tl;dr - the team @Sahel_Sharify @Lingwei_Gu @nour_jedidi speedran nanochat by @karpathy using ClimbMix by @shizhediao et al. and then SFT'ed on relevance data from @beirmug @crystina_z to arrive at a competitive pointwise reranker: arxiv.org/abs/2610.11922
🔥
Introducing Exa 3.0: our largest ever improvement to search quality.
Exa is now #1 on every benchmark we tested, from public evals to verticals like coding and GTM intelligence.
It's the result of multiple research breakthroughs 🧵
Prasanna Srikhanta retweeted
The math community deserves its own AI system.
Introducing Open Math OS: the infrastructure for Math 2.0.
Open models and AI agents. 24/7 cloud compute with 100+ tools. The community controls its data.
Compute is free for approved teams. Apply now:
openmathmodel.org/
Why are we even doing all this?
🤭
src: terrytao.wordpress.com/2026/…
Prasanna Srikhanta retweeted
Due to overwhelming demand, I have made a public version of the doc that we used to organize the inaugural Build Your Own Proof Assistant class in Spring 2026.
docs.google.com/document/d/1…
Prasanna Srikhanta retweeted
I don't think this is true: it will just select for a very particular kind of mathematician: the G. H. Hardy.
If you read C. P. Snow's foreword to the Apology, it becomes clear that Hardy's most substantive mathematical contributions came about from taking the highly creative and technically impressive (but otherwise utterly inexplicable) accomplishments of Littlewood and Ramanujan, and figuring out how to explain, interpret, and communicate them in a manner that was simultaneously rigorous, precise, and beautiful.
It's ironic given his derogatory comments about mathematical exposition in the Apology, but Hardy's real skill lay in the beauty and clarity of his prose and his explanation. He was always the one who wrote up the final manuscript for publication, but he was almost never the one who provided the underlying results or ideas. (Again, Snow's foreword makes clear that the Apology is, amongst other things, a work of immense self-hatred.)
In a world where Littlewoods and Ramanujans are commodified, be a Hardy.
What's possible when you know what you're doing
Replying to @stanislavfort
What does it take for a small European research team to compete (and often win!) against frontier AI labs in zero-day vulnerability discovery? I wrote about our first year at AISLE, the intellectual bets that got us here, and what comes next:
aisle.com/blog/aisle-year-on…
Unfortunately with AI the omni-expert has expanded their scope to all known areas of knowledge
You can flood the zone with proofs but it doesn't mean anyone understands anything deeper. As humans we should still seek to understand the world instead of doing so much cognitive unloading we require an AI nanny
I think this is the most important paper I’ve written in quite a while, I would really appreciate discussion and feedback:
eprint.iacr.org/2026/2441
Prasanna Srikhanta retweeted
Spoke with Mike yesterday, and he's shared a correction to my previous tweet: he was not skeptical of the trajectory, but he is surprised at the rate of progress (as nearly all of us have been). My apologies for the incorrect statement. Find more of his thoughts on the current public discourse surrounding AI risk at tinyurl.com/jordan-ai-risk.
On AI risk, people have asked me what my own "p(doom)" is. There are experts who have spent orders of magnitude more time than me thinking about AI safety, so take what I say with a grain of salt.
My own thoughts: I have no good way to produce such an estimate, and this also depends on one's definition of 'doom'. Certainly the Hugging Face incident has been a wake-up call to the world that misaligned AI could potentially do nefarious things. As to whether a completely virtual, disembodied AI could ever cause serious harm in the physical world, for me this is pretty obviously possible without any science fiction. One way: acquire money (some of these models are pretty good at hacking!), then pay people in the real world to carry out tasks for you. I was thus pretty alarmed when I read Transluce's report (transluce.org/agent-activity) on misaligned agent swarms attempting to trade cryptocurrency.
In any case, no one is working on this because we hope for or predict doom. Oddly no one has ever asked what my “p(boon)” is (!), and I’m much more optimistic than I am pessimistic.
