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How good are VLMs at geological reasoning? Can we teach to reason where no labels can be established / training examples are hard to create?
We create a stratigraphic diagram exam environment and train VLMs on it. - then show they seem to transfer to seismic domain.
only about 2 million/employee better than my employer ;-)
My quick takeaways on the Anthropic S-1:
1. This is a historical moment
2. $6.6M in revenue per employee!! Hard to even comprehend how good that is but Anthropic is AI native as it gets so makes sense.
3. I always thought OpenAI would drop their S-1 first
4. Customers spend about 9x more after a year. Net Revenue Retention is approximately 900% as of Sep 30, 2026. Good SaaS companies brag about 120%.
5. Cowork is growing faster than Claude Code did. Goes to show you the demand for consumer products. Duo will probably rip.
6. 3 years ago this company did $41M in revenue. In the first six months of 2026, it did $16.3 billion. I don't think anyone has a mental model for that curve yet, I sure don’t.
7. Nearly half of revenue comes through cloud marketplaces. About 48% comes from customers buying through them. Big companies buy where their budget already lives, and the lesson for founders selling to enterprises is to get listed where your buyers already spend.
8. Their run rate formula is published: the last 28 days of usage times 13, plus subscriptions times 12, which i guess is the new ARR math for founders?
9. It looks like They're merging Cowork into Claude dot au which tells you the chat box era is ending and the "go do the work for me" era is here.
10. Thousands of Anthropic employees are about to become liquid at once, so expect the biggest wave of new AI startups and angel checks San Francisco has ever seen. Reminds me when Facebook went public but this is way bigger.
Let’s go!
11. Buried in the filing, Anthropic says the gap between what Claude can do and how widely it's used is one of its biggest growth opportunities, so the company itself is telling you the models are ahead of the market and someone has to close that gap for dentists, landlords, and plumbers.
12. Whatever happens, exciting times to be building in AI.
Are there any good examples of “I can monetise this like so”?
Damn that’s a nice suit
Replying to @dieworkwear
This style is a favorite of Douglas Cordeaux's, co-owner and director of Fox Brothers, makers of some of the best woolen flannel.
Claude what other classical computer vision approach can we apply to tokens?
I've long believed hierarchical representations are one of the most promising paths forward for vision problem. QuadTok is our first step: a tokenizer for adaptive image representation and generation.
Paper: arxiv.org/abs/2610.10497
Code: github.com/myc634/QuadTok
Details below.
My dots will save me so much time so I can do more instagram reels. (Personal assistants for everyone are peak silicon valley bubble imo)
Yesterday I got a bit roasted on X because I said my agent checks me in for my flights, so let me double down: it also helps me book basically every plane ticket.
I just landed in India and they asked for one of those crazy health/immigration forms with passport info, where you’re staying, flight details, etc. I sent it to my agent, it filled everything out, great job, I went back to reading my book.
A bunch of people replied: “I’m a competent adult, I know how to do this, I don’t need AI.”
Which is totally fair. Do whatever works for you!
I also know how to wash dishes and I love my dishwasher. I know how to write a letter, put it in an envelope and go to the post office, and yet I prefer email. I know how to do mental arithmetic and I still use a calculator.
The point of technology is very rarely that humans are incapable of doing the thing. It’s that our time and attention are better spent somewhere else.
Instead of spending 20 minutes fighting with a PDF, finding my passport number, hotel address and flight information in five different places, I can read my book. Instead of manually replying to three emails just to send my landlord some insurance information, an agent can handle it and I get another 20 minutes with my 18-month-old daughter, Josephine.
I think people underestimate AI agents for two reasons.
First, capitalism has this amazing tendency to take things that were once reserved for rich people and, through technology and scale, give them to everyone. Rich people have had executive assistants forever. Someone books their flights and restaurants, coordinates meetings, answers routine communications, fills out paperwork, reminds them what they forgot. AI is going to give some version of that to billions of people.
Second, a huge amount of economic progress is simply removing friction. Coase would call a lot of this transaction costs. One form takes 15 minutes, one email takes 3 minutes, one reservation takes 10 minutes. None of these things individually feels revolutionary, but remove thousands of them over a lifetime and it compounds into something enormous.
So yes, I am perfectly capable of checking myself into a flight but now I just don’t see why I should.
