Subvolts take Compute and energy infrastructure, not just intelligence, will decide the AGI race. Nov 6, 2025 - Developers
- Learn about RL2L and how AI intelligence might commoditize, impacting agent development.
- Business
- Understand the critical role of energy and compute infrastructure in the AGI race and Poolside's enterprise strategy.
This interview provides a deep dive into the critical, often overlooked, physical infrastructure needs of frontier AI development.
Intelligence Isn’t Enough: Why Energy & Compute Decide the AGI Race – Eiso Kant
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From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
Eiso Kant, Co-CEO of Poolside, joins The MAD Podcast to discuss Project Horizon, a large-scale energy and compute infrastructure project. Kant argues that frontier AI labs need to control energy, compute, and intelligence to win the AGI race. The episode covers token economics, modular hardware rollouts, partnerships like CoreWeave, and Poolside's strategy for rapid capacity deployment and enterprise solutions.
This episode explains that building advanced AI requires massive amounts of electricity and computer power, not just smart software. Poolside is building its own power and computer centers to provide this, aiming to help AI companies grow without giving up control.
This episode is for AI infrastructure investors, operators, and strategists. It explains how physical infrastructure, specifically energy and compute, is becoming a critical bottleneck for frontier AI development. Listeners will learn about Poolside's ambitious Project Horizon, their modular approach to deploying compute, and their strategy for integrating with enterprise clients. This offers insight into the non-model-centric aspects of the AGI race, directly relevant to how major labs like OpenAI, Google Gemini, and Anthropic might need to secure massive physical resources.
- HostMatt Turck
- GuestEiso KantCo-CEO & Co-Founder, Poolside
- Guest: Eiso Kant, Co-CEO & Co-Founder, Poolside
- Show: The MAD Podcast
- Length: 66 minutes
- Project: Project Horizon - a multi-gigawatt West Texas build
- Rollout: Staged 250 MW rollout using 2.5 MW modular skids
- Partnership: CoreWeave anchor partnership
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
(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
- AGI
- Eiso Kant
- Artificial General Intelligence, a hypothetical AI with human-like cognitive abilities.
- token economics
- Eiso Kant
- The study of how tokens (units of data or currency) are created, managed, and used within an AI system or ecosystem.
- RL2L
- Eiso Kant
- Reinforcement Learning to Learn, a method for AI to learn by experiencing and interacting with its environment.
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Questions people ask
- What is Project Horizon?
- Project Horizon is Poolside's initiative to build a multi-gigawatt energy and compute infrastructure in West Texas, aiming to provide essential resources for frontier AI development.
- What is RL2L?
- RL2L, or Reinforcement Learning to Learn, is a method Poolside is developing to reverse-engineer the web's thoughts and actions, potentially leading to commoditized intelligence.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Matt Turck.