The first question you might have is, why even bother? Aren't neural networks fast enough already? And that's a good question. The answer depends on the application. If we were classifying whether something is a hot dog or not a hot dog, we'd be fine with out-of-the-box inference speeds. Autonomous vehicles, however, are more demanding than just identifying hot dogs. The perception system in our vehicle has to make predictions in real time. We can't use cloud computing resources due to the latency. So all of these predictions must take place on the vehicle computational hardware. Squeezing every last bit of performance out of this hardware is crucial.
Nvidia
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to a successful dating, improves confidence
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Why are inference optimizations', 'important to deep learning?', '"Aren't neural networks"', 'fast enough?'
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"Register for Udacity's"', 'Self-Driving Car', 'Nanodegree Program', 'at', 'www
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Deep Learning in Udacity​'s Self-Driving Car Nanodegree