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Terence Tao Explains The Math Behind AI

2026-06-06 Science & Technology
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Dr Brian Keating
Dr Brian Keating
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Description

Terence Tao has read more mathematics than almost anyone alive, and he uses AI tools every day. So when one of the most cited mathematicians on Earth says these systems still can't ask a genuinely new question, it's worth understanding exactly where he draws the line — because it isn't where the headlines put it. Watch the full conversation: https://youtu.be/ukpCHo5v-Gc If AI has absorbed every textbook ever written, why can't it discover anything new? Tao, a Fields Medal winner and professor at UCLA, separates what these systems do brilliantly from what they can't do at all, and the boundary turns out to be sharper and stranger than most people assume. We cover why reproducing a famous proof is less impressive than it sounds, what a neural network found hidden inside a million knots that humans had missed, why we still can't predict which tasks AI will actually be good at, the "Keating Test" — the benchmark that would actually demonstrate machine thought — and where exhaustive recall ends and real conceptual origination begins. AI can pass every exam. It just can't ask a question nobody has asked before — yet. Chapters: 00:00 The question AI can't ask 00:48 Read every textbook, discover nothing 01:42 Why a reproduced proof proves less 02:39 A million knots, one hidden pattern 03:54 The competence we still can't predict 05:11 The Keating Test for machine thought 06:18 Where recall ends and discovery begins 📬 Get the transcript, fascinating bonus content, and my Monday M.A.G.I.C. Message: https://briankeating.com/yt 🌠 Have a .edu email and live in the USA 🇺🇸? You automatically win a meteorite: https://BrianKeating.com/edu 🔔 Subscribe: https://www.youtube.com/DrBrianKeating?sub_confirmation=1 🎯 Support Into the Impossible on Patreon — get my weekly M.A.G.I.C. Message, unfiltered bonus content, and live monthly Office Hours with me: https://www.patreon.com/drbriankeating ⭐ Join this channel for perks, monthly Office Hours, and your name in the Member Roster at the end of every episode: https://www.youtube.com/channel/UCmXH_moPhfkqCk6S3b9RWuw/join 📚 My books: Losing the Nobel Prize (memoir): http://amzn.to/2sa5UpA Think Like a Nobel Prize Winner: https://a.co/d/03ezQFu Focus Like a Nobel Prize Winner: https://a.co/d/hi50U9U Galileo's Dialogue (first-ever audiobook): https://a.co/d/iZPi9Un 🌐 More: 🏄‍♂️ Twitter: https://twitter.com/DrBrianKeating 📚 Substack https://briankeating.substack.com/ss ✍️ Blog: https://briankeating.com/blog 🎙️ Audio-only: https://briankeating.com/podcast #intotheimpossible #briankeating #science #physics #astronomy #cosmology #podcast #universe

Top Comments (10)

@DrBrianKeating 2026-06-06

Terence Tao has read more math than almost anyone alive and uses AI daily. He still says it can't ask a question nobody has asked before. Not "can't yet." Can't. Do you agree?

44 46 replies
@bitsculptor 2026-06-06

What's up with all the strange, short cuts with visible transitions directly in the middle of sentence. It looks very unusual. Channels that typically use excessive cuts as an editing "style" usually do it between sentences... not mid sentence.

35 3 replies
@newpilgrim 2026-06-06

I feel like I get a peek (an incomprehensible peek) at how quickly your mind works, Dr. Tao. Thanks to you both!

20 1 replies
@HaroldKatcher-w4t 2026-06-06

What a gift to humanity is Dr. Tao.

15
@behrad9712 2026-06-06

Thank you so much!🙏

2 1 replies
@inspo_expo 2026-06-06

It's a similarity engine at least for LLMs. Just an optimizer for statistical problems. So you CAN ask it to judge a new idea and it will do a good job. And a small amount of time it will come up with it's own idea tweaks that are good

2
@LukeAvedon 2026-06-10

Can confirm: AI has ALREADY turned me into a paper clip.

2
@markmarkmark08 2026-06-06

Great interview! Thank you, Prof. Keating! 🫡🫡🫡

1 1 replies
@seanrodgers1839 2026-06-23

A long time ago, in university, I had a brief look into the math that is now used in AI. It was kind of like magic; it found patterns in what seemed like transform data.

1 1 replies
@LauralynThrockmorton-i9c 2026-06-17

I loved your master class!!! I learned how to find an earring in a vacuum bag. Just take half out, shake it, etc. Just like you said in the master class 😂

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