41–50 of 57 posts
Betting on local instead of cloud is always an interesting gamble. Pros: - Security - Control Cons: - Resource limitations - (...)
Haven't found any info of the availability or price. Interesting concept anyway.
Earlier quoted context omitted.
>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…
Are there any good examples of FPGA implementations of CNN? I see one example in Verilog on github: https://github.com/ziyan/altera-de2-ann/blob/master/src/ann/...
Lots of misunderstanding in this comments section. 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…
(Also, of course, this stick doesn't seem to have any kind of connectivity besides the USB to the host computer. How do I connect my camera? Having to shuffle the data from a camera to the stick passing the host computer somewhat defeats the point.)
Lots of misunderstanding in this comments section. 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…
This is their own press release. What does that kind of hardware for CV primitives have to do with deep learning? (Also, of course, this stick doesn't seem to have any kind of connectivity besides the USB to the host computer. How do I connect my camera? Having to shuffle the data from a camera to the stick passing the host computer somewhat defeats the point.)
They have hardware convolutions on 12 SHAVE cores (kind of a DSP core). It means that the chip can run some useful subset of convolutional neural networks very fast and energy efficient.
They also have 2 general purpose SPARC cores, which allows you to have a "normal" program running there. Not sure, how locked the USB stick going to be, and if running your custom program would be an option.
>How do I connect my camera? The chip itself has a couple of MIPI lanes. The USB stick likely does not expose that. And I agree, that's suboptimal.
If this is for CV, why not use the myriad DSPs from every silicon company ever?
Seems like a buzzword fueled product.
I don't see why you would need deep learning NN on a phone. If this is for CV, why not use the myriad DSPs from every silicon company ever? Seems like a buzzword fueled product.
Likewise, I can imagine people using this with an embedded Raspberry Pi.