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Ryan Peterman

@ryanlpeterman • 30,140 subscribers

Quit my job to build the podcast & ergonomic keyboard I wish existed • ex-software engineer @instagram, @meta • See what I'm building here ↓

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The singularity has already begun for math: Scott Aaronson is one of the world's leading quantum computing researchers and spent two years at OpenAI working on AI safety. We talked about why he thinks the singularity has already begun for math, who gets credit when AI writes the proof, and whether intelligence will still matter once machines do the thinking. In this episode: • Why the singularity has already begun for math • Who gets credit when AI writes the proof • What a proof that P = NP would be worth • Why he turned down getting rich to keep blogging • Whether intelligence will still matter Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:34 Why he updated so hard on AI 01:14 The people still denying AI progress 03:53 The singularity has already begun for math 08:30 Will human-driven math research survive 13:12 Who gets credit for AI-written papers 15:55 OpenAI's $15M Navier-Stokes proof 19:20 What if AI proved P = NP 23:07 Why AI is so good at finding counterexamples 26:13 The goalposts keep moving 28:52 Why AI disclosure matters in research 32:59 The fake Monet experiment 35:23 Why he blogs instead of getting rich 39:45 Are AI labs racing too fast 42:01 Will intelligence still matter 47:12 Book recommendations 52:27 Advice for students today 57:23 Reacting live to a new AI result 59:58 Outro

Ryan Peterman

78,801 görüntüleme • 19 gün önce

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My goal was to record a conversation completely free of "AI doomer" takes as a timeline cleanser. For this episode, I interviewed Casey Muratori (Casey Muratori) who is a video game developer and programming creator also known for his talks about the history of computing. In this episode: • Surprising findings in computer history • Where bad code comes from • The only unbreakable law in software engineering • His career in the video game industry • Why you should read technical papers Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsors of this episode for supporting my work: • Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 01:08 Digging into computer science history 04:08 What shocked him 16:23 Dijkstra was depressed 26:17 The personal side of goto considered harmful 35:09 The anatomy of a 35 year mistake 50:12 Clean code horrible performance 58:33 How to write high performance code 01:01:18 Where bad code comes from 01:06:37 Why design docs before code is a bad idea 01:09:20 The only unbreakable law in software engineering 01:15:57 How he got into programming 01:21:16 Why he didnt work in big tech 01:30:44 Should you work at a startup early on 01:34:52 What video game engineering is like 01:39:57 Why preventing recursion is reasonable 01:43:24 Is vibe coding bad for the industry 01:50:17 Technical reading recommendation 01:54:27 Advice for his younger self 01:56:54 Outro

Ryan Peterman

62,932 görüntüleme • 1 ay önce

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Thariq Shihipar (Thariq) is an engineer on Anthropic’s Claude Code team I asked him how Anthropic makes the most out of the models for engineering and how the industry will change soon. In this episode: • Internal best practices in leveraging the models • What percent of Anthropic's work is fully autonomous • How Anthropic maintains higher volumes of code • What has worked in preventing AI-written breakages Where to watch: • YouTube - • Spotify - • Apple Podcasts - • Transcript - Thank you to the sponsor of this episode for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at Chapters: 00:00 Intro 00:29 Onboarding at Anthropic 02:53 Internal capabilities vs external perception 06:16 Model vs Harness 08:55 What percent of Anthropics changes are fully autonomous 14:51 Computer use 17:42 How to make the most out of your compute 20:45 Loop engineering 22:47 Where the industry will go soon 26:02 Which model do Anthropic engineers use 27:38 Is learning a particular model worth it 30:56 Prompting tips for todays models 35:04 How to get the models to do tasteful work 39:00 How much of writing is done by AI at Anthropic 45:36 Code ownership and maintenance at Anthropic 52:04 How Anthropic prevents breakages 55:24 Visibility and sharing your work 58:42 Luck surface area example 01:00:57 Should people still learn to code 01:07:42 Advice for his younger self 01:09:58 Outro

Ryan Peterman

65,784 görüntüleme • 1 ay önce