Machine learning for the future

Google fellow Jeff Dean outlines the history of machine learning (ML), neural networks and various ways to programme models to take advantage of raw data coming through in the form of images or audio. The growing number of applications that rely heavily on computer vision, language understanding and robotics, it can’t be denied that we are now living in the era of deep learning and large-scale neural networks. What we now want most from machine learning, said Google Senior Fellow Jeff Dean to the audience at SIGMOD 2016 keynote yesterday (Tuesday, June 28), is “understanding.” “We now have sufficient computation resources, large enough interesting data sets,” Dean told SIGMOD attendees. “We can store tons of interesting data but what we really want is understanding about that data.” In a keynote…

Link to Full Article: Machine learning for the future

Pin It on Pinterest

Share This

Join Our Newsletter

Sign up to our mailing list to receive the latest news and updates about and the Informed.AI Network of AI related websites which includes Events.AI, Neurons.AI, Awards.AI, and Vocation.AI

You have Successfully Subscribed!