Intelligence Isn’t Enough: Why Energy & Compute Decide the AGI Race – Eiso Kant

Video Description

Frontier AI is colliding with real-world infrastructure. Eiso Kant (Co-CEO & Co-Founder, Poolside) joins the MAD Podcast to unpack Project Horizon— a multi-gigawatt West Texas build—and why frontier labs must own energy, compute, and intelligence to compete. We map token economics, cloud-style margins, and the staged 250 MW rollout using 2.5 MW modular skids. Then we get operational: the CoreWeave anchor partnership, environmental choices (SCR, renewables + gas + batteries), community impact, and how Poolside plans to bring capacity online quickly without renting away margin—plus the enterprise motion (defense to Fortune 500) powered by forward deployed research engineers. Finally, we go deep on training. Eiso lays out RL2L (Reinforcement Learning to Learn)— aimed at reverse-engineering the web’s thoughts and actions— why intelligence may commoditize, what that means for agents, and how coding served as a proxy for long-horizon reasoning before expanding to broader knowledge work. Poolside Website - https://poolside.ai X/Twitter - https://x.com/poolsideai Eiso Kant LinkedIn - https://www.linkedin.com/in/eisokant/ X/Twitter - https://x.com/eisokant FIRSTMARK Website - https://firstmark.com X/Twitter - https://twitter.com/FirstMarkCap Matt Turck (Managing Director) Blog - https://www.mattturck.com LinkedIn - https://www.linkedin.com/in/turck/ X/Twitter - https://twitter.com/mattturck LISTEN ON: Spotify - https://open.spotify.com/show/7yLATDSaFvgJG80ACcRJtq Apple - https://podcasts.apple.com/us/podcast/the-mad-podcast-with-matt-turck/id1686238724 00:00 Cold open – “Intelligence becomes a commodity” 00:23 Host intro – Project Horizon & RL2L 01:19 Why Poolside exists amid frontier labs 04:38 Project Horizon: building one of the largest US data center campuses 07:20 Why own infra: scale, cost, and avoiding “cosplay” 10:06 Economics deep dive: $8B for 250 MW, capex/opex, margins 16:47 CoreWeave partnership: anchor tenant + flexible scaling 18:24 Hiring the right tail: building a physical infra org 30:31 RL today → agentic RL and long-horizon tasks 37:23 RL2L revealed: reverse-engineering the web’s thoughts & actions 39:32 Continuous learning and the “hot stove” limitation 43:30 Agents debate: thin wrappers, differentiation, and model collapse 49:10 “Is AI plateauing?”—chip cycles, scale limits, and new axes 53:49 Why software was the proxy; expanding to enterprise knowledge work 55:17 Model status: Malibu → Laguna (small/medium/large) 57:31 Poolside's Commercial Reality today: defense; Fortune 500; FDRE 1:02:43 Global team, avoiding the echo chamber 1:04:34 Next 12–18 months: frontier models + infra scale 1:05:52 Closing