SVAIL Tech Notes: A Look at Persistent Recurrent Neural Nets - Baidu Research

Today we posted a new Tech Note in which Greg Diamos, a research scientist at Baidu's Silicon Valley AI Lab, discusses a new technique for speeding up the training of deep recurrent neural networks. At SVAIL, our mission is to create AI technology that lets us have a significant impact on hundreds of millions of people. We believe that a good way to do this is to improve the accuracy of speech recognition by scaling up deep learning algorithms on larger datasets than what has been done in the past. These algorithms are very compute intensive, so much so that the memory capacity and computational throughput of our systems limits the amount of data and the size of the neural network that we can train. So a big challenge is figuring out how to run deep learning algorithms more efficiently.