Viking from Jomsborg. The DAO investor. Applied math. Geometric quantization. Building reasoning layer.
jomsborg.eth
Joined January 2013
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Jacek (Jomsborg.eth) retweeted
The flood of results building on OpenAI's Quasi-Riemann Hypothesis breakthrough keeps coming!
Today, we have a preprint from Baiying Liu showing that all finite-order Hecke L-functions are zero-free to the right of 0.8749!
This improves on 31/32 (= 0.96875), established only a few days ago by Cureton and Thorner.
Some fascinating developments following OpenAI's shock breakthrough proof of the Quasi-Riemann Hypothesis, which was released publicly on October 6:
1. Building on OpenAI's proof, a recent Hexagon preprint (released on October 12) by Cureton and Thorner establishes that ALL finite-order Hecke L-functions are zero-free to the right of 1 - 1/6000.
2. And now, today, an arXiv preprint by Frei, Somos and Widmer uses this result to prove unconditionally the 2007 Ellenberg–Venkatesh bounds on ℓ-torsion in class groups of number fields.
I was amused to see the AI declaration in the second paper: "No artificial intelligence tools were used in this work."
No other way
"Pardon also reports that AI has proved several nontrivial lemmas for him. However, he says it has not yet produced a major breakthrough in his own research."
A Fields Medalist says AI can now understand mathematical proofs even when his notes are almost unreadable to other mathematicians.
John Pardon explains that until recently, AI was little more than a spelling checker for his mathematical writing.
Now, he says, it can examine highly compressed, incomplete research notes and identify subtle mathematical mistakes.
For example, a missing condition such as finite or sifted in a statement about colimits can change its meaning. According to Pardon, AI can recognize such omissions by interpreting the broader mathematical context.
His assessment is:
“The AI understands. 100%.”
Pardon also reports that AI has proved several nontrivial lemmas for him. However, he says it has not yet produced a major breakthrough in his own research.
Pardon believes AI is changing mathematical research, but he also emphasizes that students must work through easier problems themselves to develop the understanding needed for harder ones.
He finds value in deliberately approaching unfamiliar problems, even when AI could immediately explain the answers.
Full Interview: futureclass.substack.com/p/j…
I had rear chance to talk to Stani before his project ICO. Very convincing talk.
A teenager pretended to go to school for a year, secretly stayed home to code, and eventually built one of DeFi's biggest protocols.
> Stani Kulechov grew up in Finland. His father saved for about six months to buy the family a computer.
> Stani became obsessed with programming and spent a year pretending to go to school while secretly staying home to code.
> He eventually studied law at the University of Helsinki, but discovering Ethereum changed his plans.
> He saw how smart contracts could make financial services work without traditional intermediaries.
> In 2017, he launched ETHLend, a project that let people lend and borrow cryptocurrency through Ethereum.
> The idea evolved into Aave, which launched in 2020.
> He kept building, and Aave grew into one of DeFi's biggest lending protocols.
> Then, in April 2026, an exploit at Kelp DAO sent shockwaves through DeFi.
> The attacker used some of the stolen rsETH as collateral on Aave to borrow other assets, exposing the protocol to a major bad-debt crisis.
> Aave itself hadn't been hacked, but it was caught in the fallout.
> Stani pledged 5,000 ethereum:native toward the wider recovery effort.
> A teenager who secretly stayed home to code went on to build one of DeFi's biggest financial platforms.
> Years later, when a crisis hit the ecosystem around it, he stepped up to support the recovery.
Imagine if he'd stopped coding and followed the path everyone expected of him.
Jacek (Jomsborg.eth) retweeted
Personal update: Turns out that what I thought was leaving OpenAI became more of a sabbatical.
When I left a few months ago, I felt that the most important thing to focus on was making AI more useful to people. But we’ve since entered a different regime of AI progress. One in which getting the safety and security challenges of increasingly capable AI right has to become a central priority.
So I’ll be returning to OpenAI, joining @merettm to help chart a path through these challenges.
There’s much work to do, so let’s get going.