
Metastable
3.3K posts

Metastable
@metastable_1
Experiencing vertigo while standing on the precipice.


Llama3(1) 405b (basemodel) really has leaked already. Here you can download it: 764GiB (~820GB) HF link: huggingface.co/cloud-district… Magnet: magnet:?xt=urn:btih:c0e342ae5677582f92c52d8019cc32e1f86f1d83&dn=miqu-2&tr=udp%3A%2F%2Ftracker.openbittorrent.com%3A80 Torrent: files.catbox.moe/d88djr.torrent Credits: #p101516633" target="_blank" rel="nofollow noopener">boards.4chan.org/g/thread/10151…


Mark Zuckerberg was reportedly building a $100M Hawaii compound with a huge underground bunker 👀


This result points to something larger: AI systems are becoming capable of holding together long, difficult chains of reasoning, connecting ideas across distant fields, and surfacing paths researchers may not have explored. We believe those same abilities will soon accelerate work in biology, physics, engineering, and medicine. That future still depends on human judgment. Expertise becomes more valuable, not less. AI can help search, suggest, and verify. People choose the problems that matter, interpret the results, and decide what questions to pursue next.

"post-AGI, no one is going to work and the economy is going to collapse" "i am switching to polyphasic sleep because GPT-5.5 in codex is so good that i can't afford to be sleeping for such long stretches and miss out on working"

working towards AGI while not feeling the AGI is the real risk

This is a general-purpose LLM. It wasn’t targeted at this problem or even at mathematics. Also, it’s not a scaffold. We have not pushed this model to the limit on open problems. Our focus is to get it out quickly so that everyone can use it for themselves.

Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 years, mathematicians believed the best possible solutions looked roughly like square grids. An OpenAI model has now disproved that belief, discovering an entirely new family of constructions that performs better. This marks the first time AI has autonomously solved a prominent open problem central to a field of mathematics.


Okay, it was obvious that LLMs struggle with numbers because of the tokenizer—how did I miss that image generators structure with *letters* because of the tokenizer? Obvious in hindsight but I did not have an explanation for the “dalle can’t spell” phenomenon until just now



Kamala Harris is now calling for Democrats to hold a “No Bad Idea Brainstorm” where they discuss: - Abolishing the Electoral College - Packing the Supreme Court - Making Puerto Rico and D.C. states “We’ve got to neutralize these red states from cheating!”

"post-AGI, no one is going to work and the economy is going to collapse" "i am switching to polyphasic sleep because GPT-5.5 in codex is so good that i can't afford to be sleeping for such long stretches and miss out on working"

Aw, shit, didn't remember saying that at all. Was speaking ex tempore and trying to visualize a finished surviving world that had come into existence, not thinking through or endorsing a policy for getting there from here. I wish I had not visualized or spoke of that particular finished state, don't endorse it as a policy goal for today's world, and at the time I spoke was hopeless about any such policy being possible, nor trying to compose feasible optimized policy proposals, because I hadn't yet observed the reception of the Bankless podcast. I agree this is easier to misunderstand, wasn't good to say, and I recant and apologize for that phrasing and example given the serious policy proposal I later made.





Everyone in the world has to take a private vote by pressing a red or blue button. If more than 50% of people press the blue button, everyone survives. If less than 50% of people press the blue button, only people who pressed the red button survive. Which button would you press?

Exactly what I thought, they are using years old models that are known to be miles worse than the models we are using today. Don't be fooled by this outdated bs. The models were: Gemini (2.0, Google; version available December 2024 DeepSeek (V3, High-Flyer; version available December 2024) Meta AI (Llama 3.3, Meta; version available December 2024) ChatGPT (3.5, OpenAI; version available November 2022) Grok (2, xAI; version available August 2024)



In January 2025, we committed to generating 10GW of compute and have already identified over 8GW of that. Now, we're planning for 30GW of compute by 2030. A milestone that scales with the rapidly accelerating demand for intelligent systems. Image generated by @ChatGPTapp Images 2.0 😉 #YouCanJustBuildThings

Intel is proud to join the Terafab project with @SpaceX, @xAI, and @Tesla to help refactor silicon fab technology. Our ability to design, fabricate, and package ultra-high-performance chips at scale will help accelerate Terafab’s aim to produce 1 TW/year of compute to power future advances in AI and robotics. It was fun hosting @elonmusk at Intel this past weekend!













