Maxim Raginsky

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Researcher with public evidence across AI research.

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web: http://maxim.ece.illinois.edu substack: https://realizable.substack.com

Articles & links

Looks like others have made the same point as well: arxiv.org/abs/2610.08144

Navier-Stokes lost in translation: Why Lean verification of AI autoformalisation does not guarantee correct natural language proofs arxiv.org
AI Weekly's analysis →
  • A new preprint argues OpenAI's announced Lean proof of Navier-Stokes blow-up does not correspond to the natural-language proof it was meant to verify.
  • The authors place semantically faithful autoformalisation at SCI = infinity in the Solvability Complexity Index hierarchy, above the Halting problem's SCI = 1.
  • They present several practical examples of AI mistranslations between natural language and Lean producing mismatches between the proofs and their Lean verifications.
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View on Bluesky · ♥ 4 ↻ 0 ↩ 1 · 5 from the directory shared this · 9d ago

absolute banger arxiv.org/abs/2609.28591

The Siren Call of Silicon Leviathan: Reflections on blowup and Aufklärungsdämmerung arxiv.org
AI Weekly's analysis →
  • Mathematician Alexander Gamburd describes OpenAI's output as 166 pages, 616,000 lines of Lean, 88 hours, 10,000 software agents.
  • At the time of writing, the paper reports, no human being had read the proof in full.
  • Gamburd calls accepting the certificate without the demonstration a Hobbesian bargain and asks for a covenant requiring human understanding.
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View on Bluesky · ♥ 8 ↻ 1 ↩ 0 · 3 from the directory shared this · 22d ago

Yifeng Chu and I just posted our paper on chaining-type bounds for expected soft maxima of Gaussian processes. The analysis makes use of a nice blend of ideas from probability, statistical physics of disordered systems, and information theory. arxiv.org/abs/2606.22611

Upper and Lower Bounds on Expected Soft Maxima of Gaussian Processes arxiv.org
AI Weekly's analysis →
  • The paper derives upper and lower bounds for soft maxima of centered Gaussian processes, defined as Gibbs averages at inverse temperature β > 0.
  • The bounds retain the same multiscale structure as generic chaining expressions, with a truncation term governed by the inverse temperature β.
  • As β → ∞, the bounds recover the majorizing measure theorem; applied to the Sherrington-Kirkpatrick model, they yield a finite-size Parisi formula.
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View on Bluesky · ♥ 10 ↻ 2 ↩ 0 · 2 from the directory shared this · 116d ago

One can always count on @jwherrman.bsky.social to make good sense of what’s happening in and around AI:

In AI, Nothing Ever Happens. Wait, It’s Happening! nymag.com
AI Weekly's analysis →
  • Late 2025 brought open talk of an AI financial bubble, with even implicated CEOs voicing skepticism about the research path ahead.
  • Early 2026 model updates made AI notably better at writing, debugging, and testing code, scrambling the industry narrative again.
  • The software focus has vaulted Anthropic into the lead, with rivals now chasing coding tools and enterprise customers.
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View on Bluesky · ♥ 10 ↻ 0 ↩ 0 · 3 from the directory shared this · 100d ago

Video of the talk I gave at the Cultural AI conference at NYU back in March is finally up (thanks again to @leifw.bsky.social and @t-shoemaker.bsky.social for having arranged this excellent event). www.youtube.com/watch?v=iYu9...

Part 4 | Cultural AI: An Emerging Field youtube.com
View on Bluesky · ♥ 22 ↻ 3 ↩ 0 · 2 from the directory shared this · 132d ago

New essay by @lioneltrolling.bsky.social: “We need to have a robust public debate and understanding of just how and where we apply AI technology. Not “smash the machines” and not “let it rip” either. Is that likely to happen? Well, no, but that’s what should happen.”

unpopularfront.news
View on Bluesky · ♥ 11 ↻ 1 ↩ 0 · 2 from the directory shared this · 61d ago

Recent commentary

Pope Leo on “AI alignment” — whose values will these systems be “aligned” with?

View on Bluesky · ♥ 20 ↻ 3 ↩ 1 · 145d ago

Ricoeur on reading, very relevant for LLMs that act via the interface of language: "reading ... is at its best a struggle between two strategies, the _strategy of seduction_ pursued by the author in the guise of a more or less trustworthy narrator ... , and the _strategy of suspicion_ pursued ...

View on Bluesky · ♥ 14 ↻ 5 ↩ 1 · 15d ago

Came across the well-known quote of Oppenheimer in a book: “When you see something that is technically sweet, you go ahead and do it and you argue about what to do about it only after you have had your technical success. That is the way it was with the atomic bomb.” That's the way it is with AI now.

View on Bluesky · ♥ 19 ↻ 1 ↩ 1 · 6d ago

I find the "digestion" metaphor (i.e., mathematicians "digesting" AI-generated proofs) vulgar and off-putting. It's a sign of the times, genuine intellectuals like Yuri Manin are being replaced by a new generation whose identity is shaped by narrow professionalization and impoverished imagination.

View on Bluesky · ♥ 16 ↻ 0 ↩ 3 · 21d ago

Quine's indeterminacy of translation obviously applies to the process of translating mathematical texts to their Lean formalizations. Useful to keep in mind in the context of all the current AI-and-math discourse.

View on Bluesky · ♥ 11 ↻ 2 ↩ 1 · 9d ago

Peter Winch, writing in 1958, prefigures a lot of the current obsessions at the intersection of AI and language:

View on Bluesky · ♥ 5 ↻ 0 ↩ 2 · 126d ago

“[H]e did not mean to imitate those philanthropic models who make a profit out of poisonous pickles to support themselves while they are exposing adulteration, or hold shares in a gambling-hell that they may have leisure to represent the cause of public morality.” (about Dr Lydgate in _Middlemarch_)

View on Bluesky · ♥ 3 ↻ 0 ↩ 0 · 14d ago

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