11–20 of 57 posts
How powerful is it?
Not very... At 15 inferences per second in fp16 for Googlenet, I'd guesstimate 50-60 GHFLOPs. That would give it very roughly 2x perf/W over TitanX.
It's still pretty interesting, though, since only need to do the training once.
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.
Seems like the more logical approach would be to have a widget app developers could easily deploy embedded TensorFlow builds in Android & iPhones. Has anyone looked into doing this or found someone already doing this?
Thought TensorFlow already did this, how is this USB different? Seems like the more logical approach would be to have a widget app developers could easily deploy embedded TensorFlow builds in Android & iPhones. Has anyone looked into doing this or found someone already doing this?
How about this kind of extra processor comes in a mobile phone, which improves regular camera vision, all health sensors, better everything that we can do with mobile phones..
How about this kind of extra processor comes in a mobile phone, which improves regular camera vision, all health sensors, better everything that we can do with mobile phones..