Turing Award Winner: Early AI, LLM Predictions, Causality | Judea Pearl

<p>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.</p><p><br></p><p>• My ergonomic keyboard project I mentioned, you can follow along here: https://read.compose.llc/</p><p>• The Kickstarter page for it: https://www.kickstarter.com/projects/ryanlpeterman/compose-simple-ergonomics-beautifully-done</p><p><br></p><p>Podcast links:</p><p><br></p><p>• YouTube: https://youtu.be/FleTXB1fAcQ</p><p>• Apple: https://podcasts.apple.com/us/podcast/the-peterman-pod/id1777363835</p><p>• Transcript: https://www.developing.dev/p/turing-award-winner-early-ai-llm</p><p><br></p><p>Thank you to this episode&#39;s sponsor for supporting my work:</p><p><br></p><p>• 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/</p><p><br></p><p>Timestamps:</p><p><br></p><p>(00:00) Intro</p><p>(00:54) How he got into AI</p><p>(11:17) Greatest scientist of all time</p><p>(20:15) What people thought of AI in the 80s</p><p>(26:23) Entering academia and researching AI</p><p>(34:52) The invention of Bayesian networks</p><p>(46:28) Pioneering work in causality</p><p>(55:38) The causal hierarchy</p><p>(59:34) LLMs and predictions</p><p>(01:20:12) A restless mind pays</p><p>(01:24:36) Advice for his younger self</p><p>(01:26:37) Outro</p><p><br></p><p>Where to find Judea:</p><p><br></p><p>• X/Twitter: https://twitter.com/yudapearl</p><p>• Website: https://bayes.cs.ucla.edu/jp_home.html</p><p>• Wikipedia: https://en.wikipedia.org/wiki/Judea_Pearl</p><p><br></p><p>Where to find Ryan:</p><p><br></p><p>• Newsletter: https://www.developing.dev/</p><p>• X/Twitter: https://x.com/ryanlpeterman</p><p>• LinkedIn: https://www.linkedin.com/in/ryanlpeterman/</p><p>• Threads: https://www.threads.com/@ryanlpeterman</p><p>• Instagram: https://www.instagram.com/ryanlpeterman</p><p>• TikTok: https://www.tiktok.com/@ryanlpeterman</p><p><br></p><p>Referenced in this episode:</p><p><br></p><p>• The Book of Why: https://en.wikipedia.org/wiki/The_Book_of_Why</p><p>• Bayesian networks: https://en.wikipedia.org/wiki/Bayesian_network</p><p>• Alpha-beta pruning: https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning</p><p>• Pearl vortex: https://en.wikipedia.org/wiki/Pearl_vortex</p><p>• Graphoid: https://en.wikipedia.org/wiki/Graphoid</p><p>• Causality: Models, Reasoning, and Inference: https://en.wikipedia.org/wiki/Causality_(book)</p><p>• Coexistence and Other Fighting Words: Selected Writings of Judea Pearl, 2002–2025: https://bayes.cs.ucla.edu/COEXISTENCE/</p>