The metric is simple and computable with Lean:
interestingness = proof difficulty / description length ≈ easy to state, hard to prove.
On mathlib, the ranking is intuitive: trivial identities score low, while variants of Fermat’s Last Theorem score near the top.
More surprisingly, interestingness predicts downstream utility: ρ = 0.756. [2/5]
BREAKING: Anthropic’s new wet lab produces its first discovery, with nearly 1,000 Claude agents autonomously uncovering a novel enzyme system after 21 hours of work.
if you are a squirrel whose life's work rests at the base of a very large, very old tree that is slowly falling, there is nothing you can do but soften the inevitable blow. adapt or lose !
The rumors were true once again; they are sitting on multiple major announcements. Open AI announced this morning that the unnamed internal model involved with Navier-Stokes has resolved more than 100 long-standing open problems across most areas of mathematics.
Jascha Sohl-Dickstein has an amazing blog post showing that the boundary between hyperparameter settings where neural network training succeeds and fails has a fractal structure.
The visualizations are mesmerizing.
https://t.co/j6xb3kNXzl
People clowning on him don’t understand what he’s saying.
All the wealth of humanity to date supports perhaps 250k living math phds. Roughly the population of St. Louis, Missouri.
The training pipeline for that group has been irreparably shattered in the last month.
A phd is supposed to make an original contribution to their field to graduate.
That’s just…. not possible anymore.
938 years after the founding of the first university in Bologna…
Do universities now reward… teaching ? comprehension of something discovered by a machine? application ? do mathematicians become quotidian (gasp of disgust) engineers?
Tao is upset because he knows none of those outside the field care about its future. He is a horrified gardener watching humanity gorge on its seed corn.
It is irreparable of course. The old way is dead dead.
We live in the short interregnum before the new king is born: a Lean crawler that spawns a billion copies exploring every corner of math latenspace.
So much math to understand that even if 8 billion humans had the ability of the 250k mathematicians alive today, it would still take a million years to comprehend.
It is ironic and sad.. because Tao himself is a pioneer of collaborative math: math that is understood by a combination of minds rather than an pindividual.
The tools that Tao began exploring a few years ago, solving problems through blog posts and using Lean to guarantee each mind’s contribution stood on its own when assembled into the greater truth, have been turned against him.
Math’s path to utilize multiple minds didn’t restrict access to human minds, and now the machines have blitzkrieged themselves into the heart of the matter.
The agents use rudimentary message boards, working 10,000 to a task, tirelessly, using Lean to verify the correctness of each contribution.
It was good while it lasted… and now it’s gone.