Hammerhead AI Announces Columbia University Research Collaboration on AI Factory Power Orchestration

The collaboration will examine reinforcement-learning methods for coordinating power, cooling, and compute within operational and safety limits.

REDWOOD CITY, Calif., Oct. 6, 2026 /PRNewswire/ -- Hammerhead AI today announced a research collaboration with Columbia University focused on reinforcement learning approaches to AI factory power orchestration.

The collaboration brings together Hammerhead's engineering and simulation experience with a Columbia research team led by Prof. Clifford Stein, Wai T. Chang Professor of Industrial Engineering and Operations Research and Professor of Computer Science, along with researchers and graduate students in the Department of Industrial Engineering and Operations Research. The parties expect to study how reinforcement learning, simulation, and control-policy evaluation can help coordinate power, cooling, and compute while respecting operational, reliability, and safety requirements.

"Power is increasingly a binding constraint on AI infrastructure, and the systems used to manage it must be rigorously evaluated before they are trusted in production environments," said Rahul Kar, CEO and Founder of Hammerhead AI. "This collaboration with Columbia gives us the opportunity to formalize critical operational challenges, test new methods against realistic constraints, and advance the discipline of safe control for AI infrastructure."

A Research Challenge With Operational Stakes
As AI demand grows, access to timely power capacity has become a material constraint on new deployment. In many U.S. markets, grid interconnection and power-delivery timelines can extend for years, increasing the value of making better use of capacity that is already available.

Addressing this challenge requires coordination across interconnected systems, including IT workloads, power infrastructure, thermal management, and site-level operating policies. These systems have competing objectives and hard constraints, including equipment limits, reliability requirements, and safety boundaries.

The research collaboration will explore how reinforcement-learning methods can be formulated, simulated, tested, and evaluated under these conditions. The work develops approaches to how AI factories use available power capacity more effectively while maintaining operator-defined controls and operating limits.

About Hammerhead AI
Hammerhead turns available power into deployable inference capacity in months, helping data center operators convert underutilized assets into new AI revenue. Its software platform, ORCA, orchestrates power, cooling, and compute to unlock at least 30% more capacity from existing infrastructure. Founded by veterans who have managed over 8 GW of mission-critical assets, Hammerhead is backed by leading investors including Buoyant Ventures and SE Ventures. Learn more at hammerheadco.ai or follow HammerheadAI, Inc. on LinkedIn.

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SOURCE Hammerhead AI