The Peterman Pod

Sergey Levine is one of the world's top robotics researchers and co-founder of Physical Intelligence. We talked about where humanoid robotics is today, thoughts on the Chinese robotics ecosystem, and his predictions for future timelines.

• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/
• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done

Podcast links:

• YouTube: https://youtu.be/9OSbaPjv0Rc
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/sergey-levine-current-state-of-humanoid?r=n49ky

Thank you to this episode's sponsor 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 https://workos.com/

Timestamps:

(00:00) Intro
(00:37) Where are we today
(04:20) Most surprising capabilities so far
(07:03) The most inspiring real world robotics
(08:36) If OpenAI or Anthropic got into robotics
(10:22) Chinese robotics
(13:15) Will one lab breakout from the rest
(16:59) Thoughts on a concrete roadmap
(21:03) Generalization and demonstrating it
(26:04) Types of data and which is best for robotics
(34:34) Why humanoid robotics differs from Waymo
(37:10) If humanoid robotics failed here is why
(39:55) Are there hot take modeling architectures in robotics
(42:05) Thoughts on AI safety in robotics
(46:44) Top robotics research paper recommendation
(49:35) Why is Boston Dynamics less top of mind
(53:47) Advice for his younger self
(56:42) Outro

Where to find Sergey:

• Google Scholar: https://scholar.google.com/citations?user=8R35rCwAAAAJ&hl=en
• Website: https://people.eecs.berkeley.edu/~svlevine/
• Wikipedia: https://en.wikipedia.org/wiki/Sergey_Levine
• X/Twitter: https://x.com/svlevine?lang=en
• LinkedIn: https://www.linkedin.com/in/sergey-levine-5a31a24/

Where to find Ryan:

• Newsletter: https://www.developing.dev/
• X/Twitter: https://x.com/ryanlpeterman
• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/
• Threads: https://www.threads.com/@ryanlpeterman
• Instagram: https://www.instagram.com/ryanlpeterman
• TikTok: https://www.tiktok.com/@ryanlpeterman

Referenced in this episode:

• Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware (ALOHA / ACT paper): https://arxiv.org/abs/2304.13705
• Emergence of Human to Robot Transfer in Vision-Language-Action Models: https://arxiv.org/abs/2512.22414
• Summary of human to robot paper: https://www.pi.website/research/human_to_robot

Anders Hejlsberg is the creator of TypeScript and C#, and I asked him about how the TypeScript compiler got 10x faster through a rewrite in Go and his thoughts on how AI has impacted software engineering.

• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/
• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done

Podcast links:

• YouTube: https://www.youtube.com/watch?v=cywK3XYYJ2o
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/creator-of-typescript-10x-faster

Thank you to this episode's sponsors 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 https://workos.com/
• Jira by Atlassian: Get more work done with your favorite agents and models all in one place, check them out at https://jira.dev/

Timestamps:

(00:00) Intro
(00:48) Why write a compiler in JavaScript
(07:29) Why rewrite the compiler in Go
(14:49) LLMs for large migrations
(20:12) Why Javascript is so popular
(26:32) Why ever use Javascript on the backend
(32:59) What it takes to build a programming language
(37:06) Will there be fewer languages in 10 years
(42:57) Hands on engineering vs delegation
(49:14) Why fast tooling matters more now
(51:16) AI software engineering predictions
(58:52) The most technically challenging work
(01:02:04) Top book recommendation
(01:03:50) Advice for his younger self
(01:05:00) Outro

Where to find Anders:

• GitHub: https://github.com/ahejlsberg
• X/Twitter: https://x.com/ahejlsberg
• Wikipedia: https://en.wikipedia.org/wiki/Anders_Hejlsberg
• LinkedIn: https://www.linkedin.com/in/ahejlsberg/

Where to find Ryan:

• Newsletter: https://www.developing.dev/
• X/Twitter: https://x.com/ryanlpeterman
• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/
• Threads: https://www.threads.com/@ryanlpeterman
• Instagram: https://www.instagram.com/ryanlpeterman
• TikTok: https://www.tiktok.com/@ryanlpeterman

Referenced in this episode:

• Flow type checker repository: https://github.com/facebook/flow
• TypeScript compiler repository: https://github.com/microsoft/TypeScript
• Algorithms + Data Structures = Programs (book): https://en.wikipedia.org/wiki/Algorithms_%2B_Data_Structures_%3D_Programs
• TypeScript native rewrite: https://devblogs.microsoft.com/typescript/announcing-typescript-7-0/

Leonardo de Moura is the creator of Lean and the Z3 theorem prover. I talked with him about how Lean works and why LLMs plus Lean will fundamentally change how we write software and do math.

• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/
• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done

Podcast links:

• YouTube: https://youtu.be/KzdYKeAqWhY
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/creator-of-lean-the-end-of-handwritten

Thank you to this episode's sponsor 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 https://workos.com/

Timestamps:

(00:00) Intro
(00:28) How formal verification works
(05:21) A new way of writing software
(13:15) Proof assistants vs programming languages
(21:06) How Lean has assisted in mathematical breakthroughs
(32:03) When is it worth formalizing software
(33:29) How Lean will impact handwritten math
(38:55) The Z3 theorem prover project he started
(45:44) The most technically challenging work of his career
(51:10) Lean vs its competitors
(01:00:37) The future of Lean
(01:04:10) Technical book recommendations
(01:06:15) Advice for his younger self
(01:07:10) Outro

Where to find Leonardo:

• Wikipedia: https://en.wikipedia.org/wiki/Leonardo_de_Moura
• Website: https://leodemoura.github.io/
• GitHub: https://github.com/leodemoura
• LinkedIn: https://www.linkedin.com/in/leonardo-de-moura-26a27b5/
• X/Twitter: https://x.com/Leonard41111588

Where to find Ryan:

• Newsletter: https://www.developing.dev/
• X/Twitter: https://x.com/ryanlpeterman
• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/
• Threads: https://www.threads.com/@ryanlpeterman
• Instagram: https://www.instagram.com/ryanlpeterman
• TikTok: https://www.tiktok.com/@ryanlpeterman

Referenced in this episode:

• Lean 4: https://github.com/leanprover/lean4
• Mathlib: Lean Mathematical Library: https://github.com/leanprover-community/mathlib4
• Lean4Lean: https://github.com/digama0/lean4lean
• Liquid Tensor Experiment: https://xenaproject.wordpress.com/2020/12/05/liquid-tensor-experiment/
• Veil protocol verification language: https://veil.dev/
• Z3 theorem prover: https://github.com/Z3Prover/z3
• seL4 formally verified microkernel: https://github.com/seL4/seL4

Roberto Ierusalimschy is the creator of the Lua programming language. I interviewed him about Lua's unique strengths, programming language design and predictions for how AI will impact programming languages.

• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/
• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done

Podcast links:

• YouTube: https://youtu.be/jCZnFKk6M9A
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/creator-of-lua-scripting-programming

Thank you to this episode's sponsor 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 https://workos.com/

Timestamps:

(00:00) Intro
(00:43) What sets Lua apart
(08:35) Comparing Lua with Python
(13:04) Top book recommendation on language design
(14:20) How JIT works and why it is hard
(23:21) Compiling Python and interpreting C
(30:31) How cross language calls work
(36:58) Lua unique design decisions
(51:17) Predictions for AIs impact on languages
(01:00:10) Top 3 languages to learn to become a better engineer
(01:03:21) Advice for his younger self
(01:04:19) Outro

Where to find Roberto:

• Website: https://www.inf.puc-rio.br/~roberto/
• Wikipedia: https://en.wikipedia.org/wiki/Roberto_Ierusalimschy

Where to find Ryan:

• Newsletter: https://www.developing.dev/
• X/Twitter: https://x.com/ryanlpeterman
• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/
• Threads: https://www.threads.com/@ryanlpeterman
• Instagram: https://www.instagram.com/ryanlpeterman
• TikTok: https://www.tiktok.com/@ryanlpeterman

Referenced in this episode:

• The Evolution of Lua: https://www.lua.org/doc/hopl.pdf
• LuaJIT: https://luajit.org/
• How much does it cost: https://www.youtube.com/watch?v=EUvgoxBm7uc
• JavaScript: The Good Parts (not an affiliate link): https://www.amazon.com/dp/0596517742

Judea Pearl is a Turing Award winner and a pioneer in artificial intelligence and causal reasoning. We talked about how he got into science, his major breakthroughs and his predictions for AI today.

• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/
• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done

Podcast links:

• YouTube: https://youtu.be/FleTXB1fAcQ
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/turing-award-winner-early-ai-llm

Thank you to this episode's sponsor 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 https://workos.com/

Timestamps:

(00:00) Intro
(00:54) How he got into AI
(11:17) Greatest scientist of all time
(20:15) What people thought of AI in the 80s
(26:23) Entering academia and researching AI
(34:52) The invention of Bayesian networks
(46:28) Pioneering work in causality
(55:38) The causal hierarchy
(59:34) LLMs and predictions
(01:20:12) A restless mind pays
(01:24:36) Advice for his younger self
(01:26:37) Outro

Where to find Judea:

• X/Twitter: https://twitter.com/yudapearl
• Website: https://bayes.cs.ucla.edu/jp_home.html
• Wikipedia: https://en.wikipedia.org/wiki/Judea_Pearl

Where to find Ryan:

• Newsletter: https://www.developing.dev/
• X/Twitter: https://x.com/ryanlpeterman
• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/
• Threads: https://www.threads.com/@ryanlpeterman
• Instagram: https://www.instagram.com/ryanlpeterman
• TikTok: https://www.tiktok.com/@ryanlpeterman

Referenced in this episode:

• The Book of Why: https://en.wikipedia.org/wiki/The_Book_of_Why
• Bayesian networks: https://en.wikipedia.org/wiki/Bayesian_network
• Alpha-beta pruning: https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning
• Pearl vortex: https://en.wikipedia.org/wiki/Pearl_vortex
• Graphoid: https://en.wikipedia.org/wiki/Graphoid
• Causality: Models, Reasoning, and Inference: https://en.wikipedia.org/wiki/Causality_(book)
• Coexistence and Other Fighting Words: Selected Writings of Judea Pearl, 2002–2025: https://bayes.cs.ucla.edu/COEXISTENCE/