Corinna Hong

Founder & CEO, Axiom · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderexecutivescientist@CarinaLHong ↗LinkedIn ↗axiommath.ai ↗

A former Rhodes Scholar and MIT graduate, Carina Hong left Stanford to found Axiom, a startup building self-improving AI systems for formal mathematical reasoning and automated theorem proving. Under her leadership, Axiom raised over $260 million to advance formal verification across mathematics and software.

31statements → 18claims → 4claims resolved → 75%fully supported → 3.68/5average certainty → 2.13/5average debate potential → 3.8/5argument clarity · the sources →

3 supported 0 partly supported 1 contradicted 1 not yet assessed 13 not checkable as stated how the 18 claims stand · each chip opens the sources

2 predictions · 16 assertions · 8 insights · 5 disclosures · every statement was checked. The predictions and assertions are the 18 claims: statements the public record can support or contradict. 4 are resolved, 1 is not yet assessed, and 13 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Corinna argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported
AxiomProver achieved a perfect score on the 2025 Putnam math exam
“Eight within the time limit, and then 12 out of 12.”
Corinna Hong Feb 26, 2026 ▶ 4:02 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong

Their most notable contradicted claim

Assertion Contradicted
The open-source Lean dataset contains only tens of millions of tokens
“It's only two-digit million number of tokens out there in the open, open world.”
Corinna Hong Feb 26, 2026 ▶ 28:35 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong

Expressed certainty vs assessment result

none yet certainty 1
none yet certainty 2
none yet certainty 3
67% certainty 4
100% certainty 5

weighted support: a fully supported claim counts one, a partly supported claim counts half. Each filled bar is clickable and opens exactly those claims; "none yet" means nothing said at that certainty level has resolved yet

Argument clarity: do they answer the question? how? →

3.8 / 5 directness 3.6 · coherence 3.6 · precision 3.6 · compression 3.1

redirected or did not address 4 of 14 assessed questions (29%). Watch them ▸

This is a score against a rubric. It is not a rank. Every host question → answer exchange is scored with names hidden on directness, coherence, precision and compression, 1–5 each, on meaning alone: disfluencies are ignored, and only raw unedited episodes count. This is the score that measures thought. Every scored exchange, scores shown → · The rubric and its checks →

