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Remote AI-training data centers may lack 'flexibility' in wake of DeepSeek, says major investor.
Compute efficiency breakthroughs like DeepSeek will impact data centers depending on location and use case, says Mark Prybutok, Head of Digital Infrastructure at GI Partners.
Prybutok notes the many hyperscaler-backed, data center mega-projects now being "purpose built" for AI training in remote areas, where prices as well as latency is lower. AI training workloads prioritize computing power over low latency, allowing operators to take advantage of cheaper land and lower energy costs.
But evolutions in technology may change the economics of these planned remote mega-campuses. "It's important to have flexibility in use cases," says Pryputok. "Why do we see more of these massive hyperscale campuses being developed near [data infrastructure hubs like] Northern Virginia? The reason is that it's important for those end users, those hyperscalers, to have flexibility in use case."
Prybutok shares his insights in the full Cool Vector episode, "GI Partners, in Digital Infrastructure Since 2001, Has Advice for Newcomers," on the Cool Vector YouTube channel:
Follow Cool Vector on LinkedIn: https://www.linkedin.com/company/cool-vector-media/
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