
CS prof @Penn & founder @Rabdos_AI: creating data for the world’s hardest reasoning, from the chalkboard to the wet lab
Philadelphia, PA
Joined January 2019
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Mayur Naik retweeted
We've released the weights for Beam!!
🤗 huggingface.co/reflection
📄 Model card: reflection.ai/beam-model-car…
🧪 Try Beam in our playground & get an API key: platform.reflection.ai/playg…
📚 AND we take open model safety seriously and have posted our safety report: reflection.ai/beam-safety-re…
We built our first model!! Beam is a competitive text-only 501B-A23B MoE, openly released under the Apache 2.0 license
It’s been fun scaling the production RL/OPD stack for this over the past year. I’m so proud of the team! We attained exactly what we set out to do and ended up with a stable run on 10K GB300s that produced more than 100M rollouts across ~1M tasks that significantly improved the final performance of the model
👇 many more details in our announcement below :)
Mayur Naik retweeted
My team at @AnthropicAI is hiring: DevRel, but for scientists.
Run hackathons, build demos, and help us grow a community of researchers using Claude.
If you're a scientist who also loves to teach or post about AI for science, please apply!
job-boards.greenhouse.io/ant…
Mayur Naik retweeted
We're significantly expanding access to Gemini for scientists via antigravity - sign up now!
Top of mind question for scientists on data retention - please turn off telemetry if you'd like.
docs.google.com/forms/d/e/1F…
Excited to launch Gemini 4 Argon, designed to help with hardest coding and knowledge work tasks with its frontier capabilities..
For developers and enterprises, it’s available in the paid tier of the Gemini API and the Gemini platform, for Ultra subscribers in Google Antigravity, and Ultra and Pro subscribers in the Gemini app and Search.
Read more: blog.google/innovation-and-a…
am thinking about what the future of a "math book" should be... heavy on graphics; with interactive elements (e.g. GPT Sites); dynamic references that auto-update N-times-per-year to reflect changes; self-repairing to fix errors...
not paper & not a pdf... maybe a github repo?
Mayur Naik retweeted
Penn CIS is hiring in security and AI systems! You can find the application here: cis.upenn.edu/open-faculty-p….
As in prior years, the committee doesn't care if you have few or many papers. They focus only on 2 or 3, so make sure that your application focuses on your best work!
Mayur Naik retweeted
Congratulations to Anthropic on the release of Claude Opus 5.5! 🎉
At Rabdos, we spend our days thinking about the hardest problems in math and science, so it's exciting to watch frontier reasoning keep advancing this quickly.
Mayur Naik retweeted
THE SYMPOSIUM PUZZLE:
The final dinner of the symposium was less a banquet than a convergence theorem that had failed to be uniform. Five luminaries -- Hardy, Poincaré, von Neumann, Gödel, and Ramanujan -- sat in a row at the head table, each in a different jacket, each with a different drink, each newly returned from a different lecture tour, and each guarding a different mathematical instrument as though it were a proof of the Riemann Hypothesis.
Hardy sat brooding at the far left in herringbone, one hand curled around an espresso, the other resting upon an antique abacus whose beads he refused, on principle, to move. Immediately to his right sat a severe scholar in charcoal, upright as a metronome and no more companionable.
Poincaré, ever the classicist, wore tweed. Farther down the line, Ramanujan (newly back from Göttingen) sat resplendent in navy, sipping tea and turning a golden compass over in his fingers as though it might draw identities straight out of the air. The navy jacket sat immediately to the left of the pinstripes, a juxtaposition that pleased no tailor present. The guest who had lectured at Cambridge, meanwhile, was the one in herringbone.
When the conversation turned from foundations to apparatus, the scholar fresh from Princeton began boasting of a brass astrolabe he had recently acquired. Seated right next to him, the Göttingen speaker sneered that the workmanship was inferior to what one found on the Continent. Not to be outdone, von Neumann slapped an ivory slide rule onto the table with algorithmic enthusiasm.
Gödel, with characteristic gravity, raised a glass of port in a toast that seemed prepared for its own incompleteness. The scholar just back from Oxford preferred brandy and, being full of it, soon leapt onto the table to make a point that no one had invited. In the ensuing disorder, a fellow guest's black coffee went flying. That black coffee, in the left-to-right order of cups along the table, had been sitting somewhere between Hardy's espresso and Ramanujan's tea.
By morning the hall was deserted. Under the table lay four instruments: the antique abacus, the brass astrolabe, the ivory slide rule, and the golden compass.
The silver caliper was gone.
Who possessed each instrument -- and who had been carrying the missing silver caliper?
🤖 Made with AI
Mayur Naik retweeted
MathDuels update:
Gemini-3.5-Flash ranking #4, surpassing GPT-5.2 & Claude-Opus-4.7
Impressive performance for its speed & size.
nice math problem i came up with last december...
Consider a cube of side length 2, aligned with the coordinate axes. Place three cylinders inside it, each of height 2 and radius R, each aligned with some coordinate axis. The cylinders may not intersect. What is the maximal R?
Mayur Naik retweeted
Very excited to share a new milestone in AI for Math: Aletheia, powered by Gemini Deep Think, was just used to autonomously solve a Kirby problem! “Kirby’s list” is a “compendium of the most important unsolved problems in topology, the study of deformable shapes” (Quanta magazine). 🧵
Mayur Naik retweeted
We are delighted to unveil our research blog Rabdology at rabdology.ai, where we chart the jagged math-frontier of AI reasoning.
