Nearly everything at Google has an acronym. Machine learning, the artificial intelligence method for processing reams of data, currently all the rage across Google, is just “ML” inside the company.
Here’s Google’s New Strategy to Catch Up in the Cloud: Inject It With Machine Learning
Google hopes its AI smarts can boost its cloud game.
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On Wednesday, Google presented its newly assertive push for the enterprise, hosting its inaugural cloud developer conference in San Francisco. Naturally, ML was involved. In fact, Google unveiled a handful of new offerings that, in essence, pour ML all over the cloud.
“I’ve become convinced that there’s a new architecture emerging,” an exuberant Eric Schmidt, chairman of Google parent Alphabet, said from the stage. “This platform is not the end; it’s the bottom. There’s something above it. And that something is machine learning.”
It’s a bold, if vague, statement — but one that underscores how Alphabet writ large sees its future. On the cloud side, Google’s intent is that machine intelligent features can distinguish its platform from those of larger rivals Amazon and Microsoft. Specifically, Google expanded its open source AI tool, TensorFlow, to its cloud platform and pitched a package of AI-infused APIs for enterprise customers. Those include Google’s computer systems for translating languages, recognizing speech and scanning an image (say, a cat) and detailing it immediately (this is the type of cat).
A few practical non-cat business applications were mentioned — a partner, Wix, builds websites more efficiently with visual recognition. But Jeff Dean, Google’s machine learning guru, specified that the bigger impact is allowing businesses to deploy Google’s advanced data-churning methods on their own models. “They can take their data and actually build insight,” he said on Wednesday.
That’s the pitch: If your business picks Google for the cloud, you get Google’s best smarts thrown in.
Diane Greene, Google’s new enterprise honcho, cited machine learning along with security as the two pillars behind her strategy. “If your customer competitor is embracing machine learning, it’d be prudent for you to embrace it too,” she told the audience.
It’s true that machine learning is spreading across enterprises. Amazon and Microsoft are working on it too, and likely injecting it in their cloud offering. Google may be ahead on the tech here, but it’s not clear if it alone is a compelling asset for Google’s cloud. For big enterprises, which Google wants, moving data to the cloud (or moving from one cloud to another) is expensive. And they tend to care about other tailored features, security and customer service over machine learning capabilities.
Google focused on Coca-Cola, Spotify and Disney as big customers during the event, but did not mention any newcomers (although Netflix appeared on a list thrown up during the event). No customers onstage discussed if they had switched over from Amazon Web Services, the market leader.
Increasingly, companies rely on more than one cloud service. That plays to Google’s strength as it pushes uphill from third place. The quieter, yet more interesting, announcement from the day was a tool called Stackdriver. It’s a dashboard tool for customers that use both Google’s and Amazon’s cloud.
This article originally appeared on Recode.net.
