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Intel and Movidius  (Source: Intel)
As of today, Movidius and Intel have delivered deep learning into a small USB stick that goes for $79 in Mouser and RS Components.

Movidius and Intel have brought deep learning into a very small USB device that cost $79, with the device carrying AI to hardware with ease. Last year during April, Movidius displayed its first application of this device, at which was referred to as the Fathom Neural Compute Stick. The Product was not able to get out the public by the company quickly as they intended due to their busy acquisition process from Intel.


Photo Source: Movidius
The goal of Movidius has substantially been to carry this form of image based deep learning from the cloud to the edge through its Myriad 2 visual processing unit. The chipsets are being used on whole lot of things such as drones to AR headset and security cameras, which enables them in getting to identify and recognize objects in the world surrounding them.

The Movidius Neural Computer Stick places one of these virtual processing units into a USB 3.0 stick, offering researchers, developers the capability to implement prototyping, validation, and deployment of inference applications offline, which in turn can carry about an amass of latency and power consumption enhancement.


Photo Source: The Verge
The device is supported when associated to constrained host computing devices such as Raspberry Pi, the compute stick provides pull and play intelligence. Impressively this news comes after a month Intel announced its cancellation plans on the continuation of Joule, Galileo and Edison compute modules.
 
Getting acquired from Intel has bestowed Movidius a few more flexibility in adding features such as the attainment to plug in a few of the compute sticks to accumulate more deep learning power. As for the manufacturing aspect, Movidius has also been able to take down its price from its original $99 to the current $79 price even as its builds has obtained more size.  The device is now available for purchase from Mouser and RS Components.

Sources: Flipboard, Tech Crunch





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