Figure Eight and Google for AutoML Training

Yes, this is the Grail ... good training data, initially and ongoing, is essential.  Also sufficient contextual metadata.   We had projects fail because we did not consider these issues.  Was much impressed with a Figure Eight webinar I attended, they appear to understand the issues more than others.  Ultimately in autonomous learning,  you have to plan for re-learning,   Will be following up.

Figure Eight partners with Google to give AutoML developers better training data   By Frederic Lardinois in TechCrunch

Figure Eight, a platform that helps developers train, test and fine-tune their machine learning models, today announced a major new collaboration with Google that essentially turns Figure Eight into the de facto standard for creating and annotating machine learning data for Google Cloud’s AutoML service.

As Figure Eight’s CEO Robin Bordoli told me, Google had long been a customer, but the two companies decided to work closer together now that AutoML is launching in beta and expanding its product portfolio, too. As Bordoli argues, training data remains one of the biggest bottlenecks for developers who want to build their own machine learning models — and Google recognized this, too. “It’s their recognition that the lack of training data is a fundamental bottleneck to the adoption of AutoML,” he told me.

Since AutoML’s first product focuses on machine vision, it’s maybe no surprise that Figure Eight’s partnership with Google is also currently mostly about this kind of visual training data. Its service is meant to help relatively inexperienced developers collect data, prepare it for use in AutoML and then experiment with the results. ... "