Episode

Talking With Azeem Azhar

Podcast
Paul Krugman Podcast
Published
Jun 13, 2026
Duration seconds
2824
Processing state
not_requested
Canonical source
https://paulkrugman.substack.com/p/talking-with-azeem-azhar
Audio
https://api.substack.com/feed/podcast/201847235/3d961c704dc40c81c18d8c95992eec54.mp3
JSON
/v1/public/podcasts/paul-krugman-podcast-7703924/episodes/talking-with-azeem-azhar
Markdown
/podcast/paul-krugman-podcast-7703924/talking-with-azeem-azhar.md

Actions

  • POST https://stenobird.com/v1/public/podcasts/paul-krugman-podcast-7703924/episodes/talking-with-azeem-azhar/transcription-requests
    Idempotently request low-priority transcript generation for this episode.
  • GET https://stenobird.com/podcast/paul-krugman-podcast-7703924/talking-with-azeem-azhar.md
    Read the agent-friendly Markdown representation of this episode resource.

Summary

I last spoke with Azeem, the proprietor of Exponential View, 18 months ago — ancient history on this subject. So we revisited the state of AI. . TRANSCRIPT: Paul Krugman in Conversation with Azeem Azhar (recorded 6/12/26) Paul Krugman: Hi everyone. Paul Krugman back on my usual schedule of recording interviews. And today I’m talking with Azeem Azhar , who I spoke to in January 2025, basically centuries ago in AI time. And with AI on everybody’s mind, I thought it would be good to revisit. I should say Azeem is an independent researcher and founder of Exponential View , which is one of the top tech Substacks out there. So hi, welcome to another conversation. Azeem Azhar: Yeah, thank you, Paul. And it has been eighteen months, also known as one and a half centuries in AI time since we spoke. Krugman : Yeah. Let me ask sort of the dumbest question: what is this thing called AI? How does it do what it does? I mean, even skeptics have to admit that it’s really impressive how it’s sort of leapt over all of the previous barriers. How is this happening? Azhar : You know, I think we’re still figuring it out. I think of AI ultimately as a machine that does certain things, and it’s been built by passing first millions, then billions, then tens of billions, hundreds of billions of trillions of words of human output through a neural network to give it some sense of how humans have thought about the world. And because it operates at dimensions well beyond the form of space and time, it seems to be able to find relationships between quite complex concepts. And I think we’ve all had that experience, whether we’ve been using Chat GPT or Claude over the last two or three years, that it seems to be able to recognize things that are quite deeply related that don’t immediately spring to mi…