Google Fellow Talks Neural Nets, Deep Learning EE Times

SAN FRANCISCO--We are already living with deep learning and large-scale neural networks, as evidenced by the growing number of applications that rely on computer vision, language understanding, and robotics. In a keynote talk, Dean outlined the history of machine learning (ML) and neural networks and various ways to program models to take advantage of raw data coming through in the form of images or audio. Dean pointed to Google--s speech recognition team, which through the use of neural networks reduced word errors by 30%. The team used the networks to replace the acoustic model of its speech recognition pipeline -- which uses raw audio waveforms to determine sounds and words -- and achieved --the biggest single improvement in two decades.-- The fundamental problems being solved by ML and neural networks can be found in other fields such as medical and satellite imaging.