Movidius chips have been showing up in quite a few products recently. It's the company that helps DJI's latest drone avoid obstacles, and FLIR's new thermal camera automatically spot people trapped in a fire, all through deep learning via neural networks. It also signed a deal with Google to integrate its chips into as-yet-unannounced products. Now, the chip designer has a product it says will bring the capacity for powerful deep learning to everyone: a USB accessory called the Fathom Neural Compute Stick.
The Fathom contains the Myriad 2 MA2450 VPU paired with 512MB of LPDDR3 RAM. 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.
Unlike Tegra's solutions for deep learning, the Fathom isn't a standalone system. 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." You can use the Fathom to rapidly prototype neural networks, moving to something with a lot more power once you're ready to deploy.
To read more, click here.