Final week, I attended a chat at MIT by Neil Thompson, who research progress in computing and artificial intelligence. Over the course of simply half an hour, Thompson made a convincing case that a number of scientific fields are about to be upended by AI.
As mathematicians reel from the best way AI is automating their area, Thompson’s newest research means that likelihood, statistics concept, financial concept, high-energy concept, gravitation and cosmology, and quantum physics could also be subsequent, because of the quickly evolving capabilities of frontier fashions. Between mid-2024 and mid-2026, the research reveals, the most effective AI fashions went from having the ability to appropriately clear up about 2 % of theoretical issues in these fields to about 35 % of such issues. And there are not any indicators that this progress will decelerate.
“Inside just some years, we anticipate quite a lot of concept inquiries to be completely reworked when it comes to AI’s skill to do them,” says Thompson.
Broadly, Thompson’s lab digs into how advances in laptop science impression society and have an effect on innovation. This research—which Thompson carried out alongside Gabriel Manso, a PhD scholar, and Claudio Mayrink Verdun, a analysis scientist—took issues acknowledged in analysis papers posted on-line between December 2025 and Might 2026, after which examined whether or not totally different OpenAI fashions—o1, o3, GPT-5, GPT-5.1, GPT-5.4, and GPT-5.5—might clear up them.
Crucially, options to those issues had been present in papers printed after the coaching cutoff for GPT-5.5 and previous fashions. Which means the fashions they examined needed to work out options for themselves, quite than counting on solutions fed in as coaching knowledge. (Such papers served as floor fact for testing the fashions’ fixing abilities.) The researchers additionally blocked web entry, which prevented the fashions they examined from wanting up options on-line.
The areas lined by the research had been restricted—the trio centered on fields through which AI fashions might determine issues out with no need to run simulations or experiments. However the work means that the sorts of shock waves at the moment being felt in math are prone to ripple out to different math- and theory-heavy areas of scientific inquiry.
Final month, OpenAI rocked the math world by asserting that an unreleased mannequin had solved a long-standing, grand problem in arithmetic generally known as Navier-Stokes, which issues equations that specify the conduct of fluid movement. The episode proved additional controversial after a mathematician at NYU— who had been working with one other educational related to Anthropic—accused OpenAI of gazumping them after studying of their progress.
OpenAI and others have since introduced hundreds more solutions to longstanding math issues, triggering one thing of a disaster within the area. Some mathematicians have called for limits on the use of AI, warning that the method of fixing issues is commonly as helpful as having the ultimate reply.
