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Analog computing has a lot of yet unrealized potential for machine learning algorithms. However, currently it does not make sense to build a specialized analog
by p1esk 9y ago
Analog computing has a lot of yet unrealized potential for machine learning algorithms.
However, currently it does not make sense to build a specialized analog chip to run specific type of ML algorithms, because algorithms are still being actively developed. I don't see GPUs being replaced by ASICs any time soon. And before you point to something like Google's TPU, the line between such ASICs and latest GPUs such as V100 is blurred.
- deepnotderp 9y agoPlease explain where analog computation has a benefit over digital that outweighs its numerous disadvantages.
- p1esk 9y agoWait, aren’t you working on analog chips?
- deepnotderp 9y agoNo. You may have confused me with the Isocline/Mythic guys or a red herring comment. Our approach to deep learning chips is very public and amongst the craziest...A̶n̶d̶ ̶e̶v̶e̶n̶ ̶I̶ ̶w̶o̶u̶l̶d̶n̶'̶t̶ ̶t̶o̶u̶c̶h̶ ̶a̶n̶a̶l̶o̶g̶ ̶c̶o̶m̶p̶u̶t̶a̶t̶i̶o̶n̶ To clarify: I'm always open to opposing evidence, but based on the data at the moment, I believe that analog computing buys you very little.
- p1esk 9y agoI'm sure you know both cons and pros of analog computing. As long as you can significantly improve digital tech every year, keep doing that. But as soon as that stops, or becomes too expensive, analog is the way forward.
- deepnotderp 9y agoAgain, what advantage does analog have? People seem to assume that analog intrinsically consumes less power, which due to bias and leakage currents isn't true in the general case.
- sanxiyn 9y agoI define GPU as something that can efficiently implement DirectX. Hence TPU is not GPU. And I predict ML algorithms will run on non-GPU, soon-ish.