Terence Tao · 2026-10-06 · notable
Terence Tao — 'Math 2.0' must reward more than solving problems
Terence Tao argues that a "Math 2.0" shaped by AI should value exposition, community building and new research directions, not just being first to solve an open problem, and calls for new rules for publishing and careers.
Terence Tao says AI-era math must stop rewarding only the first solver of a problem.
What is it?
"Math 1.0" vs "Math 2.0" is a four-part Mathstodon thread by Terence Tao, posted on October 6. Tao contrasts the old system, where a breakthrough proof led to talks, workshops, new collaborators and textbook versions, with what he sees happening as AI tools solve open problems.
How does it work?
The thread builds the argument in steps. Tao says AI could support follow-up work, but is often used by prompters who solve problems without engaging with the field, so fewer seminars happen and fewer newcomers join. Because a solved problem cannot be unsolved, he argues, open problems are being harvested in a way that leaves parts of mathematics less fertile.
Why does it matter?
Tao proposes that "Math 2.0" should reward exposition, community building and opening new directions, and that AI can help with all of these if used with more imagination than pointing an agent at open problems. He calls on the community to change its criteria for education, publication and career advancement.
Who is it for?
mathematicians, research leaders, people building AI-for-math tools