Google, Movidius aims to make smartphones see on their own

January 28, 2016 - 

Google is working with Movidius to incorporate powerful image recognition technology into smartphones.

The two companies entered into an agreement whereby Google will source Movidius processors along with the entire Movidius software development environment for its mobile devices. In turn, Google will contribute to Movidius’ neural network technology roadmap.

The agreement enables Google to accelerate adoption of machine learning applications in its mobile devices. Reportedly, the technology will “allow the next generation of smartphones see on their own” and provide such benefits as helping “blind individuals more easily maneuver urban areas or converse with familiar people on the street”.

The agreement, according to a joint statement issued by the companies, primarily allows Google to deploy its advanced neural computation engine on Movidius’ ultra-low-power platform, introducing a new way for machine intelligence to run locally on devices.

“What Google has been able to achieve with neural networks is providing us with the building blocks for machine intelligence, laying the groundwork for the next decade of how technology will enhance the way people interact with the world,” said Blaise Agüera y Arcas, head of Google’s machine intelligence group in Seattle. “By working with Movidius, we’re able to expand this technology beyond the data center and out into the real world, giving people the benefits of machine intelligence on their personal devices.”

Google will utilize Movidius’ latest flagship chip: the MA2450. The MA2450 is the only commercial solution currently on the market with the performance and power-efficiency to undertake complex neural network computations in ultra-compact form factors.

The MA2450 is the most powerful iteration of the Myriad 2 family of vision processors, providing a series of improvements over the first-generation Myriad 2 VPU announced last year, the MA2100.

“The technological advances Google has made in machine intelligence and neural networks are astounding. The challenge in embedding this technology into consumer devices boils down to the need for extreme power efficiency, and this is where a deep synthesis between the underlying hardware architecture and the neural compute comes in,” said Remi El-Ouazzane, CEO, Movidius. “Movidius’ mission is to bring visual intelligence to devices so that they can understand the world in a more natural way. This partnership with Google will allow us to accelerate that vision in a tangible way.”

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About Rawlson King

Rawlson O’Neil King is a contributing editor at BiometricUpdate.com and is an experienced communications professional, management consultant, trade journalist and author who recently published a book about control and electronic networks and who has written numerous articles in trade publications and academic journals about smart home and building technologies. Follow him @rawlsonking2.