Unsupervised Learning

It’s hard to imagine more of a dream Unsupervised Learning guest than @ylecun. Yann is one of the godfathers of AI, and he has some fascinating contrarian views on the limitations of LLMs. It was incredible to get to have a wide-ranging discussion with Yann about these views, reflections on his time at Meta and departure and what’s next for him. We hit on: ▪️ LLM limitations and a path forward for robotics ▪️ Why he left Meta ▪️ How he came to so dramatically disagree with his Turing co-laureates Geoff Hinton and Yoshua Bengio on LLMs ▪️ His predictions for 2027 ▪️ His new company AMI and the bet on world models ▪️ Why he compares OpenAI and Anthropic to Sun Microsystems ▪️ Why he tells PhD students to stop working on LLMs Plus some sharp views on the current safety discourse, how breakthrough research actually happens and what FAIR got right and wrong. YouTube: youtu.be/ngBraLDqzdI Spotify: bit.ly/4dL8fvT Apple: bit.ly/4wxgpiX

It’s hard to imagine more of a dream Unsupervised Learning guest than @ylecun. Yann is one of the godfathers of AI, and he has some fascinating contrarian views on the limitations of LLMs. It was incredible to get to have a wide-ranging discussion with Yann about these views, reflections on his time at Meta and departure and what’s next for him. We hit on: ▪️ LLM limitations and a path forward for robotics ▪️ Why he left Meta ▪️ How he came to so dramatically disagree with his Turing co-laureates Geoff Hinton and Yoshua Bengio on LLMs ▪️ His predictions for 2027 ▪️ His new company AMI and the bet on world models ▪️ Why he compares OpenAI and Anthropic to Sun Microsystems ▪️ Why he tells PhD students to stop working on LLMs Plus some sharp views on the current safety discourse, how breakthrough research actually happens and what FAIR got right and wrong. YouTube: youtu.be/ngBraLDqzdI Spotify: bit.ly/4dL8fvT Apple: bit.ly/4wxgpiX

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

At @OpenAI, Chief Scientist @merettm helps lead the research roadmap to AGI including a research intern-level AI system by September 2026 and a fully automated AI researcher by March 2028. I sat down with Jakub to check on those timelines and ask him all of my top-of-mind AI questions including: ▪️ How OpenAI thinks about extending RL beyond code and math ▪️ The current state of alignment research as more powerful models loom ▪️ The future of continual learning ▪️ How startups should think about building their own models/harnesses And he also shared some great stories around OpenAI’s pioneering work on math. YouTube: youtu.be/vK1qEF3a3WM Spotify: bit.ly/4sjUyrN Apple: bit.ly/41jAdrN 0:00 Intro 1:53 Research Intern Capability Timelines 4:59 Math Breakthroughs 7:59 RL Beyond Verifiable Tasks 12:32 RL vs In-Context 19:01 Allocating Compute Internally 28:18 AI for Science 31:40 Pattern Matching 33:23 Solving the Hardest Math Problems 37:40 Chain of Thought Monitoring 44:33 Generalization and Value Alignment in Models 47:57 Inside OpenAI 51:55 Quickfire

This week on Unsupervised Learning, @jacobeffron and I sat down with @jakeserval, co-founder & CEO of @getserval. Serval is going directly after ServiceNow in ITSM and already working with companies like Notion, Clay, Abridge, Fox, Mercor, and Verkada. We partnered with Serval at the Series A. What’s stood out most over the last year is their speed of execution. We get into how they’re winning customers and talent so quickly, including: ▪️ Why building a system of record beats layering on top ▪️ The "mirror architecture" that lets Serval land enterprise customers ▪️ Why ITSM is more vulnerable to AI disruption than other verticals ▪️ The Future IT Stack when agents submit their own requests ▪️ The AI-native org chart ▪️ Why recruiting is the #1 job of every Serval employee ▪️ The Dream Team Draft: recruiting during hypergrowth YouTube: youtu.be/Q0bxRANHjFY Spotify: bit.ly/4m4PJRX Apple: bit.ly/3POsYp8 0:00 Intro 1:25 What is Serval? 4:51 Early Doubts and Strategy 6:34 AI Tailwinds in ITSM 8:04 Competing with ServiceNow 9:41 Why ITSM Is Vulnerable 11:52 Automation via Codegen 16:27 Critical Guardrails 28:32 Internal Support Complexity 30:24 Hiring as the Moat 31:44 Dream Team Recruiting 33:49 Managers vs Super ICs 36:44 Junior Engineers and AI Native Workflows 43:13 Quickfire