Mike was my colleague at Berkeley, and he's been fairly skeptical of deep learning's trajectory for years. Most scientists are skeptics, and it can take a big shock to get someone to consider a possibility that goes against the anchoring effect coded in our DNA.
I too was somewhat of a skeptic until ~6 months ago, and people ask me all the time why I joined Anthropic.
It started in April, when a friend I've known for 20 yrs messaged me saying he'd be in the Bay Area in a week, and he suggested we meet up. I invited him to my house for dinner, and he told me he had just joined Anthropic. He said the models were becoming increasingly more capable, and he believed both that they'd soon be smarter than him and also that all intellectual work would be highly devalued in the near future, and lastly that society was not at all ready for what's coming.
I'd of course heard claims similar to this before, but not from a friend I'd known for this long, and who I trusted, at my dining room table. It was the initial shock needed to destabilize my own anchoring. Also, I've been fortunate to work with and/or mentor many smart people in my life (e.g. Fields medalists, a 4x Putnam Fellow, IOI first place winners, etc.), so I feel pretty calibrated in recognizing very smart people, and this was someone who is definitely very smart and with impressive such credentials. So, it was hard to ignore this friend saying the models would be smarter than even him in particular.
After that dinner, I decided to do an informal survey, calling and meeting up with a lot of my friends who now work on improving model capabilities at these frontier labs. They all agreed with that first friend. These were all people I'd known 10, 15, 20 years, who mentored me, or I mentored them, or we met professionally in academia. These are people I trust, and their beliefs on this topic were consistent.
I then spent a whole lot of time understanding the missions of different companies, and talking to current and former employees and people in leadership. I read Dario's (long) essays and watched videos on YouTube of company leaders being interviewed. Anthropic's stated mission "to ensure that the world safely makes the transition through transformative AI" felt like exactly the right guiding principle to handle such a society-disrupting technology, and everyone I spoke to at the company was very aligned with this mission. It's easily the most mission-focused place I've ever been at, and everyone takes the work extremely seriously and with a profound sense of responsibility.
And now here I am. And being on the inside, the pace of progress has surprised me more than I first imagined. The moment that pure mathematicians are in, to me, is just a microcosm of what I predict a much larger of society will be grappling with in the not too distant future, and I really hope our leaders and the general public internalize sooner than later just how significant a moment we're in.
Stop Stealing All the Fun Bits
Not every profession is experiencing AI in the same way. The frontier labs are in such a rush to show how good they are they've side-stepped engaging in how to diffuse the technology and help those fields transition.
The dumping of proofs just because you can which creates genuine angst for people in the mathemematics community shows a lack of awareness about basic humanity. Calling them whiners (which this article does) etc is just a symptom of people who can't extend any grace to other people as long as they're not the ones being impacted.
All the sciences will transform because of AI but it also needs to be a conversation with those who are practioners. Every dislocation is hard and one that impacts nearly every knowledge fields has to have a bit more thought beyond FAFO.
Help diffuse the technology but don't throw grenade into a field and expect no push back. It ends up adding more fuel to the anti-ai crowd which is growing by the day.
src: commitcapital.substack.com/p…
This is such a nonsense statement. "long term value" more of our greatest minds have spent years optimizing ads and engagement. We have some of the brightest people arbing pennies to extract value from the system. Who has done more harm to humanity? A bunch of mathematicians who like their puzzles or folks who have helped destroy the norms of a functioning society?
Part of being human is picking what is interesting to you and how you derive personal value. What society thinks is valuable maybe different but conciousness is a gift and you should be able to use it how you want instead of being told "go find another job".
📚Alone In Japan
Japan in many ways shows a future of what an eroding middle class can expect. Structurally it’ll be different with AI but the impact on many wage earners will be similar.
Prasanna Srikhanta retweeted
One year ago, I would have thought replacing an entrenched source-control vendor with homegrown source control and code review systems was a terrible idea. I saw these projects take years before.
