The big difference with Google and AutoML is that Google was already doing lots of machine learning in the past, just not deep learning. With deep learning it

The big difference with Google and AutoML is that Google was already doing lots of machine learning in the past, just not deep learning. With deep learning it took the transition seriously internally as well: there's a huge push to get all models to use Tensorflow - even if the transition itself is painful - and this helps the infrastructure providers as well to gather feedback. With IBM it all started as a very successful research project, but instead of working more on the Watson system, it decided to rename dumber projects to be under the Watson umbrella as well thereby giving the impression that it's the same system that won in Jeopardy.