CERAWeek — dubbed the Davos of energy — is where policymakers, producers, technologists and financiers gather to discuss how the world powers itself next.

NVIDIA and Emerald AI unveiled at the conference last week a new way forward — treating AI factories not as static power loads but as flexible, intelligent grid assets. This collaboration unifies accelerated computing, AI factory reference architectures and real‑time energy orchestration, helping large AI deployments connect to the grid faster, operate more efficiently and fortify system reliability.

Built on the NVIDIA Vera Rubin DSX AI Factory reference design and Emerald AI’s Conductor platform, the approach brings together compute, power networking and control into a single architecture. The result is an AI factory that can generate high‑value AI tokens while dynamically responding to grid conditions — flexing when needed, supporting reliability and reducing the need to overbuild infrastructure for peak demand.

AES, Constellation, Invenergy, NextEra Energy, Nscale Energy & Power and Vistra are working to build the energy generation capacity needed to meet rapidly growing power demand. The companies plan to collaborate on optimized generation strategies to support AI factories built on the NVIDIA and Emerald AI architecture, including hybrid projects that use co‑located power to accelerate time to power while delivering value to the broader grid. By pairing large AI loads with flexible operations, new generation resources and intelligent controls, this approach strengthens grid reliability.

It’s an important milestone in grid resilience, supported by an ecosystem for advanced AI factories. This new computing infrastructure paradigm — described by NVIDIA founder and CEO Jensen Huang as a five-layer AI cake — has energy as its foundational layer.

Power constraints are reshaping AI data centers, with energy efficiency or performance per watt, specifically tokens per second per watt, the defining metric of our modern computing infrastructure. By prioritizing computational efficiency, organizations can lower operating costs, maximize revenue and create a resilient digital infrastructure for businesses and consumers across America and worldwide.