Google Partners With Chip Startup To Take Machine Learning Out Of The Cloud And Into Your Pocket

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Machine learning has become important to many products -- such as Google photos search and speech recognition. It's a kind of artificial intelligence that that gives computers the ability to learn, make predictions and find patterns. But most of all that complex computing typically needs to take place in the cloud, where the algorithms are being processed through power-intensive clusters of graphics processing units. Now Google wants to break those machine learning capabilities out of the data center and put them directly into devices. On Wednesday, the machine learning group at Google (now a division of Alphabet) announced it would start licensing processors from chip startup Movidius, which makes low-power chips it calls vision processing units (or VPUs).


Will Google's new partnership lead to smartphones that learn?

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A new partnership between Google and machine vision processing developer Movidius could pave the way for mobile devices to become even smarter. The deal, announced Wednesday, will allow Google to make use of Movidius processors and software development while providing Movidius with the web giant's help in its neural network technology work. "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 Google machine intelligence software architect and designer Blaise Agüera y Arcas in a Movidius press release. "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." Artificial neural networks are adaptive computer algorithms that attempt to mimic the understanding process of a human brain.


Intel buys computer vision startup Movidius as it looks to build up its RealSense platform

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Intel's RealSense platform was the star of its Intel Developer's Forum conference in San Francisco last month and it seems the company is only looking to grow the scale and capabilities of its computer vision tech. Today, the company announced that it is acquiring the computer vision startup behind Google's Project Tango 3D-sensor tech, Movidius. In a blog post, Movidius CEO Remi El-Ouazzane announced that his startup will continue in its goal of giving "the power of sight to machines" as it works with Intel's RealSense technology. Movidius has seen a great deal of interest in its radically low-powered computer vision chipset, signing deals with major device makers, including Google, Lenovo and DJI. The eight-year old company has about 180 employees with offices in Silicon Valley, Ireland and Romania.


Intel buys computer vision startup Movidius as it looks to build up its RealSense platform

#artificialintelligence

Intel's RealSense platform was the star of its Intel Developer's Forum conference in San Francisco last month and it seems the company is only looking to grow the scale and capabilities of its computer vision tech. Today, the company announced that it is acquiring the computer vision startup behind Google's Project Tango 3D-sensor tech, Movidius. In a blog post, Movidius CEO Remi El-Ouazzane announced that his startup will continue in its goal of giving "the power of sight to machines" as it works with Intel's RealSense technology. Movidius has seen a great deal of interest in its radically low-powered computer vision chipset, signing deals with major device makers, including Google, Lenovo and DJI. The eight-year old company has about 180 employees with offices inSilicon Valley, Ireland and Romania.


Google and Movidius to Enhance Deep Learning Capabilities in Next-Gen Devices Machine Vision Technology

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In turn, Google will contribute to Movidius' neural network technology roadmap. This agreement enables 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. Local computation allows for data to stay on device and properly function without internet connection and with fewer latency issues. This means future products can have the ability to understand images and audio with incredible speed and accuracy, offering a more personal and contextualized computing experience. "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 Ag?era y Arcas, head of Google's machine intelligence group in Seattle.