Google has struck a deal with the vision processor firm behind its Tango tablets that could bring machine learning to mobile devices independent of the cloud.
Movidius today announced that Google will be sourcing the company's processors and software development environment to "introduce a new way for machine intelligence to run locally on devices."
Machine learning allows computers to interpret visuals and audio in a more natural way, rather than using comparisons to a database of information as a way of learning.
Currently, basic machine learning tech in smartphones and other mobile devices are represented in software like Apple's Siri, Microsoft's Cortana, Google Now and even Facebook's personal assistant project M.
But the software in a mobile device is limited by a mobile device's power and processing capabilities, relying instead on a connection to the internet or the cloud to help answer your questions.
Google will be using Movidius' MA2450 chip, which allows for advanced computation without the need for high power.
According to Movidius, Google's future mobile devices could have the "ability to understand images and audio with incredible speed and accuracy, offering a more personal and contextualized computing experience" without requiring the a data center.
"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 a statement.
"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."
Neither company has revealed exactly what kind of mobile devices will be packed with this machine learning tech, but we expect Google Now to become a lot smarter sooner rather than later.
Movidius and Google talk more about the partnership in the video below.