New blackboard lecture with Reiner Pope: how do chips actually work - starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. Reiner [https://reiner.org/] is CEO of MatX [https://matx.com/], a new chip startup (full disclosure - I’m an angel investor). He was previously at Google, where he worked on software [https://arxiv.org/abs/2211.05102] efficiency [https://jax-ml.github.io/scaling-book/], compilers, and TPU architecture. Watch this one on YouTube [https://youtu.be/oIk3R-sMX5o] so you can see the chalkboard. Read the transcript [https://www.dwarkesh.com/p/reiner-pope-2]. Sponsors * Crusoe [https://crusoe.ai/dwarkesh] was one of only five GPU clouds that made the gold tier in SemiAnalysis' most recent ClusterMAX report. Gold-tier providers like Crusoe delivered 5-15% lower TCO than silver-tier clouds, even with identical GPU pricing. This is because optimizations like early fault detection and rapid node replacement don't necessarily show up in the sticker price, but still matter a ton in the real world. Learn more at crusoe.ai/dwarkesh [https://crusoe.ai/dwarkesh] * Cursor [https://cursor.com/dwarkesh] is where I do most of my work—from reading research papers to visualizing technical concepts to coding up internal tools for the podcast. Most recently, I used it to build two different review interfaces for my essay contest, one that anonymizes submissions for scoring and another that lets me see applicants' essays next to their resumes and websites. Whatever you're working on, you should try doing it in Cursor. Get started at cursor.com/dwarkesh [https://cursor.com/dwarkesh] * Jane Street [https://janestreet.com/dwarkesh] let me ask Ron Minsky and Dan Pontecorvo, two senior Jane Streeters, a bunch of questions about how they use AI. We discussed everything from the types of models they're training to how they think about the future of trading to why they're more bullish than ever on hiring technical talent. You can watch the full conversation and learn more about their open positions at janestreet.com/dwarkesh [https://janestreet.com/dwarkesh] Timestamps 00:00:00 – Building a multiply-accumulate from logic gates 00:16:31 – Muxes and the cost of data movement 00:26:10 – How systolic arrays work 00:39:11 – Clock cycles and pipeline registers 00:51:51 – FPGAs vs ASICs 01:03:25 – Cache vs scratchpad 01:07:27 – Why CPU cores are much bigger than GPU cores 01:12:00 – Brains vs chips 01:15:33 – A GPU is just a bunch of tiny TPUs Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe [https://www.dwarkesh.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]