Google needs to double its AI serving capacity 'every six months' and scale 'the next 1000x in 4-5 years' according to an internal presentation

If there's one thing sure to ruin your day at work, it's receiving an unrealistic target from your higher-ups. Pour one out, then, for the Google employees who attended an all-hands meeting earlier this month, only to be told that they need to double its serving capacity every six months to meet AI compute demand.

That's according to CNBC, as the news outlet got a look at a presentation reportedly given to employees by Google AI infrastructure chief Amin Vahdat earlier this month. A slide entitled "AI compute demand" informed the team that "Now we must double every six months... the next 1000x in 4-5 years."

CNBC also reports some direct quotes from the meeting, which was also said to be attended by Alphabet CEO Sundar Pichai. While Microsoft, Amazon, and Meta have been pouring huge sums of money into data center expansion in recent months to boost their own AI serving capabilities, it appears that Google's lofty expansion goals might not be receiving the same budget.

Vahdat reportedly told employees that "[Google's] job is of course to build this infrastructure, but it's not going to outspend the competition, necessarily" and that the real goal will be providing infrastructure that is "more reliable, more performant, and more scalable than what's available anywhere else."

That's not all. Vahdat is also claimed to have said Google needs to "be able to deliver 1,000 times more capability, compute, storage networking, for essentially the same cost and increasingly, the same power, the same energy level."

"It won't be easy," the Google AI chief said. "But through collaboration and co-design, we're going to get there."

That sounds like quite the task, doesn't it? I can only imagine the blank faces in the room as the Google engineers wrapped their heads around the idea of expanding their infrastructure on a truly gigantic scale, in record timeframes, without substantially increasing the budget—both literally and figuratively.

Management consultancy firm McKinsey & Company estimates that AI data centers are expected to require $5.3 trillion in capital expenditures by 2030, or roughly $1 trillion over Nvidia's current market cap, if you prefer to think of it that way. Certainly, if efficiencies could be made to enable unbelievably rapid AI compute expansion without pushing data center power requirements and budgets further into the stratosphere, the company to do so would be in a prime position to make the most of the AI boom.

If, indeed, it lasts that long to begin with, given mounting concerns over a massive, potentially economy-wrecking AI bubble. Still, they don't call it a moon shot for nothing. Get to work, Google AI infrastructure engineers. It sounds like an impossible task, but Vahdat seems to believe in your work ethic. You didn't need a lunch break anyway, did you?

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