&gt;Acceleration is needed for training -- not running the models themselves<p>This isn&#x27;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&#x27;t possible otherwise.<p>Here&#x27;s a whitepaper by Microsoft about using FPGA&#x27;s to speed up CNNs: <a href="http:&#x2F;&#x2F;research.microsoft.com&#x2F;apps&#x2F;pubs&#x2F;?id=240715" rel="nofollow">http:&#x2F;&#x2F;research.microsoft.com&#x2F;apps&#x2F;pubs&#x2F;?id=240715</a><p>Article by Google explaining the importance of optimizing neural networks to run on mobile phones: <a href="http:&#x2F;&#x2F;googleresearch.blogspot.com&#x2F;2015&#x2F;07&#x2F;how-google-translate-squeezes-deep.html" rel="nofollow">http:&#x2F;&#x2F;googleresearch.blogspot.com&#x2F;2015&#x2F;07&#x2F;how-google-transl...</a>