Domain-specific AI isn’t here quite yet, but deep language learning models like BERT and GPT-3 suggest it’s just a matter of time before your niche sees its own transformative AI innovations.

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningWith recent reports on deep learning language models like Google BERT and OpenAI’s GPT-3, it’s easy to assume that true AI is here and ready to revolutionize businesses everywhere. Although AI is already remaking businesses, it’ll take a few more years for the smarts exhibited in things like GPT-3 to make their way into deep, narrow domains. That’s because the advances we’ve seen over the last couple of years draw upon general, internet-scale learning. They can’t help you develop a new cancer treatment or design the wing of a new aircraft because they haven’t been trained on deep, domain-specific data.

Will there be a GPT or BERT to provide human-level insight for your domain? Eventually, but not for a while. Models like BERT and GPT-3 draw upon the enormous data offerings of the public internet, giving them a superhuman breadth of knowledge. Unfortunately for us, these mega-models are better at “faking” their understanding than actually knowing what they’re talking about. This is fine when you ask them to do something low-stakes like write a poem or talk about a historical event . It’s less acceptable when you need to know about the side effects or possible drug interactions of a new breast cancer drug.

This problem arises because AIs rely on oceans of data to function. Most domain areas aren’t vast oceans, however. Instead, they’re large lakes, at best. This relative lack of data may seem surprising. You read all the time that businesses are drowning in data. The more specific your problem gets, however, the less data your AI has to draw upon. […]

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