# AI is solving science's hardest problems

> AI models have jumped from solving 2 percent to 35 percent of theoretical physics and maths problems in just two years, upending multiple scientific fields.
- Title: AI is solving science's hardest problems · WIRED | Shortify
- Summary: AI models have jumped from solving 2 percent to 35 percent of theoretical physics and maths problems in just two years, upending multiple scientific fields…
- Keywords: artificial intelligence, mathematics, theoretical physics, neil thompson, openai, scientific research, solving, science's, hardest, problems, WIRED
- Source: WIRED — https://wired.com/story/ai-is-coming-for-science-next-watch-out
- Author: Will Knight
- Published: 2026-10-14T18:15:00+00:00
- Read time: 1 min
- Topics: artificial intelligence, mathematics, theoretical physics, neil thompson, openai, scientific research
## AI is automating theoretical science
Neil Thompson, who studies computing progress at MIT, presented evidence that AI will soon upend probability, statistics, economics, physics and cosmology.
## Dramatic progress in two years
Between mid-two thousand twenty-four and mid-two thousand twenty-six, the best AI models improved from solving about two percent of theoretical problems to about thirty five percent.
## Thompson's study tested real solutions
Thompson, Gabriel Manso and Claudio Mayrink Verdun tested OpenAI models o one, o three, GPT-five and later versions on problems from papers published after the models' training cutoff.
## Math world already shaken
In September, OpenAI announced an unreleased model had solved Navier-Stokes, a long-standing grand challenge in mathematics concerning fluid motion equations.
## Mathematicians worry about the process
Some mathematicians have called for limits on AI use, warning that the process of solving problems is often as useful as having the final answer.

> the process of solving problems is often as useful as having the final answer
## Experts still needed to verify
Gabriel Manso says theorists will remain essential to generate ideas and verify solutions, as AI models can make mistakes and present wrong answers confidently.

> We are still going to need people to generate good ideas to connect the dots
## Key takeaway

AI is rapidly automating theoretical work across physics, maths and economics, forcing scientists to rethink how they solve problems and verify solutions.