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Google makes AI talent play with Kaggle buy

Clint Boulton | March 17, 2017
In acquiring the crowdsourcing platform for predictive modeling and machine learning competitions, Google gains access to 600,000 data scientists in a notoriously talent-strapped market. The company says the deal will help it democratise AI.

Whether Google can harness these technologies to make the world a better place, a goal shared by Facebook, Microsoft, Baidu and other tech giants, remains an open question.

"The real challenge is deploying AI in everyday human affairs in a way that allows us to augment our intelligence and manage our planet intelligently," Jacobstein said. “We have a huge opportunity to deploy better decision-making capabilities across the board and we are underutilizing those tools."


Necessary progression of AI

For Google, acquiring Kaggle is part of a necessary progression for AI technologies, including natural language processing, predictive analytics and machine learning tools intended to achieve breakthroughs, said Forrester Research analyst Brian Hopkins.

"Google's acquisition of Kaggle essentially enables that innovation to be exponential because instead of saying there is one set of people at Microsoft or Facebook that can do this, Google can say that we are going to crowdsource this and create a set of emerging technology innovation," Hopkins said. "Being able to crowdsource and bring the best minds in and incentivize them to do that work is the way it has to happen. There is no other way it can happen. I'm pretty sure Google sees that."

However, Hopkins said it remains to be seen whether Google can effectively commercialize anything from its AI assets. Its so-called moonshots, from self-driving cars to internet-enabling balloons, have yet to pan out. 

"Google is positioned to potentially repeat what they did [for search and AdWords] in the AI space because it is a big area for them, but they have competition," Hopkins said. "They need to find the commercialization a-ha of how they're going to turn AI into something profitable just like they [turned] search into profitability," Hopkins said.

The reality is that most enterprises haven't figured out quite what to do with machine learning and associated AI tools yet, let alone how such technologies can give them a competitive edge.

Most organizations are only piloting AI and machine learning tools, including virtual assistants and robo-advisors, said Gartner analyst Whit Andrews, who tracks machine learning and AI technologies. Andrews said that a poll of 923 corporate employees with a title of vice president or higher revealed that 76 percent planned to try some form of AI or machine learning over the next 12 months.


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