When I use GPT 5.2 Thinking Extended, it gave me the impression that it's consistent enough/has a low enough rate of errors (or enough error correcting ability) to autonomously do math/physics for many hours if it were allowed to [but I guess the Extended time cuts off around 30 minute mark and Pro maybe 1-2 hours]. It's good to see some confirmation of that impression here. I hope scientists/mathematicians at large will be able to play with tools which think at this time-scale soon and see how much capabilities these machines really have.
This result reminded me of the C compiler case that Anthropic posted recently. Sure, agents wrote the code for hours but there was a human there giving them directions, scoping the problem, finding the test suites needed for the agentic loops to actually work etc etc. In general making sure the output actually works and that it's a story worth sharing with others.
The "AI replaces humans in X" narrative is primarily a tool for driving attention and funding. It works great for creating impressions and building brand value but also does a disservice to the actual researchers, engineers and humans in general, who do the hard work of problem formulation, validation and at the end, solving the problem using another tool in their toolbox.
So I would read this (with more information available) with less emphasize on LLM discovering new result. The title is a little bit misleading but actually "derives" being the operative word here so it would be technically correct for people in the field.
Not saying they're lying, but I'm sure it's exaggerated in their own report.
Okay read it: Yep Induction. It already had the answer.
Don't get me wrong, I love Induction... but we aren't having any revolutions in understanding with Induction.
I expect lots of derivations (new discoveries whose pieces were already in place somewhere, but no one has put them together).
In this case, the human authors did the thinking and also used the LLM, but this could happen without the original human author too (some guy posts some partial on the internet, no one realizes is novel knowledge, gets reused by AI later). It would be tremendously nice if credit was kept in such possible scenarios.
Theoretical physics is throwing a lot of stuff at the wall and theory crafting to find anything that might stick a little. Generation might actually be good there, even generation that is "just" recombining existing ideas.
I trust physicists and mathematicians to mostly use tools because they provide benefit, rather than because they are in vogue. I assume they were approached by OpenAI for this, but glad they found a way to benefit from it. Physicists have a lot of experience teasing useful results out of probabilistic and half broken math machines.
If LLMs end up being solely tools for exploring some symbolic math, that's a real benefit. Wish it didn't involve destroying all progress on climate change, platforming truly evil people, destroying our economy, exploiting already disadvantaged artists, destroying OSS communities, enabling yet another order of magnitude increase in spam profitability, destroying the personal computer market, stealing all our data, sucking the oxygen out of investing into real industry, and bold faced lies to all people about how these systems work.
Also, last I checked, MATLAB wasn't a trillion dollar business.
Interestingly, the OpenAI wrangler is last in the list of Authors and acknowledgements. That somewhat implies the physicists don't think it deserves much credit. They could be biased against LLMs like me.
When Victor Ninov (fraudulently) analyzed his team's accelerator data using an existing software suite to find a novel SuperHeavy element, he got first billing on the authors list. Probably he contributed to the theory and some practical work, but he alone was literate in the GOOSY data tool. Author lists are often a political game as well as credit, but Victor got top billing above people like his bosses, who were famous names. The guy who actually came up with the idea of how to create the element, in an innovative recipe that a lot of people doubted, was credited 8th
https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.83...
New Honda Civic discovered Pacific Ocean!
New F150 discovers Utah Salt Flats!
Sure it took humans engineering and operating our machines, but the car is the real contributor here!