How they sound: speaking style how? →

240 words/min while actually speaking · 22.4 um and uh per 1k words

Measured by listening to the audio itself: 9,962 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Corinna Hong said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Assertion Not checkable as stated
AxiomProver is the first AI to solve research conjectures end-to-end
“It's probably the first AI to solve a research conjecture completely end-to-end and self-verifies. That means the output are fully verified, a hundred percent correct.”
Corinna Hong Feb 26, 2026 ▶ 4:56 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Supported
AxiomProver achieved a perfect score on the 2025 Putnam math exam
“Eight within the time limit, and then 12 out of 12.”
Corinna Hong Feb 26, 2026 ▶ 4:02 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Prediction Not checkable as stated
Today's AI can solve math problems that take human researchers months
“I think that we are at a threshold of mathematical renaissance, which is to realize that there are so many unsolved problems that will currently take, say, researchers months to crack, or even technical lemmas in those really longstanding conjectures that we b…”
Corinna Hong Feb 26, 2026 ▶ 6:14 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Insight
True AI reasoning engines require verifiable rewards for intermediate proof steps
“If you want to have a reasoning engine that really truly masters at logic and mathematical reasoning, then you need to somehow get verifiable reward for the proof steps.”
Corinna Hong Feb 26, 2026 ▶ 19:52 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Open · timeframe Feb 2029
Axiom's proof verifier is 100 times faster than open-source alternatives
“So a lot of the sort of like verify, verify proof is actually, you know, one of our prover tools that's about to be released, and that's actually a hundred times faster than The other counterparts that are the open source, like effort, cloud comparator.”
Corinna Hong Feb 26, 2026 ▶ 37:32 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Not checkable as stated
AxiomProver autonomously proves theorems publishable in major mathematical journals
“Currently the batch of papers, Axiom Prover has autonomously proven and mathematicians have written You can probably get into Journal of Number Theory, Journal of Algebra, like that level.”
Corinna Hong Feb 26, 2026 ▶ 43:12 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Disclosure
Axiom Math aims to solve a Fields Medal shortlist-worthy problem using AI
“I think that we really want Accent Prover to be able to solve one long-standing problem in mathematics that you can objectively, objectively say, even though if it's an AI, you know, or double-blind, whatever, that will be in the shortlist.”
Corinna Hong Feb 26, 2026 ▶ 46:49 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Prediction Not checkable as stated
AxiomProver could eventually solve the majority of human mathematical conjectures
“Everything that human mind Can conjecture, find interesting, find tasteful, could be solved by, hopefully, majority of them by accent prover.”
Corinna Hong Feb 26, 2026 ▶ 48:56 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Insight
Generation and verification loops are the next major frontier of AI
“We still feel like we cannot fully elaborate and emphasize the thing that we are seeing that is the next frontier of AI. That is a generation and verification loop. That is the discovery of verified knowledge.”
Corinna Hong Feb 26, 2026 ▶ 1:03:09 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Supported
AxiomProver has solved four research-level open mathematical problems
“Recently, I think like a couple of weeks ago, we just announced that action prover solved these four research level open problems.”
Corinna Hong Feb 26, 2026 ▶ 4:50 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Not checkable as stated
Axiom Math's AI system proves multiple open research conjectures every week
“We actually have actually a few more research conjectures that's being proven every week just by the supply of mathematicians you know, from the world, and we try to put those problems into use.”
Corinna Hong Feb 26, 2026 ▶ 6:47 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Not checkable as stated
Numerical AI benchmarks fail to evaluate underlying logical reasoning capabilities
“Like, you know, we have seen from, say, Frontier Math and other benchmark, which only compels a numerical answer that it doesn't actually necessarily reflect the model's capability in the logical reasoning.”
Corinna Hong Feb 26, 2026 ▶ 18:17 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Insight
Mathematical reasoning is the foundational reasoning layer for AGI
“Our worldview is math reasoning is a true reasoning layer of AGI.”
Corinna Hong Feb 26, 2026 ▶ 21:26 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Disclosure
AxiomProver self-improves by adding generated mathematical proofs to its skill library
“Action Prover learns to prove things, and it kind of self-improved in a way where all the things that it proved got fed back into it, into a kind of a skill library.”
Corinna Hong Feb 26, 2026 ▶ 28:40 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Insight
Mathematical AI unlocks solutions for verification and optimization
“I think through solving math, we also realize that it can solve a lot of other problems, such as verification, such as optimization, et cetera.”
Corinna Hong Feb 26, 2026 ▶ 1:45 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Not checkable as stated
Axiom's AI generated Putnam math solutions that diverge from human proofs
“So we actually analyzed all 12 problem solutions of the Putnam exam, and we found that a lot of the solutions actually differ from the human solution.”
Corinna Hong Feb 26, 2026 ▶ 8:22 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Insight
Lean-based AI provers favor mechanistic arguments over clever human-style solutions
“Because it is a, you know, lean based system, it is really good at sort of routine bookkeeping, and it will actually choose a lot of the more mechanistic, you know, arguments over the ones that require like a clever, say one picture solution.”
Corinna Hong Feb 26, 2026 ▶ 8:30 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Not checkable as stated
Auto-formalization is harder than translating between two programming languages
“And auto formalization, which is the sort of capability of converting the natural language reasoning to say the formal language. And that's harder than translation because it's different than say translating between two programming languages. You're translatin…”
Corinna Hong Feb 26, 2026 ▶ 15:29 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Not checkable as stated
Translating formal Lean code into English is easier than auto-formalization
“There's also auto-informalization, which is kind of translate back, I mean, from Lean to English. That's easier than auto-formalization, because most of the machines' AI have seen a lot more English than Lean.”
Corinna Hong Feb 26, 2026 ▶ 15:55 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Disclosure
Axiom Math focuses on post-training reinforcement learning to achieve performance gains
“And I think that we shouldn't do pre-training. We shouldn't try to just only train from scratch. I think we're kind of focusing on post-training reinforcement learning can potentially get us better performance gain.”
Corinna Hong Feb 26, 2026 ▶ 17:26 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Insight
The Lean theorem prover language is closer to Rust than to English
“I think the sort of gap between, say, for example, Lean and another, like, strongly typed language like Rust is a lot closer than the gap between Lean and English.”
Corinna Hong Feb 26, 2026 ▶ 22:58 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Contradicted
The open-source Lean dataset contains only tens of millions of tokens
“It's only two-digit million number of tokens out there in the open, open world.”
Corinna Hong Feb 26, 2026 ▶ 28:35 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Disclosure
Axiom Math will release its Lean tools on a public API
“We are actually gonna release them on a public, like, API on these, all these dozen of pools. Very, very soon. Beginning of March.”
Corinna Hong Feb 26, 2026 ▶ 36:40 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong
Assertion Not checkable as stated
Axiom Math tested transfer learning from mathematical reasoning to code verification
“So from Putnam Perfect Score, that was four months in, then two months later was the four research conjectures, and then, you know, during this middle, we also have tested something that is transfer learning from math to code verification, so another evaluatio…”
Corinna Hong Feb 26, 2026 ▶ 41:44 AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong

Show 7statements(7 left)

Appearances (1)

EpisodeDateSpeaking time
AI That Can Prove It’s Right: Verification as the Missing Layer in AI — Carina Hong Feb 26, 2026 50m
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