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A Deep Learning USB Stick

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Re: A Deep Learning USB Stick

#3

Post by tacos »

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 for a chip for some future $19 nannycam. It's not an "accelerator" you install on your PC to put your graphics card to shame running TensorFlow.

EDIT #2: This is another one of those HN threads that's overrun by enthusiasts. Jamming a chip onto a stick is simply how they sell embedded crap now.

Here's a crypto chip that'll really get you guys going: http://www.atmel.com/tools/AT88CK590.aspx

Re: A Deep Learning USB Stick

#5

Post by skykooler »

pboutros wrote: post #2

Betting on local instead of cloud is always an interesting gamble. Pros: - Security - Control Cons: - Resource limitations - (...)

Local is also useful in situations with limited or no internet access. Say you're trying to do deep recognition on a live video feed: many places this would be useful simply do not have the bandwidth available to stream video.

Re: A Deep Learning USB Stick

#6

Post by dgacmu »

tacos wrote: post #3

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 actually useful for both. If you're running in a constrained, mobile or sensor environment, then you really do want acceleration that improves your power efficiency. It's also useful if you do high volume serving, but that's obviously not the case here.

(For example, Google's voice recognition on Android can run when offline.)

Re: A Deep Learning USB Stick

#7

Post by mattnewton »

pboutros wrote: post #2

Betting on local instead of cloud is always an interesting gamble. Pros: - Security - Control Cons: - Resource limitations - (...)

It looks like this is for running already-trained networks, and I think that's really the only practical way to do things right now if you want to make sense of something like video in real time because of bandwidth constraints. It looks like training would happen in 'the cloud' or similar.

Re: A Deep Learning USB Stick

#10

Post by rm999 »

tacos wrote: post #3

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 speed up CNNs: http://research.microsoft.com/apps/pubs/?id=240715

Article by Google explaining the importance of optimizing neural networks to run on mobile phones: http://googleresearch.blogspot.com/2015/07/how-google-transl...

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