I work on NLP, simpler tasks like information extraction from forms. My model was based on years of painstaking labelling and architecture tweaking. But last year I put an invoice into GPT-3 and it just spit out the fields in JSON, nicely formatted. No training, just works.

At first I panicked - here we have our own replacement! What do I do now? But now I realise it was not so simple. In order to make it work, you need to massage the input to fit into 2000 tokens, and reserve the rest of 2000 for the response.

I need to check that the extracted fields really do match to the document and are not hallucinated. I have to run it again to extract a few fields that came out empty for some reason. And I have to work on evaluation of prompts, it's not just writing, it has to be tested as well. Now I have so much work ahead of me I don't know what to do first.

I believe most AI adoptions will be similar. They will solve some task but need help, or create new capability and need new development. There is almost no AI that works without human in the loop today, not even chatGPT can be useful until someone vets its output, an certainly not Tesla or Waymo SDCs.