Duration: 5:30

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It’s time to solve deep learning’s productivity problem.
Deep learning is fueling breakthroughs in everything from consumer mobile apps to image recognition. Yet running deep learning-based AI models poses many challenges. One of the most difficult roadblocks is the time it takes to train the models.

The need to crunch lots of data and the computational complexity of building deep learning-based AI models also slows down the progress in accuracy and the practicality of deploying deep learning at scale. It’s the training times — often measured in days, sometimes weeks — that slow down implementation.

In order to cut the time it takes to create deep learning models with high precision, we need to reduce the time associated with deep learning training from days to hours to minutes or seconds.