Deploying at Scale

In 20 18, we tried to educate people about the broad a diversity of work loads that are actually in play when you're talking about machine learning. We had to get caught up on many, many years worth of m l research and work. Before this it was the wild west. And i think for the most part, people over optimized and over pivoted on pecific subsets of machine learning. So now we've started to agree upon what are the what are the work loads that we're going to focus on. It's a very diverse set of work loads.