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Carina Hong
@CarinaLHong
2.1K Following    15.9K Followers
@CarinaLHong believes math is training for any domain that involves structured reasoning, from working with constraints to coming up with abstractions. Watch this conversation with @mattmcilwain about how a deep love of math becomes the strategic instinct behind Axiom’s wins 💫
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Was a pretty fun podcast where I got to nerd out with @mattmcilwain about math a bit! We also covered the history of ATP, ITP, and how they converge with modern AI. Thanks to friendos at Madrona for supporting Axiom since day 1.
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I'll be speaking at #STOC2026# on AI for theory, alongside industry pioneers @WittedNote (Chief Technologist, Google), David Woodruff (CMU), @SebastienBubeck (OAI), and my friend @MarkSellke (OAI) at the very kind invitation of the organizers. See you in Salt Lake City on 6/27!
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This morning at SAIR Science x AI Summit, @CarinaLHong spoke alongside Nobel Laureate Barry Barish, Fields Medalists @wtgowers, Terrence Tao, and @leanprover Founder @leodemoura on Frontiers of AI for Math. Tune in at 2h34m30s for AxiomProver's results in its first 100 days! 💯
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Science x AI Summit 2026 (Palo Alto) is LIVE NOW! Watch live on X:
It was an honor to give a talk this morning on the frontiers of AI for mathematical research. (tune in at 2h34m30s)
Science x AI Summit 2026 (Palo Alto) is LIVE NOW! Watch live on X:
"Ono is an American Mathematical Society (AMS) Fellow, a previous AMS vice president, and founding mathematician at Axiom Math. "Kudos to the AMS and AIM for stepping up and performing this vital service. Your tireless efforts to bridge the gap between the mathematics community and our nation's leaders are deeply appreciated by us all.""
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Read more about congressional briefings:
@KenOno691 on behalf of Axiom just briefed Congress on the progress of AI for mathematics. A rising tide lifts all boats. In the AI era, we share our understanding of the frontier here at Axiom with Washington to advocate for investment in math and fundamental science research.
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The Ultimate List of Artificial Intelligence "Neolabs": May 2026. A Neolab is a pre-revenue scale startup working on long-term AI breakthroughs, usually with a $1B+ valuation. There are now 63 of them!
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Excited to launch RadixArk officially today! I have spent the past half year working with RadixArk and the SGLang community, and it has been the most rewarding experience I have had. RadixArk, and the SGLang community, has a very unique engineering culture. The code and the system have the final say. Feedback is direct because everyone trusts the intent. There is very little hierarchy around ideas, and good technical judgment matters more than title or seniority. With a high bar and fast feedback loops, people grow incredibly quickly. In many places, you spend most of your time looking at one company’s stack. Here, through SGLang community, we get to see the forest, not just the trees: many labs, companies, hardware platforms, workloads, and real production systems. There is a lot of exciting work ahead across inference, training, RL, orchestration, kernels, multi-hardware, and many real-world systems problems in between. If you love coding, enjoy building real systems, and want to work on the full AI stack from inference to training, come join us at RadixArk. This is just the beginning.
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We raised a Series B led by @sequoia at a $2 billion valuation and I’m excited to welcome @andrew__reed to our board. All our existing investors doubled down: @kleinerperkins, @IndexVentures, @khoslaventures, @firstround, @sparkcapital, @AbstractVC, and @terraincap.
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Axiom is at ICLR VerifAI workshop in Rio, Brazil! Hit up @nautsimon_ and @manooshree to chat about how it's like working with us! We have swags too.
Go XTX
Jane Street made ~$40B in 2025 with 3,500 employees, a ~2x from the year before. At ~65-70% profit margin, that's $8M profit / employee, the highest for a 1000+ ppl company. High-frequency trading continues to be the most efficient money making engine. I want to share an old story about my Jane Street interview in 2014. Jane Street was known for hiring a lot of math, physics and CS olympiad winners from top universities and putting them through many rounds - including, for trading roles, a gauntlet of mental math. It was my 6th interview and my final round and I recall being asked "What is the next day after today in DD/MM/YYYY where all the digits are unique?" They'd toy with you and say "You can use a pencil and paper, if you want" but you knew that was an instant no. Painstakingly and as quickly as I could, I came to an answer. "How confident are you that this is correct on a 0-1 probability scale?" the interviewer said. "0.95", I blurted out, not fully knowing how to answer that. "Are you sure?" After thinking harder for a few more seconds, I realized I could've flipped the digits around to get a closer date. I gave the interviewer my answer. It was correct. "0.95 huh?" he chuckled. That's when I knew I failed. Note: fwiw, other companies that come close in efficiency are - Tether ($90M+ profit/emp) - Hyperliquid ($80M+ profit/emp) and on revenue: - Valve ($50M/emp) - OnlyFans ($37M/emp) - Craigslist ($14M/emp) - Anthropic ($12M/emp, run rate) - OpenAI ($8M/emp, run rate) For comparison, Nvidia is very efficient at scale and is $4.4M/emp.
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About to brief congress regarding AI and AI for math and education and formalization. @amermathsoc @NSF @axiommathai @leanprover
Continuing to model the world through long-form podcasts! @CarinaLHong This episode is full of the "beauty of mathematics". She is also our youngest guest to date — Hong Letong, born in 2001, known online as the "Math Girl". This is her first-ever interview in Chinese. We talked about mathematics as invented versus discovered, proofs from the Book of Proofs, the entrepreneurial journey of the most unlikely founder, and of course, AI for Math. ✍🏻✍🏻 A 4-hour Interview with Carina Hong: AI for Math, Lean, Proofs from The ... 来自 @YouTube
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