Machine Learning

Gibbon: Data is changing so rapidly, how do you sort of accommodate for the rate of change? And in addition, i think that rate of changes also can be overwhelming to people who are wanting to maybe make the transition into machine learning. A lot of our field has transition from classical stuff to m l stuff in a relatively rapid rot. Being able to be flexible pr starts to become very, very important. It's having this fast iteration cycle easily trumping raw performance.