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So what can you do with a deep-learning stick of truth? EDIT: Looks like the explanation is in a linked article: https://techcrunch.com/2016/04/28/plug-the-fat

So what can you do with a deep-learning stick of truth? EDIT: Looks like the explanation is in a linked article: https://techcrunch.com/2016/04/28/plug-the-fathom-neural-compute-stick-into-any-usb-device-to-make-it-smarter/ https://techcrunch.com/2016/04/28/plug-the-fathom-neural-com... How the Fathom Neural Compute Stick figures into this is that the algorithmic computing power of the learning system can be optimized and output (using the Fathom software framework) into a binary that can run on the Fathom stick itself. In this way, any device that the Fathom is plugged into can have instant access to complete neural network because a version of that network is running locally on the Fathom and thus the device. This reminds me of Physics co-processors. Anyone remember AGEIA? They were touting "physics cards" similar to video cards. Had they not been acquired by Nvidia, they would've been steamrolled by consumer GPUs / CPUs since they were essentially designing their own. The $79 price point is attractive. I wonder how much power can be packed into such a small form factor? It's surprising that a lot of power isn't necessary for deep learning applications.

legolassexyman 9y ago
> The $79 price point is attractive. I wonder how much power can be packed into such a small form factor? It's surprising that a lot of power isn't necessary for deep learning applications. It runs pretrained NN, which is the cheap part. So this is a chip optimized to preform floating point multiplication and that's it.
- shams93 9y ago
  Yeah I can run pretrained models on my pi3, that's not that exciting, its more exciting that 2nd handle graphics cards are dumping onto the market.
  - shams93 9y ago
    If you can use a set of say 3 of these running in paralell on a pi3 with tensorflow to train models from scratch then this is more interesting.
    - RBerenguel 9y ago
      No training, only evaluation: https://ncsforum.movidius.com/discussion/104/can-i-use-this-for-training-of-neural-network-with-tensorflow https://ncsforum.movidius.com/discussion/104/can-i-use-this-...
wyldfire 9y ago
I wonder how it stacks up against the snapdragon 410e. You can buy one on a dragonboard for roughly the same price ~$80 [1]. The dragonboard has four ARM cores, a GPU, plus a DSP. You could run OpenCV/FastCV on any or all three. [1] https://www.arrow.com/en/products/dragonboard410c/arrow-development-tools https://www.arrow.com/en/products/dragonboard410c/arrow-deve...
- zitterbewegung 9y ago
  Why not both? Plug in the USB deep-learning USB stick. Use the snapdragon to do ETL and or download models to be run on the Movidlus so that it can perform inference. I am waiting for the day that we can do some nontrivial training on mobile hardware.

legolassexyman 9y ago

> The $79 price point is attractive. I wonder how much power can be packed into such a small form factor? It's surprising that a lot of power isn't necessary for deep learning applications. It runs pretrained NN, which is the cheap part. So this is a chip optimized to preform floating point multiplication and that's it.

shams93 9y ago
Yeah I can run pretrained models on my pi3, that's not that exciting, its more exciting that 2nd handle graphics cards are dumping onto the market.
- shams93 9y ago
  If you can use a set of say 3 of these running in paralell on a pi3 with tensorflow to train models from scratch then this is more interesting.
  - RBerenguel 9y ago
    No training, only evaluation: https://ncsforum.movidius.com/discussion/104/can-i-use-this-for-training-of-neural-network-with-tensorflow https://ncsforum.movidius.com/discussion/104/can-i-use-this-...

wyldfire 9y ago

I wonder how it stacks up against the snapdragon 410e. You can buy one on a dragonboard for roughly the same price ~$80 [1]. The dragonboard has four ARM cores, a GPU, plus a DSP. You could run OpenCV/FastCV on any or all three. [1] https://www.arrow.com/en/products/dragonboard410c/arrow-development-tools https://www.arrow.com/en/products/dragonboard410c/arrow-deve...

zitterbewegung 9y ago
Why not both? Plug in the USB deep-learning USB stick. Use the snapdragon to do ETL and or download models to be run on the Movidlus so that it can perform inference. I am waiting for the day that we can do some nontrivial training on mobile hardware.