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OpenAI cofounder Greg Brockman on the scaling hypothesis and refactoring as a killer AI use case

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Manage episode 489546979 series 3672576
Content provided by Stripe. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stripe or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Greg Brockman—OpenAI cofounder and Stripe's first engineer—joins John Collison to talk about research-driven product development, an early moment he thought OpenAI was doomed, S curves in AI advancement, and energy bottlenecks.

Timestamps

(00:00) Intro

(02:51) Was OpenAI the first company to take the scaling hypothesis seriously?

(04:53) Lessons from Dota about deep learning

(08:08) What is a good new Turing test?

(08:57) Personalization in AI

(09:57) Research-driven product development

(10:26) An early moment OpenAI felt doomed

(15:01) OS limits on AI product development

(17:59) When will AI make novel advancements in math or science?

(20:03) Energy bottlenecks

(22:30) S curves in AI advancement

(24:00) AI coding

(26:25) Refactoring as a killer AI use case

(27:26) How OpenAI decides what products to built

(28:53) Growing up in North Dakota

(30:17) How far away is AGI?

  continue reading

5 episodes

Artwork
iconShare
 
Manage episode 489546979 series 3672576
Content provided by Stripe. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stripe or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Greg Brockman—OpenAI cofounder and Stripe's first engineer—joins John Collison to talk about research-driven product development, an early moment he thought OpenAI was doomed, S curves in AI advancement, and energy bottlenecks.

Timestamps

(00:00) Intro

(02:51) Was OpenAI the first company to take the scaling hypothesis seriously?

(04:53) Lessons from Dota about deep learning

(08:08) What is a good new Turing test?

(08:57) Personalization in AI

(09:57) Research-driven product development

(10:26) An early moment OpenAI felt doomed

(15:01) OS limits on AI product development

(17:59) When will AI make novel advancements in math or science?

(20:03) Energy bottlenecks

(22:30) S curves in AI advancement

(24:00) AI coding

(26:25) Refactoring as a killer AI use case

(27:26) How OpenAI decides what products to built

(28:53) Growing up in North Dakota

(30:17) How far away is AGI?

  continue reading

5 episodes

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