Google alters its cloud playbook, enlisting partners to sell more AI chips

Thomas Kurian, chief executive officer of cloud services at Google LLC, speaks during the Google Cloud Next event in San Francisco on April 9, 2019.

Michael Short | Bloomberg | Getty Images

Google has spent years pitching customers on the advantage of buying its chips, models and cloud services in one place, offering a full stack that rivals Amazon and Microsoft have tried to replicate.

Now, the company is pushing its equipment outside of its own walls to reach more customers and build a bigger business around artificial intelligence chips, a market that Nvidia has dominated.

A day ahead of its third-quarter earnings report, Alphabet said on Tuesday that Oracle will offer Google's tensor processing units, or TPUs, the custom chips the internet giant has been developing since 2013. It's the first time customers will be able to access TPUs outside of Google's infrastructure, and shows that cloud boss Thomas Kurian, who previously spent more than 20 years at Oracle, is looking elsewhere for growth.

"They're a very strong competitor, and it's very possible that they could eventually take market share from Nvidia," said Chris Ballard, managing director of Check Capital Management, referring to Google's position in chips.

Kurian, who joined Google in late 2018, is operating from a position of strength. Analysts expect Google Cloud revenue to jump about 90% from a year earlier, after growing 82% in the second quarter, with TPUs contributing to its momentum.

"Google was great at doing its own thing, but it was never able to serve customers," said Uday Cheruvu, a portfolio manager at Harding Loevner, which owns Alphabet shares. "That mindset has changed."

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Google opened up TPUs to outside data centers in the second quarter, before this week's announcement with Oracle.

With $25 billion in second-quarter cloud revenue, Google trailed Amazon Web Services at $42 billion and Microsoft Azure at $29 billion.

But Google is growing the fastest.

'Optimize the whole stack'

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