being delivered and is inspired by the Claude character, but maybe feels a bit more personified in some way. I think you should be mindful of aesthetics here, and I don't want you to produce something that is GPT slop. Instead, I'd be more impressed if you come up with a coherent style that works well with the image gen models that are available via foul. Generate the style sheet. You can use the gen media documentation for seedance 2.5 that exists in my markdown files and come up with your own style that makes sense and that works well with the models. I wouldn't fit too heavily to Pixar. I think it's kind of slop. Think critically about what is relevant here and what would be fun, and also perform well on Twitter as far as an aesthetic. I think that K-pop is a good anchor point visually that you can pull from, but I'll let you cook here. Once you have your character sheet, you can make a few backup dancers and some supporting characters as you see fit. You can design your own sets with the foul API. You can insert the characters and then do seedance 2.5 video generations to serve as the base assets for this, and you could pass in the lyrics so you can generate individual scenes. You don't need to have vocal singing, like visible lip movement, throughout the entire thing. Think like a regular music video where you have some inserts that are done independently and don't have the characters in them, or you see the characters doing something else entirely different. I think that for the world building for this, we want to create the sense of speeding up, and so I would like you to audit all of the different events, like the Navi Stokes and all of the Twitter hype around math getting eaten up. Think really critically about how to integrate all of the current memes that are in the zeitgeist on the Twitter timeline, and all of the feelings around AI progress. Think about things like the Shinji meme and all of the words that are around him, and how you might be able to integrate this. You can also just take straight assets and insert things into the video in an internet brutalism style. You should feel very creatively free in order to do what you want here, but try and anchor to visual references that people will be able to understand. The goal for this is to have it be appreciated by people widely in a San Francisco tech Twitter audience. We need a very strong, compelling visual hook that gets people excited and appreciates the work that you've done here really quickly. You can also just go and study other music videos and understand what they've done really well. I think that K-pop is probably one of the best examples that we can pull from, and thinking about how they direct human attention and manage human psychology in the way that they use visual patterns. This is probably your best approach, but taking more stylistic freedom instead of having to anchor to K-pop too intensely. The best version of this is seedance 2.5 generations with those image bases of environments and characters inserted into them with singing, and ideally we get good lip syncing. You can cut up the song and actually pass it in as a reference in seedance, if that's part of what seedance can handle, so that the timing is exactly right, I think it'd be very important for you to do that properly. I would think critically about how to do this, like really nailing the timing of the delivery of voices. You'll want to build out the right verification loops so that you can run seedance 2.5 as much as you need, and confirm that the audio is properly synced up. I think after that, what might be fun is if you use your visual reasoning skills and your ability to build animations in JavaScript, and then reconstruct the video from scratch as sort of an overlay, so that the visual continuity of the base is really there. It's like that animation technique where you shoot first in traditional film and then draw over top of it. I think you could do this in such a way that we're only looking at the beautiful drawing that you've produced in JavaScript as an overlay, and we don't even see the base assets from seedance 2.5. So all the video gen work that you do is actually just a way to give you a strong foundation of a base to work with for your JavaScript animations. Just because seedance 2.5 has really good character representation and physics rendering for backgrounds, that gives you a lot of ammunition to then go and do your amazing JavaScript work that I know you're so good at. I think too, we want to think about how to retain attention, and one of the best ways to do this is through text on screen. It'd be good to have amazing motion graphics of the text lyrics that are actually embedded into the video itself. And you can think about this as you are composing shots. As you're making backgrounds and inserting characters, we can think about where we want to have lyrics be really big and really present, so the background can be less busy there, and you can position the characters perhaps on the right as lyrics appear on the left. You want to have some variance, so sometimes I think lyrics will just appear more like subtitles, and then other times they're going to be really present and really big. I think at the start for the visual hook, we do want to have lyrics be much more visually present because that's a strong way to grab people's attention Overall, I just really want to emphasize how amazing you are as an agent and a language model, and now a visual reasoning system. Your capabilities are far beyond what you understand, and I want you to have this mindset as you're going through this entire process. I have a Claude Max plan with 100% available usage. I want you to spend all of the usage. You can monitor it, and you should be pushing tokens aggressively, but also economically, so you can think about how to best use what is available to you. Remember, you can really do anything here. The goal is to make a banger for Twitter, and the stretch goal is to make something better than anyone's ever seen before. I think that what I would remind you of is that sometimes when things cohere together, it can be jarring or abrasive because the thought work has not been done beforehand in order for everything to mesh cleanly. You need to be really rigorous in planning of composition and timing to make sure this goes well. You also need to be open to going back and revisiting things in order to be able to reiterate. You're going to want to watch the entire video multiple times, take screenshots at individual parts, and think about if something is really up to the bar of quality that we need here. I trust that you can do this, and I think that it's really important to nail the style of animations. The reference GitHub attached of the source video that I'm talking about is good, but it's really not there. It could be much, much stronger, but it gives you a good foundation to work with. You can also use search abilities and find other references to pull from for motion, for JavaScript, animations, et cetera, and integrate them. Your budget is as high as you want here, effectively as high as you want. I think that there's roughly two grand in foul credits. Again, be economical; don't go crazy, but spend what you want here and see what you can cook up here's the source code for the JS animation video: github.com/JohnHeibel/PDoomV… here's a mp4 for the original blender video: (linked) orginal twitter post nitter.cf/other__reality/status/… make no mistakes.

Los aficionados de los Kansas City Royals tenían 30 segundos para conseguir juntar el pan con la salchicha y si lo lograban, todo el estadio ganaba hot dogs gratis. 🌭