I want to share some of the most surprising lessons from a year spent building ML tools, what we think is needed going forwards and why we believe tha

Four lessons from a year building tools for machine learning

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2021-07-16 18:00:07

I want to share some of the most surprising lessons from a year spent building ML tools, what we think is needed going forwards and why we believe that given the right tools domain experts will play a much larger role in the future of AI.

Over the last year Humanloop has been building a new kind of tool for training and deploying natural language processing (NLP) models. We’ve helped teams of lawyers, customer service workers, marketers and software developers rapidly train AI models that can understand language, then use them immediately. We started focussed on using active learning to reduce the need for annotated data but quickly learned that much more was needed.

What we really needed was a new set of tools and workflows designed from first principles for the challenges of working with AI. Here is some of what we learned.