Terence Tao on Dwarkesh Patel: How Erdős Problems Exposed AI

ℹ️ EPISODE INFO

Released

March 20, 2026

Duration

1h 23m

Channel

Dwarkesh Podcast

Watch on YouTube

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📝 EPISODE DESCRIPTION

We begin the episode with the absolutely ingenious and surprising way in which Kepler discovered the laws of planetary motion. People sometimes say that AI will make especially fast progress at scientific discovery because of tight verification loops. But the story of how we discovered the shape of our solar system shows how the verification loop for correct ideas can be decades (or even millennia) long. During this time, what we know today as the better theory can often actually make worse predictions (Copernicus's model of circular orbits around the sun was actually less accurate than Ptolemy's geocentric model). And the reasons it survives this epistemic hell is some mixture of judgment and heuristics that we don’t even understand well enough to actually articulate, much less codify into an RL loop. Hope you enjoy! 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒

• Transcript: https://www.dwarkesh.com/p/terence-tao
• Apple Podcasts: https://podcasts.apple.com/us/podcast/terence-tao-kepler-newton-and-the-true/id1516093381?i=1000756353875
• Spotify: https://open.spotify.com/episode/24xF8YGra2w3HXZYbhgVKU?si=U5V-SgvSQ8eVIcG2Z86wfQ

𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒

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To sponsor a future episode, visit https://dwarkesh.com/advertise. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00:00 – Kepler was a high temperature LLM 00:11:44 – How would we know if there’s a new unifying concept within heaps of AI slop? 00:26:10 – The deductive overhang 00:30:31 – Selection bias in reported AI discoveries 00:46:43 – AI makes papers richer and broader, but not deeper 00:53:00 – If AI solves a problem, can humans get understanding out of it? 00:59:20 – We need a semi-formal language for the way that scientists actually talk to each other 01:09:48 – How Terry uses his time 01:17:05 – Human-AI hybrids will dominate math for a lot longer

🎤 SPEAKERS

• Dwarkesh Patel

  host

  Podcast host and interviewer of the Dwarkesh Patel podcast.

• Terence Tao

  guest

  Mathematician and UCLA professor known for work across analysis, number theory, and related fields.

🧾 EPISODE SUMMARY

In this episode of Dwarkesh Podcast, featuring Dwarkesh Patel and Terence Tao, Terence Tao on Dwarkesh Patel: How Erdős Problems Exposed AI explores terence Tao on AI math: verification, depth, and new workflows Kepler’s laws illustrate how massive hypothesis generation only matters when paired with high-quality data and rigorous verification, and AI similarly drives the cost of idea generation toward zero while shifting the bottleneck to validation and filtering.

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