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Start free trial →Volts · Climate & Energy · November 2026
The conversation was about how simplifying the power chain in an AI data center frees up space and power. Belur says the savings can either cut energy use or go into more compute, which is how he frames the pitch to hyperscalers.
…contains the battery backup unit, the power supply unit, the power distribution unit, and et cetera. So if you can simplify that entire powertrain, and if the end phase can show that, hey, you don't even need that local battery anymore, hey, that could be a huge advantage to the entire system.
Yeah, yeah, lots more compute in the same building.
Yeah. So the question comes: if I save 5% in efficiency, do I take that 5% efficiency to saving electrons, saving energy? I think that's a very good reason to do if you are power constrained, which in a lot of cases we are. But in the other case, it means I can add 5% more GPUs. Right. I can add more GPUs, which means I can generate more revenue. I can be more efficient. The amount of tokens per watt improves.
So hyperscalers need this and have a lot of money. So they're the first big market that SSTs are going after approximately. This is all semi-speculative. We're talking about pilots of this next year, maybe, and then the industry shifting to SSTs 28, 29, 30, something like that. But that's the big…
Yes, I'm far more bullish as an engineer. I think about it on a first principles basis. I go, why wouldn't you put something that's more reliable, more efficient, and lower cost? And so if you believe in the AI in the AI transformation, which I'm a believer in, I think you should expect this to…
Yes, but it's always the engineering mindset running up against the institutional conservatism of people with lots of money who have been doing things a certain way for a long time. It always goes more slowly than one might like. But one way or the other, these are about to move into data centers…