58 episodes
Turing Award Winner: TPU vs GPU vs CPU, Computer Architecture, RISC vs CISC | David Patterson
13/07/2026 | 59 mins.David Patterson is a Turing Award winner famous for his contributions to computer architecture. I interviewed him about his past work, thoughts on GPU/TPUs and career advice from half a century of experience.
• 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/Pn4ZwlEh5nw
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/turing-award-winner-tpu-vs-gpu-vs?r=n49ky
Timestamps:
(00:00) Intro
(00:42) RISC vs CISC
(12:51) Compilers
(17:38) GPUs
(23:07) GPU vs TPU vs CPU
(32:12) Is Moores law dead?
(38:04) GPU benchmarks
(41:40) How to have a bad career
(49:59) Courage and optimism
(55:56) Advice for his younger self
(58:15) Outro
Where to find David:
• Wikipedia: https://en.wikipedia.org/wiki/David_Patterson_(computer_scientist)
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:
• AlexNet paper: https://proceedings.neurips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf
• David Patterson's “How to Have a Bad Career” talk: https://www.youtube.com/watch?v=Rn1w4MRHIhc
• “Life Lessons from the First Half-Century of My Career”: https://cacm.acm.org/opinion/life-lessons-from-the-first-half-century-of-my-career/
• The 7 Habits of Highly Effective People (book): https://en.wikipedia.org/wiki/The_7_Habits_of_Highly_Effective_People
• Working (book): https://en.wikipedia.org/wiki/Working_(Terkel_book)Turing Award Winner: NSA, Public Key Cryptography, Crypto Wars | Martin Hellman
06/07/2026 | 1h 1 mins.Martin Hellman is a Turing Award winner who helped to invent public-key cryptography against the NSA's wishes. I interviewed him all about his work and why it broke the law at the time.
• 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/AZLOETBCQM4
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/turing-award-winner-nsa-public-key
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
(00:34) Why his work broke the law
(08:39) How people did encryption before
(18:51) The crypto wars
(26:22) The story behind Diffie Hellman key exchange
(36:48) Signatures vs key exchange
(43:05) RSA patent wars
(48:08) Why inventions happen at similar times
(50:29) What he worked on after cryptography
(57:31) His thoughts on death
(59:40) Advice for his younger self
(01:00:45) Outro
Where to find Martin:
• Wikipedia: https://en.wikipedia.org/wiki/Martin_Hellman
• Website: https://ee.stanford.edu/~hellman/
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:
• Martin Hellman's “The Evolution of Public Key Cryptography”: https://www.youtube.com/watch?v=Tev3tVzH91s
• Keys Under Doormats: https://cacm.acm.org/opinion/keys-under-doormats/
• Cryptography's Role in Securing the Information Society (CRISIS report): https://nap.nationalacademies.org/catalog/5131/cryptographys-role-in-securing-the-information-society
• Secure Communications Over Insecure Channels: https://doi.org/10.1145/359460.359473
• New Directions in Cryptography: https://doi.org/10.1109/TIT.1976.1055638MIT Complexity Theorist: Why You Can Do Better Than “Optimal” On Leetcode & SAT | Ryan Williams
29/06/2026 | 1h 12 mins.Ryan Williams is a professor at MIT and the winner of the Gödel Prize in theoretical computer science. I interviewed him all about his work starting by asking him a popular Leetcode question (3 SUM).
