🖥️ The AI Hardware Stack: From Chip to Chiller

⚡ Power, Cooling & Rack-Scale Systems for the AI Era

A high-signal summit diving deep into the physical hardware systems that underpin the next generation of AI — spanning advanced chip architecture, AI servers, power delivery, liquid cooling, rack-scale design, and data center infrastructure.

As AI workloads transition from training into large-scale inference, robotics, and real-world deployment, the most pressing bottlenecks are increasingly physical: power density, thermal limits, memory bandwidth, rack-level integration, energy availability, and the operational complexity of running high-density compute at scale.

This gathering convenes researchers, engineers, founders, investors, and operators active across chip design, data center hardware, AI infrastructure, thermal systems, power systems, and large-scale compute.

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🎙️ Topics on the Table

🔬 AI Chips & Accelerators

GPUs, ASICs, memory architectures, and advanced packaging are evolving into the core compute engine of modern AI. Discussion will cover what is shifting at the silicon level — and why these systems place ever-greater demands on power, bandwidth, and thermal performance.

⚡ Powering AI at Scale

Energy access is emerging as one of the most significant constraints on AI growth, with global data center electricity consumption projected to roughly double by 2030. Panelists will address grid capacity, energy availability, power delivery architecture, and where next-generation AI data centers can realistically expand.

🌊 Cooling High-Density AI Hardware

AI systems generate unprecedented heat at the chip, board, and server level, pushing thermal engineering to the forefront of hardware design. This session explores how liquid cooling, server-level thermal management, and cooling infrastructure are adapting to support ever-denser AI workloads.

📐 Standards & Deployment Readiness

Dense AI systems are compelling data centers to rethink deployment workflows, monitoring strategies, serviceability, and interoperability. The conversation will examine what requires greater standardization — from rack interfaces to facility readiness — for AI hardware to scale reliably.

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👥 Speakers & Panelists

🔔 Featured speakers and panelists will be announced soon — stay tuned!

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🎟️ Who Should Attend

This event welcomes:

• 🎓 Stanford, Harvard, and MIT Alumni
• 🤝 UAIS & Aexodus Capital affiliates and partners
• 🔧 Chip architects and AI hardware founders
• 🏗️ Data center leaders, infrastructure operators, and engineers
• 💼 Investors, LPs, and VCs

⚠️ Strictly limited capacity. This gathering is deliberately curated to preserve the high-signal environment established in previous series events, ensuring every conversation meaningfully advances the Physical AI industry.

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🏢 Hosted & Sponsored By

Hosted by: SFPlayground, Universal AI Services, and Aexodus Capital
In collaboration with: the Stanford Alumni Club and the MIT Club of Northern California

📍 Register to receive the venue address.