SAN MATEO, California – April 28th, 2016 – Movidius, the leader in low-power machine vision technology, today announced both the Fathom Neural Compute Stick – the world's first deep learning acceleration module, and Fathom deep learning software framework. Both tools hand-in-hand will allow powerful neural networks to be moved out of the cloud, and deployed natively in end-user devices. The new Fathom Neural Compute Stick is the world's first embedded neural network accelerator. With the company's ultra-low power, high performance Myriad 2 processor inside, the Fathom Neural Compute Stick can run fully-trained neural networks at under 1 Watt of power. Thanks to standard USB connectivity, the Fathom Neural Compute Stick can be connected to a range of devices and enhance their neural compute capabilities by orders of magnitude.
The Myriad 2 is the chip found in the previously mentioned DJI and FLIR products. It's able to handle many processes simultaneously, which is exactly what neural networks call for. Because it's specifically designed for this -- its architecture is very different from the GPUs and CPUs that typically handle processing -- it offers a lot of grunt without requiring much power. It can handle up to 150 gigaFLOPS (150 billion floating-operations per second) while consuming no more than 1.2 watts. The idea is you plug it into the USB 3.0 port of any system running Linux to get a "20-30x performance improvement in neural compute."
To make this a reality, chip maker Movidius has introduced the Fathom Neural Compute Stick. Dubbed as the "the world's first embedded neural network accelerator", this USB stick contains a deep learning processing accelerator. This stick could be connected to an existing Linux device to increase the efficiency of neural networking tasks 20-30 times. Movidius Fathom performs its task at more than 150GFLOPS, consuming less than 1.2W. "Featuring a full-fledged Myriad 2 VPU, the Fathom Neural Compute Stick not only enables rapid prototyping, but also delivers high levels of neural network compute to existing devices via a USB port," tells the explainer on Movidius website.
It's not often a unique product shows up in our email and news feeds, but we became curious over something a little different today: a USB compute module for neural networks and machine learning. Movidius' new Fathom Neural Compute Stick is an ultra-low power processor featuring a Myriad 2 VPU (vision processing unit), providing up to 150 GFLOPS of compute for about 1 Watt of power. Neural networks and machine learning have fascinated people for a long time; teaching machines and computers to think rather than simply'do'. The problem is that it's extremely difficult; not just from a hardware perspective (people aren't binary), but from an academic and psychological perspective too; the how we think. Instead of writing code that goes through images or live camera feeds, doing edge detection, writing more algorithms to define shapes and generally teach the computer what it needs to do (explicitly), neural networks are a way to teach a computer to teach itself – often creating systems that are faster and more accurate than the hand-coded method.
Chip makerMovidius has unveiledthe worlds first embedded neural network accelerator. Known as the Fathom Neural Compute Stick, this device could be pluggedinto a Linux device to allow it to performfunctions like image recognition, language comprehension, and pattern detection. To make this a reality, chip maker Movidius has introduced the Fathom Neural Compute Stick. Dubbed as thethe worlds first embedded neural network accelerator, this USB stick contains a deep learning processing accelerator. This stick could be connected to an existing Linux device to increase the efficiency of neural networking tasks 20-30 times.