Russ Salakhutdinov - Kimi K3 CEO’s PhD Advisor Predicts the Future of AI Agents

Kimi K3 took the world by storm last week for open-sourcing frontier level intelligence, so I sat down with Zhilin Yang's (Kimi CEO) PhD advisor Russ Salakhutdinov to talk.Russ has been everywhere in modern AI. He did his PhD with Geoff Hinton back when neural nets were a punchline, sold his startup to Apple and worked on Project Titan, teaches at Carnegie Mellon, and spent the last couple years at Meta Superintelligence Lab building computer use agents. Now he's the founder of Sooth Labs, building AI that forecasts the future.We talked about why there's no secret architecture inside the frontier labs and why the real moat is data, engineering, and infrastructure. He explains why Cursor and half the startups you know are quietly running on Chinese open source models, why all the LLMs are going to be commodities, and why the people actually building AGI don't buy the two-year timeline. We get into his time at Meta, why computer use agents still hit 60% when you need 99.9%, whether AI can beat prediction markets, and why the RL environment business isn't sticky. And he makes the case that AI should replace McKinsey, Bain, and BCG.Chapters:0:00 - Intro1:26 - Bumping into Hinton on the street3:25 - When neural nets were the third choice5:21 - Generating digits before it was cool6:59 - AlexNet breaks computer vision10:18 - Teaching models to describe what they see12:10 - Early text-to-image (and the toilet seat that beat Google)16:52 - Hallucination is a feature19:36 - Selling Perceptual Machines to Apple22:45 - Self-driving: 0 to 80 in a year, stuck for 530:30 - Inside FSD and Waymo's architecture34:18 - Building Visual Web Arena at CMU39:07 - Why he joined Meta Superintelligence40:09 - The agent that plans your faculty job hunt42:00 - Paying people for their browser history42:45 - The coupon-hunting agent43:35 - Why agents still fail46:14 - 60% when you need 99.9%47:04 - Agents on your phone50:12 - No secret architecture at the frontier labs51:20 - Why coding and math got solved first54:01 - Models that smell and touch56:14 - The future of software engineering59:41 - Founding Sooth Labs1:00:07 - The 13% graduation prediction1:05:55 - Why ChatGPT can't forecast1:08:12 - Agents first, decision systems next1:09:23 - The Wikipedia contamination story1:13:43 - Can AI beat prediction markets?1:16:26 - AI replaces McKinsey1:18:20 - Why the crowd is hard to beat1:19:30 - China's open source models rise1:24:26 - Why the US needs its own open models1:25:53 - RL environment businesses won't last1:28:35 - The end of SaaS, LLMs as commodities1:32:55 - What's next: self-improvement, forecasting, robots1:35:34 - The only useful robot is the Roomba1:37:53 - What he'd study in college today1:41:20 - Adapt or get left behind1:44:07 - Wrapping up