This is our first post in a weekly series. Read on, and if you enjoy it, please subscribe! (Link at bottom of blog's main page.)
The Three-Cylinders Problem: When AI models choose Beauty over Truth
rabdology.ai/three-cylinders
We pose a problem that a good geometry student can solve in twenty minutes. We gave it to four of the world’s most advanced AI models and watched what happened. Three of them got it wrong — and the way they got it wrong tells you something different about the state of AI mathematical reasoning than the usual benchmarks.
Mayur Naik retweeted
I feel sorry for either this person or their PhD advisor for them to say "The thing that still matters —> taste <— was never really taught". This is *most* of what my advisor taught me; the rest (semantics, coding, etc) was just hard work; he answered questions and gave feedback.
Amber (Jiachen) Liu 🍊@JIACHENLIU8May 7United States
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I was talking to a CS professor yesterday and he told me he's so relieved ⛱️ now that his PhD students have left for their summer internships.🌞. He finally gets to do interesting research himself again. It wasn't a complaint. Just something he'd been sitting with.
The old PhD bargain was pretty clean: professors had ideas, students had time, execution was the bridge. You did the work, and somewhere along the way, taste rubbed off.
That bridge is mostly gone now. A senior researcher with taste and a research agents ships faster than the same researcher plus a junior student. Explaining 🎙️ an idea to someone who doesn't yet have taste costs more than just building it. (the reason professor still needs students is because the research agent 🤖 is not yet capable enough)
Nobody wants to say this out loud
Professors keep mentoring because the system 🏫 asks them to, not because it's the highest-leverage thing they could be doing with their week.
The thing that still matters —> taste <— was never really taught. It was supposed to leak out of the execution. Now there's no execution to leak from.
Mayur Naik retweeted
I've just finished a week where I have been using agentic workflows basically 24/7. Here are some impressions:
1. I am extremely tired. Supervision of so many projects is distracting, frustrating and exhausting.
2. I have never worked on so many fronts at once. It's not only a superficial impression. I've read a ton, did courses with students, coded, learned new mathematical theorems, explored new git repos.
3. The more you work with agents, the better you become at instructing them. Don't overthink the prompts. Doing things step by step and letting the agent guide you is very productive.
4. I failed in some of those
projects. Basically I got the impression that I could do everything with the agent. Maybe, but time
and tokens are constrained.
5. I don't use much ready made software anymore. I build or scaffold stuff that I need. My favorite modality is text and best interface is simple text API. Everything can be pipelined.
6. Mathematics can be treated as software. Whatever you need to do with it, it can be decomposed into small
parts. The thinking bit is still mostly done in my brain if necessary.
7. I think of my past life as a warm-up for this new period. The offline reading, coding and internalizing was super important. Without it, I would be a pure vibe-coder. With training, you sail a ship.
8. I don't want to see my paychecks. It's expensive, because the better you get, the more you spend on more and more projects. You abandon them in a more advanced state, but there is a token price to pay.
9. Each time I see a challenge, I think whether I can find a solution with the agent. I don't skip tasks. Sometimes I feel overly optimistic. It's part of the learning to see where the agents are limited.
10. I think I master entirely new workflows. They are not properly described in the books. It's a
brave new world. Each standard task
can be turned into a task for the agent. It's very enabling.
Happy coding everyone!
Mayur Naik retweeted
In MathDuels leaderboard, Gemini-3-Flash dominates at its size: the only models ahead of it are the latest, largest frontier releases.
Gemma-4-31b-it has the highest author rating of any opensource model.
Thanks @GoogleDeepMind for these smart little models 🥹
Mayur Naik retweeted
Excellent idea. A revival of mathematical duels but in the AI form. Which model is the best problem composer and which one solves problems with no trouble. And the judge is a human professional.
Mayur Naik retweeted
4/ Paper arxiv.org/pdf/2511.08462
Code github.com/neuralprogram/QLC…
CodeQL LSP MCP Server github.com/neuralprogram/cod…
Thanks to co-authors @_ziyang_ @saikatdutta2012 @AI4Code
Happy to chat at ICLR!
"Not having a coding experience is becoming an advantage."
Replit CEO Amjad Masad:
"You don't need any development experience. You need grit. You need to be a fast learner."
"If you're a good gamer, if you can jump in a game and figure it out really quickly, you're really good at this."
"Coders get lost in the details."
"Product people, people who are focused on solving a problem, on making money, they're going to be focused on marketing, they're going to be focused on user interface, they're going to be focused on all the right things."
"I think this year it's gonna flip, and I think not having a coding background is gonna be more advantageous for the entrepreneur."
@amasad with @jackneel
Mayur Naik retweeted
📢 Excited to share that our paper "QLCoder: A Query Synthesizer For Static Analysis of Security Vulnerabilities" has been accepted to #ICLR2026!
🥳
Congrats to my co-authors @lambdaclaire, @AI4Code, and @_ziyang_
Preprint: arxiv.org/pdf/2511.08462
Mayur Naik retweeted
Like a deep-sea anglerfish illuminating its surroundings, ESCA "illuminates" an agent's environment with structured scene graphs ( source). This new framework from UPenn, accelerated by JAX, is a game-changer for embodied AI.
goo.gle/esca-screen-graphs-j…
#AI #JAX #Robotics #Innovation


























