Google extends long arm of influence further into AI

Google has launched a new initiative, Gradient Ventures, its own VC arm to seek out AI talent and invest in start-ups.

Jamie Davies

July 12, 2017

4 Min Read
Google extends long arm of influence further into AI

Google has launched a new initiative, Gradient Ventures, its own VC arm to seek out AI talent and invest in start-ups.

The initiative itself is a simple one. Google will provide funds and access to experienced engineers to help the start-ups develop to the next level. AI is proving to be an area which will underpin the success of the next technology revolution, whether it is in the enterprise organizations, internet applications or even the infrastructure technology, and Google isn’t messing around.

“AI-powered technology holds a lot of promise – from improving patient health to making data centres more efficient,” said Anna Patterson, Managing Partner at Venture Gradient. “But while we’ve seen some amazing applications of AI so far, we know there are many more out there that haven’t even been imagined yet. And sometimes, these new ideas need support to flourish.

“That’s why we’re announcing Gradient Ventures, a new venture fund from Google with technical mentorship for early-stage start-ups focused on artificial intelligence. Through Gradient, we’ll provide portfolio companies with capital, resources, and dedicated access to experts and boot camps in AI. We’ll take a minority stake in the start-ups in which we invest.”

For years now, Google has created a perception surrounding the brand, which has mainly been for the purposes of recruitment, but can be used to great effect with this venture as well.

The perception is that of fun and excellence. The fun side is simple. Slides, sweets, bean bags and sleep pods. It has essentially created a university campus to appeal to engineers who might be slightly dismayed by the bland and boring offices which most other software companies operate in. It’s a clever idea, as it doesn’t cost that much money (certainly less than a vast amount of perks) and creates a niche for the brand to operate in.

It also makes sure that a lot of people apply to work for the company. Whether it is the promise of a fantastic lunch (that seems to work for one of our producers who goes to visit his Googler wife at work quite a lot) or a fun work environment, the company has a gluttony of engineers to choose from. The brightest and the best apply for Google.

Google has long boasted of having the best and most creative engineers in the world (it can be difficult to argue with them at times), but that is one of the biggest selling points of Gradient Ventures; start-ups with have the chance to work alongside the Googlers. And what start-up in the world wouldn’t want to do that.

Start-ups will be knocking down the Gradient Ventures door, in an attempt to get into the good books of Google. Most multi-nationals have to go searching to find the best start-ups to acquire or partner with, but Google is developing an ecosystem on its doorstep. To be honest, most companies try to do this. Orange has its own and Oracle has its Start-up Accelerator Project, for example, but few brands have the appeal of Google. Amazon or Microsoft or Apple are a couple who could compete, but Google has the longevity and consistency of excellence.

Google has shown its intentions in the artificial intelligence arena with the purchase of Deepmind in 2014 for $625 million, which looks like a bargain in today’s money, but it isn’t stopping. AI could define the next generation, and Google is putting itself in prime position.

Alongside the VC initiative, the team has also launched People + AI Research initiative (PAIR) which will bring together various Google engineers to study and redesign the ways people interact with AI systems. The focus here is not on the applications directly, but the relationship between users and technology. The research is split into three areas:

  • Engineers and researchers: answering questions such as; how might we make it easier for engineers to build and understand machine learning systems? What educational materials and practical tools do they need?

  • Domain experts: How can AI aid and augment professionals in their work?

  • Everyday users: How might we ensure machine learning is inclusive, so everyone can benefit from breakthroughs in AI?

It’s an area which might not make much money for Google, but the human elements of AI are crucial, and if it improves overall acceptance of the tech, that is a very good thing for the Google bet in the long-run.

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