What’s it like building at Abridge? “It feels like the beginning of the Internet… It’s love for software that I have never seen.” Watch to see what our builders say about working at Abridge. We’re fortunate to be backed by investors who share our vision, including @a16z @eladgil @khoslaventures @NVIDIA Ventures @IVP @SVAngel @lightspeedvp @Redpoint @sparkcapital @BessemerVP @usv We’re hiring in SF!

Legora sets the bar for operating at AI speed. Watching them become one of the fastest growing software companies of all time these past few years has provided constant lessons on what’s required to win in this new world. Fresh off @WeAreLegora's $550M Series D, CEO @MaxJunestrand joined @loganbartlett and me on Unsupervised Learning to provide a masterclass on building an AI-native company. He shared some amazing lessons around - Constantly rebuilding for the bleeding edge of model capabilities - Partnering with customers for both immediate impact and long-term transformation - Running Legora differently from traditional software companies He also included some spicy takes on - Why foundation models entering legal is good for Legora - Pricing AI products - The future of the legal industry It’s impossible to listen to Max and not pick up the infectious energy that makes Legora such a special company. Check out the full episode: YouTube: youtu.be/wzRZp-1EuaE Spotify: bit.ly/3Nc53za Apple: bit.ly/40ufr8m 0:00 Intro 1:16 Legora’s Series D Story 3:24 Why You Need Low Ego to Build in AI 5:58 From 60% to 100% Accuracy in One Summer 7:04 Law Firm Economics Shift 14:09 Pricing Seats Vs Outcomes 18:31 Why Foundation Models Entering Legal Helps Legora 30:10 Convincing a 75-Year-Old Partner to Go All In 33:02 Hiring Legal Engineers 34:32 Running an AI-Native Company 35:57 The Opus 4.5 Christmas Breakthrough 40:02 Building With Customers 44:01 All In On US Expansion 51:22 Stockholm Startup DNA

Legora sets the bar for operating at AI speed. Watching them become one of the fastest growing software companies of all time these past few years has provided constant lessons on what’s required to win in this new world. Fresh off @WeAreLegora's $550M Series D, CEO @MaxJunestrand joined @loganbartlett and me on Unsupervised Learning to provide a masterclass on building an AI-native company. He shared some amazing lessons around - Constantly rebuilding for the bleeding edge of model capabilities - Partnering with customers for both immediate impact and long-term transformation - Running Legora differently from traditional software companies He also included some spicy takes on - Why foundation models entering legal is good for Legora - Pricing AI products - The future of the legal industry It’s impossible to listen to Max and not pick up the infectious energy that makes Legora such a special company. Check out the full episode: YouTube: youtu.be/wzRZp-1EuaE Spotify: bit.ly/3Nc53za Apple: bit.ly/40ufr8m 0:00 Intro 1:16 Legora’s Series D Story 3:24 Why You Need Low Ego to Build in AI 5:58 From 60% to 100% Accuracy in One Summer 7:04 Law Firm Economics Shift 14:09 Pricing Seats Vs Outcomes 18:31 Why Foundation Models Entering Legal Helps Legora 30:10 Convincing a 75-Year-Old Partner to Go All In 33:02 Hiring Legal Engineers 34:32 Running an AI-Native Company 35:57 The Opus 4.5 Christmas Breakthrough 40:02 Building With Customers 44:01 All In On US Expansion 51:22 Stockholm Startup DNA