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Insights

Insights2026.10.26

AI turned out 722 math manuscripts at once. Now the scarce resource is mathematicians to read them

OpenAI released 722 AI-generated math manuscripts at once. Of the 719 left after withdrawals, only 42% have proofs confirmed by the Lean program. This piece follows the record of 3 withdrawals over a calculation error the next day, 14 separate proof revisions, and how mathematicians reacted. Together they show math's bottleneck moving from producing proofs to finding people who can read and check them.

Insights2026.10.26

Handing classification to AI now costs almost nothing. Almost no one checked whether it got the answers right

TypeSafe's decision model Jev matched Claude Sonnet 5's score of 67.8% at $0.0004 per decision, but the answers it was graded against came from two AI models that aren't on the leaderboard. When Red Hat retested it on public data with labels already attached, Jev ranked first or fourth depending on the task, and the results did not show it was faster or cheaper. Now that decisions are nearly free, the first thing to check isn't the model's price. It's whether you have an answer key that can show the decisions were right for your work.

Insights2026.10.26

AI agent hacks hit several Korean financial firms, but the breached systems were loan-broker and staff tools, not banking apps

US security firm CrowdStrike analyzed AI work logs left on an attacker's server. The attacker ran a free open-source tool on other companies' commercial AI models and tried to break into many financial firms at once. What got breached were not banking apps but work systems for loan brokers and staff with weak identity checks. Korea's Financial Services Commission told firms to review systems by whether they are open to the outside, not by whether customers use them.

Insights2026.09.27

AI agents finished whole research papers on their own, but judgment, not experimentation, is where they stalled

Researchers from Princeton, the UK AI Security Institute, and other institutions gave frontier agents the research questions behind two unpublished NeurIPS submissions, then had the original authors grade the results. The agents handled everything from the literature review to typesetting without human help, yet both papers were rejected. Here are the five failures the paper traced in the run logs, along with the limits the authors acknowledged.

AI-generated

Insights2026.09.27

Crediting a career coach for a cover letter didn't hurt trust, but crediting AI did

In 13 experiments preregistered before any data was collected, University of Arizona researchers Schilke and Reimann found that a cover letter credited to a career coach earned the same trust as one with no note at all, while only the one credited to AI lost trust. The penalty held across six ways of wording the disclosure and when disclosure was required by rule, and in the final experiment an advisor exposed by a third party scored lower still than one who disclosed it himself.

AI-generated

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