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Scott Aaronson

Professor of computer science, UT Austin

Real Alpha has cut 9 moments of Scott Aaronson (Professor of computer science, UT Austin) talking, from 2 interviews on MTS and The Peterman Pod, the latest published Oct 17, 2026.

What Scott Aaronson said

  1. MTS · · 6 min

    AI crossed long-standing limits in multiplication and Fourier transforms

    “many of us believed that that was going to be the ultimate limit for how fast you could multiply two numbers.”
    Scott Aaronson15:55
  2. MTS · · 8 min

    Mathematicians need to understand AI proofs, not dismiss them

    “we do need to digest these things and understand them and produce humanly comprehensible explanations of these results.”
    Scott Aaronson11:12
  3. MTS · · 3 min

    AI solved research problems Aaronson had left untouched for 25 years

    “some of the open problems for my papers 25 years ago, and just boom, boom, boom”
    Scott Aaronson34:48
  4. MTS · · 4 min

    Researchers are racing to understand OpenAI's new proofs

    “actual experts, you know, are mostly just rushing to understand the new, you know, theorems that have just dropped on us.”
    Scott Aaronson4:11
  5. MTS · · 5 min

    Aaronson teaches alignment through competing perspectives

    “But actually, next week, we're going to be reading papers that take a much more skeptical perspective.”
    Scott Aaronson22:48
  6. MTS · · 8 min

    Teach fundamentals, but emphasize students' own questions

    “those kinds of soft skills, right, those are going to be where we have an advantage for the longest”
    Scott Aaronson33:41
  7. The Peterman Pod · · 5 min

    Why AI is best at finding counterexamples to conjectures

    Aaronson explains that AI excels at disproving long-held conjectures because it has no preconceptions and the search parallelizes. He then shows how critics keep moving the goalposts.

  8. The Peterman Pod · · 4 min

    Why AI disclosure matters: the path to a proof is the value

    “You care not just about the destination, but about the journey, right? How did you get there okay”
    Scott Aaronson29:32
  9. The Peterman Pod · · 4 min

    OpenAI's $15M Navier-Stokes proof and how credit will work

    “They put like 15 million dollars of compute into solving this one million dollar problem.”
    Scott Aaronson16:17

The 2 episodes