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How about this kind of extra processor comes in a mobile phone, which improves regular camera vision, all health sensors, better everything that we can do with mobile phones..
The Google Tango uses the Myriad V1. The new tango to be released in may comes with this new V2 chip.
look like fraud
http://www.theverge.com/2016/3/16/11242578/movidius-myriad-2...
This is a dev board, not a consumer product. And (contrary to the title) the press release explicitly says that it is not intended for "deep learning." Acceleration is needed for training -- not running the models themselves. A quick glimpse of the power used (1 watt) lets you know exactly how much "acceleration" is going on in here. This is meant for tiny devices. EDIT: My point is that this is a small-run dev board…
>Acceleration is needed for training -- not running the models themselves This isn't true. Running neural networks (including CNNs) can be computationally and power intensive, and lends itself to the vector operations of GPUs, FPGAs, and ASICs. Putting the computations on devoted hardware could enable embedded applications that simply aren't possible otherwise. Here's a whitepaper by Microsoft about using FPGA's to s…
I see one example in Verilog on github: https://github.com/ziyan/altera-de2-ann/blob/master/src/ann/...
This is a dev board, not a consumer product. And (contrary to the title) the press release explicitly says that it is not intended for "deep learning." Acceleration is needed for training -- not running the models themselves. A quick glimpse of the power used (1 watt) lets you know exactly how much "acceleration" is going on in here. This is meant for tiny devices. EDIT: My point is that this is a small-run dev board…
>Acceleration is needed for training -- not running the models themselves This isn't true. Running neural networks (including CNNs) can be computationally and power intensive, and lends itself to the vector operations of GPUs, FPGAs, and ASICs. Putting the computations on devoted hardware could enable embedded applications that simply aren't possible otherwise. Here's a whitepaper by Microsoft about using FPGA's to s…
Have you played with Apple Accelerate? They've been baking this stuff into their chips for quite some time. Apple's FFT outperforms FFTW. https://developer.apple.com/library/mac/navigation/#section=...
How about this kind of extra processor comes in a mobile phone, which improves regular camera vision, all health sensors, better everything that we can do with mobile phones..
Someday they will be I'm sure. Probably part of the SoC. But not yet, software is not ready for it yet.
Earlier quoted context omitted.
Hey, I'll bite. Why do you think that?
their product is based on a buzz word and uses unknown hardware, the specs seem underwhelming (1W + usb = ?). their page is filled with videos of models and nature shots and a bunch of news categories that have a few articles from 2013/14. there's no way to order anything, yet they put out some wild claims: 'With Fathom, every robot, big and small, can now have state-of-the-art vision capabilities' 'It means the same…
Movidius makes low power neural network processors for mobile application. The Myriad V1 is used in google tango and the V2 (what the USB stick has) is used in the new DJI Phantom 4.
http://www.theverge.com/2016/3/16/11242578/movidius-myriad-2...
The Myriad chips are interesting because they combine MIPI camera interface lanes on the same chip as a general purpose NN/CV processor and an SDK suite of hardware accelerated computer vision functions (edge detection, Guassian blur, etc).
here's the white paper for the chip: http://uploads.movidius.com/1441734401-Myriad-2-product-brie...
Because programming these chips essentially requires having the hardware, and because the hardware was very hard to come by, programming these chips was mostly limited to Google, DJI, and other big partners.
With this release the everyday developer has access to these vision processing chips, and the barrier to development entry is considerably lower.
This is not meant to replace your titan X gpu.
You guys know if the Myriad V2 processor is locked (just neural networks) or it will be programmable?