Correction: In this podcast I say "lower bound" when I mean "upper bound" and vice versa. Was speaking using the intuition that lower is better for running time. In reality, the accurate usage is:
"Lower bound" = A proven floor for a problem e.g. "no algorithm can possibly be faster"
"Upper bound" = A proven ceiling for a specific solution e.g. "there exists an algorithm this fast"
Professor Williams answers as if I spoke accurately so the error didn't impact the flow of conversation. Just a correction for the record
• 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/AaK1SL2i_4Y
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/mit-complexity-theorist-on-leetcode
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
(00:41) Asking him a popular Leetcode question
(03:54) Doing better than the popular optimal solution
(08:26) Fine grained complexity
(17:00) A severe strengthening of P vs NP
(24:38) SAT problems and solvers
(34:51) Hot takes on famous open questions
(46:57) Simulating space with time
(01:01:02) Why he solves hard problems
(01:02:35) How to pick good research direction
(01:07:14) Technical book recommendations
(01:08:31) Advice for his younger self
(01:11:56) Outro
Where to find Ryan:
• Wikipedia: https://en.wikipedia.org/wiki/Ryan_Williams_(computer_scientist)
• Website: https://people.csail.mit.edu/rrw/
• LinkedIn: https://www.linkedin.com/in/r-ryan-williams-a1b534a/
• X/Twitter: https://twitter.com/rrwilliams
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:
• Some Estimated Likelihoods for Computational Complexity: https://people.csail.mit.edu/rrw/likelihoods.pdf
• Simulating Time with Square-Root Space: https://arxiv.org/abs/2502.17779
• Cook and Mertz's tree evaluation paper: https://dl.acm.org/doi/10.1145/3618260.3649664OpenAI Eng & Dev Tools Founder: How Software Engineering Is Changing | Charlie Marsh
22/06/2026 | 1h 22 mins.Charlie Marsh is the founder of Astral, the Python devtool startup that was acquired by OpenAI. I inteviewed him about how software engineering is changing and learnings from starting his own company as an engineer.
• 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/Iw65FD4MGgs
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/openai-eng-and-dev-tools-founder
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
(00:40) Origin story
(06:04) The front page of Hacker News
(14:35) Why he chose Rust
(20:10) Full codebase migration from Zig to Rust
(28:40) LLM generated code and open source
(35:34) Performance optimizations
(44:54) Optimization with AI and combating slop
(01:02:08) Learnings as an eng starting a company
(01:17:55) Top technical talk recommendation
(01:18:56) Advice for his younger self
(01:22:00) Outro
Where to find Charlie:
• LinkedIn: https://www.linkedin.com/in/marshcharles/
• GitHub: https://github.com/charliermarsh
• X/Twitter: https://x.com/charliermarsh
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:
• Python tooling could be much, much faster: https://notes.crmarsh.com/python-tooling-could-be-much-much-faster
• The coolest PR he's ever seen: https://github.com/astral-sh/uv/pull/789
• Andrew Kelley’s data-oriented design talk: https://www.youtube.com/watch?v=IroPQ150F6c
• Ruff: https://github.com/astral-sh/ruff
• uv: https://github.com/astral-sh/uv
• ty: https://github.com/astral-sh/ty
• Salsa: https://github.com/salsa-rs/salsaGoogle DeepMind Pre-Training Lead: How To Land a Job at a Frontier Lab | Vlad Feinberg
15/06/2026 | 1h 4 mins.Vlad Feinberg is Google DeepMind’s pre-training area lead and I asked him all about how to land a job at a frontier lab like Google DeepMind, Anthropic or OpenAI.
• 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/cDyi91onoJ8
• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835
• Transcript: https://www.developing.dev/p/google-deepmind-pre-training-lead
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
(00:33) Skills frontier labs need
(08:45) The difference between AI research and engineering
(21:41) Domains that matter for the frontier
(30:50) Marketing yourself to frontier labs
(35:13) Concrete steps engineers can take
(38:29) Overview of pre-training areas
(47:23) Jeff Dean spot bonus story
(50:14) Favorite Gemini war story
(58:59) Advice for his younger self
(01:03:07) Outro
Where to find Vlad:
• Personal Website: https://vladfeinberg.com/
• Twitter/X: https://x.com/FeinbergVlad
• LinkedIn: https://www.linkedin.com/in/vladimirfeinberg/
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:
• How to Land a Job at a Frontier Lab: https://vladfeinberg.com/2026/05/10/how-to-land-a-job-at-a-frontier-lab.html
• ThunderKittens: https://github.com/HazyResearch/ThunderKittens
• Deedy's doomer Tweet: https://x.com/FeinbergVlad/status/2056383124829872466?s=20
• Jacob Steinhardt's "Research as a Stochastic Decision Process": https://cs.stanford.edu/~jsteinhardt/ResearchasaStochasticDecisionProcess.html
• The Scaling Book: https://jax-ml.github.io/scaling-book/
• Dwarkesh and Reiner's video: https://www.youtube.com/watch?v=xmkSf5IS-zw
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