The place to run halo decompiled
Replying to @modal
Sticky Sessions for Modal Servers allow WebSocket connections to reconnect to the same container, supporting applications like collaborative editors, gaming, and multi-user rooms for voice and/or video.
Keep clients' interactions attached to the same running Modal container, so your application can maintain state across requests.
modal.com/docs/guide/sticky-…
Light into your eyes is the prompt.
If you take an LLM AI and do not provide it any prompts, goals, or any indication of expected output, it will do absolutely nothing.
It will do nothing forever in the absence of a prompt. Clearly in this state it is not conscious.
Then when prompted, it will provide an answer, and some will claim it is now conscious.
That would be a strange form of consciousness. One where it is only conscious when answering a prompt.
Gonna leave this here: oneusefulthing.org/p/centaur… jagged can also mean “very jagged”
OpenAI confirmed to the New York Times that they have made "substantial progress" on another Millennium Prize problem in the last five days, and are preparing to announce.
The rumors for the last 48 hours have been OpenAI solved the Hodge Conjecture, and that Anthropic has solved the Birch and Swinnerton-Dyer Conjecture. Since Navier-Stokes rumors abound, so I was reluctant to post about either. However, OpenAI's statement to the NYT now gives the Hodge rumors some very serious support.
In general people have not updated yet that the new unnamed OpenAI model, the one that finished training about two weeks ago, which I believe will be named Aeon, is massively better at math than Astra, which two weeks ago was the best in the world. Aeon solved Navier-Stokes in 88 hours, start to finish. Follow the trend line. That means everything is on the table. Literally everything. And this does not end with math. Please update. We are taking off.
What surprises me the most is that people dont read their work contracts. I am willing to bet that anthropic claims all IP while employed. Doesnt matter if you do it in your spare time. Such a thing often doesnt exist especially when its somehow related to your day job.
drama summary for those confused:
- Aug 15th: Tristan Buckmaster & Levent Alpöge make progress on a few important math problems
- they do NOT have a proof for the $1,000,000 Millenium Prize problem. BUT, they do claim to have a proof for a similar (non-Millenium) Navier Stokes problem that could help lead the way there
- Levent works at Anthropic, but this research was independent of his work there, with a mix of GPT and Claude models. Tristan is not related to Anthropic.
- Early Sep: Rumor spreads to OpenAI that Anthropic has solved a major problem. Tristan emails OpenAI to clarify. without revealing the problem they solved or how they did it.
- After hearing of the rumor, OpenAI started researching Navier Stokes with a new internal model.
- Sep 6th: OpenAI's Sebastien Bubeck tells Tristan that they solved the $1,000,000 Millenium Prize Navier Stokes problem. The approach is very similar to Tristan & Levent's approach to the non-Millenium problem.
- Tristan is suspicious of the timing, as only few others were trying this approach. OpenAI says the model didn't access his user data directly, but leaves unanswered whether Tristan's chat conversations were part of the training.
- OpenAI says they would partially credit Tristan for the $1,000,000 discovery (even though Tristan did not solve the $1,000,000 problem) — but only if they remove Levent as an author, as he works for Anthropic.
- Sep 8th: Tristan refuses to remove Levent, and rushes to publish their results independently.
Currently unclear is whether Anthropic had a separate solution for the $1,000,000 problem, or whether the rumor was about Tristan & Levent's independent research.
Copyright lawyers rn
it may soon be cheaper to rebuild/clone games than to buy them at the store...
it cost about $10 of compute each to knock off Super Smash Bros, as well as mario kart and a few others
built with Astra ofc
this isn't full game quality and no online vs. mode or all the maps, but we're also just getting started.
wonder how this impacts gaming companies since indie devs will be able to compete much easier, and it all comes down to execution
Maybe the lobsters won’t be first to go
For the first time, scientists have mapped the complete brain and central nervous system of an adult male fruit fly — a key model organism in science. 🪰
Working alongside HHMI Janelia Research Campus and the scientific community, @GoogleResearch scientists and researchers used AI to combine millions of 2D images into 3D neural shapes, reconstructing a record-breaking 166,000+ neurons. This foundational map of the adult male fruit fly brain can help accelerate our understanding of the brain, and is a major milestone in neuroscience.
































