Raymond Baartmans retweeted
sam: local inference is a terrible allocation of scarce resources
“a lot of people want local inference, and somehow they assume that the problem is solved now because we have open-source models, we're going to be able to run them on our computers, and so we're not going to need all the stuff in the data centre
but from a global allocation perspective, actually it's quite terrible to have everybody, like, have a bunch of the world's limited supply of DRAM sitting in their own computer and being used five percent of the time
you want maximum utilisation in the cloud if you're trying to deal with this very supply-constrained environment
somehow many people's intuition is the opposite of that”
Raymond Baartmans retweeted
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
Raymond Baartmans retweeted
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
Raymond Baartmans retweeted
It's fun to make predictions. Here's a new one:
Anthropic has solved a Millennium Prize Problem.
And I'll be even more specific.
Claude has solved Navier–Stokes.
It is out for expert review.
And to give myself a hard deadline, they will announce it before the IPO.
Raymond Baartmans retweeted
and must be abolished and redone according to contemporary standards of justice. In a sense, leftism is right--there is something "arbitrary" in the originary distribution, but, of course, any "reset" will have plenty of arbitrariness as well. Which is why any leftist
Raymond Baartmans retweeted
I think that any community past the most elementary hunter-gatherer stage has an originary distribution of something like property which is then continued and subject to redistribution in various ways. I see leftism as the conviction that this originary distribution is unjust
Raymond Baartmans retweeted
hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final
((1+xy)^3 z + y^2 (1+xy) (4+3xy), y + 3 x (1+xy)^2 z + 3 x y^2 (4+3xy), 2 x - 3 x^2 y - x^3 z): \C^3\to \C^3, has jacobian determinant -2, and sends (0, 0, -1/4), (1, -3/2, 13/2), and (-1, 3/2, 13/2) to (-1/4, 0, 0)
Raymond Baartmans retweeted
It has now become absolutely commonplace on all sides to say "the system is rigged," without proper evidence of said rigging. The seductiveness of that perverse worldview is obvious: it allows you to lie, rob and cheat without remorse and with a sense of malicious justification.
Raymond Baartmans retweeted
The immigration thing is really a metaphor for everything. America can win with immigration or it can lose because a minority of the population doesn’t like how certain people look different from themselves.
The success of the U.S. men’s national soccer team in this year’s World Cup is the product in part of America’s historically welcoming immigration system. wsj.com/opinion/world-cup-u-… via @WSJopinion
Raymond Baartmans retweeted
This new research on US unicorn startups is really interesting.
Some key facts from the report:
1. Immigrants founded or cofounded 455 of America’s 775 privately held billion-dollar startups, equal to 59% of all US unicorns.
2. 66% of all US unicorns were founded or cofounded by immigrants or the children of immigrants.
3. 79% of US unicorns have either an immigrant founder or an immigrant in a key leadership role.
4. The 455 immigrant-founded US unicorns have a combined valuation of $5 trillion.
5. That $5 trillion valuation is larger than the total stock-market value of companies listed in all but 7 countries.
6. Including immigrant-founded unicorns that went public since 2016 pushes the total value above $5.8 trillion.
7. The number of immigrant-founded US unicorns rose from 50 in 2018 to 455 in 2026.
8. 24% of US unicorns have a founder who first came to America as an international student.
Raymond Baartmans retweeted
This has quietly been a miracle month in medicine.
In the last 5 weeks we’ve got news on:
- retatrutide, the triple agonist GLP-1 from Lilly, basically melting fat and body-wide inflammation at record levels
- RevMed’s new pancreatic cancer drug showing unprecedented abilities to extend life
- small trial of a one-and-done PCSK9 gene editing therapy for slashing LDL cholesterol
- Mayo’s AI-assisted radiology showing vastly improved cancer detection
- this new therapy for metastatic solid tumors
This stuff is at varying levels of evidence. Retatrutide is ~100% on its way, other stuff needs more clinical trial data. But put it together and we’re maybe on the verge of majorly reducing the mortality of heart disease and cancer, the two leading causes of death in America.
Raymond Baartmans retweeted
the refutation comes so can continue to circulate in its pre-refutation form. It gains in value as currency for those accepting it as good coin precisely because it represents a "truth" before the "official story" could muzzle it. And then repeating it becomes a requirement
Raymond Baartmans retweeted
Once a particular claim gets minted (like "Rubio admits that Israel forced the US into war") and gets enough circulation it become unrevokable and will serve as currency in certain circles. So, there's a rush to mint it as quickly as possible and get it into circulation before
Raymond Baartmans retweeted
Don't think of LLMs as entities but as simulators. For example, when exploring a topic, don't ask:
"What do you think about xyz"?
There is no "you". Next time try:
"What would be a good group of people to explore xyz? What would they say?"
The LLM can channel/simulate many perspectives but it hasn't "thought about" xyz for a while and over time and formed its own opinions in the way we're used to. If you force it via the use of "you", it will give you something by adopting a personality embedding vector implied by the statistics of its finetuning data and then simulate that. It's fine to do, but there is a lot less mystique to it than I find people naively attribute to "asking an AI".
Raymond Baartmans retweeted
Geoffrey Hinton, father of deep learning (right) at age 31, with Chris Riesbeck (left). La Jolla, CA.
Raymond Baartmans retweeted
Transforming human knowledge, sensors and actuators from human-first and human-legible to LLM-first and LLM-legible is a beautiful space with so much potential and so much can be done...
One example I'm obsessed with recently - for every textbook pdf/epub, there is a perfect "LLMification" of it intended not for human but for an LLM (though it is a non-trivial transformation that would need human in the loop involvement).
- All of the exposition is extracted into a markdown document, including all latex, styling (bold/italic), tables, lists, etc. All of the figures are extracted as images.
- All worked problems get extracted into SFT examples. Any referenced made to previous figures/tables/etc. are parsed and included.
- All practice problems are extracted into environment examples for RL. The correct answers are located in the answer key and attached. Any additional information is added as "answer key" for a potential LLM judge.
- Synthetic data expansion. For every specific problem, you can create an infinite problem generator, which emits problems of that type. For example, if a problem is "What is the angle between the hour and minute hands at 9am?" , you can imagine generalizing that to any arbitrary time and calculating answers using Python code, and possibly generating synthetic variations of the prompt text.
- All of the data above could be nicely indexed and embedded into a RAG database for later reference, or maybe MCP servers that make it available.
Then just as a (human) student could take a high school physics course, an LLM could take it in the exact same way. This would be a significantly richer source of legible, workable information for an LLM than just something like pdf-to-text (current prevailing practice), which simply asks the LLM to predict the textbook content top to bottom token by token (umm - lame).
As just a quick and crappy example of synthetic variations of the above example, GPT-5 gave me this problem generator (see image), which can now generalize that problem template to many variations:
- When the time is 11:07 a.m., what is the degree measure of the angle between the hands? (Answer: 68)
- Determine the angle in degrees between the clock’s hands at 4:14 a.m.. (Answer: 43)
- What angle do the clock hands form when the time reads 11:47 a.m.? (Answer: 71)
- At 7:02 a.m., what angle separates the hour hand and the minute hand? (Answer: 161)
- At 4:14 a.m., calculate the angle made between the two hands. (Answer: 43)
- What angle is formed by the hands of a clock at 4:45 p.m.? (Answer: 127)
- What is the angle between the hour and minute hands at 8:37 p.m.? (Answer: 36)
(infinite practice problems can be created...)
