In this episode of Earthlings 2.0, we speak with Theo Ludwick, Co-Founder and Managing Partner at NosTerra Venture Capital, about the infrastructure behind AI's rapid growth. Theo explains why electricity has become one of the biggest bottlenecks facing AI data centers, how operators are balancing power and water use, and why energy efficiency could help unlock additional data center capacity in the near term. The conversation also explores emerging energy and cooling technologies, the shift from AI training to inference, data centers as critical infrastructure, and where investors are finding opportunities across the next generation of AI infrastructure.
Check out a few of our previous episodes on data centers:
Electricity is becoming a major bottleneck for AI data centers – The rapid growth of AI compute is driving greater demand for power. Theo explains that addressing this challenge will require a combination of energy efficiency, grid flexibility, new generation, storage, and other technologies rather than a single energy solution.
Data center efficiency could unlock more capacity in the near term – While new power generation can take years to deploy, technologies that improve efficiency and flexibility can be implemented sooner. Better chips, cooling, system orchestration, batteries, and flexible loads could help data centers use existing grid capacity more effectively as AI demand grows.
The shift from AI training to inference could reshape data center infrastructure – AI training has favored large, centralized data centers, but inference can operate across a wider range of computing environments. As inference grows, Theo expects opportunities for smaller data centers located closer to population centers, potentially changing how facilities are designed, powered, and distributed.
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