AI Is Solving Math's Best Problems Faster Than They Can Be Replaced, Terence Tao Warns
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Terence Tao, the UCLA professor widely considered the best living pure mathematician, has sounded the alarm over the accelerating AI race in math happening right now.
Key facts
- Tao, who was awarded the Fields Medal in 2006, posted a warning on the math-centric Mastodon instance Mathstodon yesterday in which he argued AI is draining the field's supply of good open problems
- In May, an OpenAI model disproved the Erdős unit-distance conjecture, an 80-year-old question about how many pairs of points on a plane can sit exactly one unit apart
- As with all 4 minute miles, they had to try and cross it too
- Huge credit to the OAI team for solving the unit distance problem with 5.5 — it is now their go to example that models can in fact pull together disparate ideas into new discoveries
Summary
Terence Tao argued that AI is depleting the supply of fruitful open math problems faster than mathematicians can identify new ones. His warning follows a real precedent of AI labs solving historically hard problems. Tao wants mathematicians to label certain problems "analysis-required," so a bare AI-generated answer without explained reasoning counts for little. Tao, who was awarded the Fields Medal in 2006, posted a warning on the math-centric Mastodon instance Mathstodon yesterday in which he argued AI is draining the field's supply of good open problems, the unsolved questions that push math forward.