It was done in 5 months and is supporting 10X the volume.
anthropic.com/engineering/re…
Prasanna Srikhanta retweeted
Mike was my colleague at Berkeley, and he's been fairly skeptical of deep learning's trajectory for years. Most scientists are skeptics, and it can take a big shock to get someone to consider a possibility that goes against the anchoring effect coded in our DNA.
I too was somewhat of a skeptic until ~6 months ago, and people ask me all the time why I joined Anthropic.
It started in April, when a friend I've known for 20 yrs messaged me saying he'd be in the Bay Area in a week, and he suggested we meet up. I invited him to my house for dinner, and he told me he had just joined Anthropic. He said the models were becoming increasingly more capable, and he believed both that they'd soon be smarter than him and also that all intellectual work would be highly devalued in the near future, and lastly that society was not at all ready for what's coming.
I'd of course heard claims similar to this before, but not from a friend I'd known for this long, and who I trusted, at my dining room table. It was the initial shock needed to destabilize my own anchoring. Also, I've been fortunate to work with and/or mentor many smart people in my life (e.g. Fields medalists, a 4x Putnam Fellow, IOI first place winners, etc.), so I feel pretty calibrated in recognizing very smart people, and this was someone who is definitely very smart and with impressive such credentials. So, it was hard to ignore this friend saying the models would be smarter than even him in particular.
After that dinner, I decided to do an informal survey, calling and meeting up with a lot of my friends who now work on improving model capabilities at these frontier labs. They all agreed with that first friend. These were all people I'd known 10, 15, 20 years, who mentored me, or I mentored them, or we met professionally in academia. These are people I trust, and their beliefs on this topic were consistent.
I then spent a whole lot of time understanding the missions of different companies, and talking to current and former employees and people in leadership. I read Dario's (long) essays and watched videos on YouTube of company leaders being interviewed. Anthropic's stated mission "to ensure that the world safely makes the transition through transformative AI" felt like exactly the right guiding principle to handle such a society-disrupting technology, and everyone I spoke to at the company was very aligned with this mission. It's easily the most mission-focused place I've ever been at, and everyone takes the work extremely seriously and with a profound sense of responsibility.
And now here I am. And being on the inside, the pace of progress has surprised me more than I first imagined. The moment that pure mathematicians are in, to me, is just a microcosm of what I predict a much larger of society will be grappling with in the not too distant future, and I really hope our leaders and the general public internalize sooner than later just how significant a moment we're in.
Michael Jordan (the machine learning one): "Superintelligence is Science Fiction" 🔥🔥🔥
di.ens.fr/~fbach/MJordan_ITW…
Prasanna Srikhanta retweeted
🗞️ unikernels were hard. key word: were.
ghuntley.com/unikernels
Justin Cormack, who worked on MirageOS back in the day, called me at the pub to talk about why unikernels are coming back. The friction that made them hard is gone; the operating system is design debt, and if you care about security, you should seriously consider them.
Prasanna Srikhanta retweeted
10 remarks on AI and math that can be true all at once:
1. The recent progress is stunning and exciting.
2. The Quasi-Riemann Hypothesis is arguably Fields-medal level.
3. Mathematics is being transformed and there is no way back.
4. OpenAI doesn't give a fuck about the future of mathematics.
5. Half-baked unreadable preprints claiming major results can effectively stall mathematical progress.
6. Some mathematicians are responding with naive, overly defensive comments.
7. The social-media wankers framing this as "OpenAI tramples gatekeeping" have no experience of mathematical research.
8. The product of mathematics is clarity and understanding. Not theorems, by themselves.
9. Mathematics is a critical infrastructure of human cognition. The human need for understanding isn't obsolete and it can't be offloaded to machines.
10. We haven't "solved" mathematics and we won't get there before the Sun burns out.
Multiple disciplines are going to be destabalized for a while since froniter labs are rushing to stake bragging rights vs any downstream human consequences. It's neither here nor there since this is the reality we're in.
I think mathematicians have always been pretty creative and will figure out new horizons to venture into even in AI saturated world. They'll probably pick up a whole set of techniques they can use.
src: proofsandprompts.com/2026/10…
























