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Good morning.

The promise of AI has always been tangible progress in science, physics, medicine and mathematics.

Well, it's happening.

On Tuesday, OpenAI released a collection of AI-generated mathematical results. Its public repository groups the manuscripts into 372 families. There are proof files, revisions and caveats.

Some of these manuscripts are very early stage concepts, others are far along.

Obviously every such release starts the predictable circus again. People start proclaiming the death of mathematics and tell us mathematics is now solved. Others tell us that this entire exercise is useless but don’t tell us why. They just hate the technology I guess. But nobody bothers to look at this from up close.

Because that requires someone to actually read these papers. An outrageous demand in the age of instant opinions.

OpenAI’s own documentation makes an essential distinction: these results are at different stages of verification. Some have formal proofs ; others still need scrutiny. Even a formalised result does not automatically certify every claim in the accompanying paper.

So no, a mountain of PDFs is not a mountain of settled truth. But dismissing the whole thing because it arrived by machine would be equally stupid.

The reaction reported by WIRED includes concerns about credit and the sheer volume of work being released. Those are legitimate questions. Who checks the results? Who explains them?

We have spent years worrying about machines doing our work. We should also prepare for machines producing more work than we know how to judge. Proposals. Designs. Legal arguments. Software patches. Each one looking plausible, polished and perfect.

And more difficult to imagine : we might soon go into the territory where us humans cannot check the AI’s work anymore because it has surpassed us in intellect. Where the AI is doing things we cannot comprehend anymore.

It’s like Einstein would attempt to explain his theory of relativity to a 5-year old. They simply don’t have the brainspace for it.

The scarce skill becomes deciding what deserves to survive contact with reality. And even that skill is being put into question by the limits to our intellect.

We’re truly in uncharted waters.

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AI News

OpenAI releases a mathematical avalanche. OpenAI published hundreds of manuscripts from an internal frontier model, alongside research details and some Lean proof formalizations. The results have differing verification status; the release offers material for researchers to examine, rather than blanket confirmation that every claimed result is correct. (OpenAI)

Mistral previews its largest model. Mistral Large 4 is available through a public preview API, with downloadable weights promised by the end of October. The European lab is testing expanded cybersecurity capabilities with vetted partners before that release; its performance claims remain company-reported. (Mistral)

OpenAI introduces text watermarking. OpenAI opened optional textGrain watermarking for selected API models and plans to mark eligible ChatGPT and Codex output in the EU over coming weeks. Detector access initially targets approved experts, and OpenAI warns that editing and short passages undermine reliability. (OpenAI)

OpenAI safety-report lead resigns. David Robinson, who led the writing of OpenAI’s launch safety reports, resigned and publicly criticised the company’s culture of perpetual sprints. His essay argues for stronger organisational safeguards while noting that OpenAI stands by its safety practices. (The Atlantic)

Anthropic expands verified cybersecurity access. Anthropic introduced three Cyber Verification Program tiers, extending advanced models and reduced cyber blocking to qualifying security professionals. Access depends on the work involved and verification requirements, with the least restricted tier reserved for closely vetted organisations handling especially sensitive systems. (Anthropic)

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Closing Thoughts

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