Comment by billythemaniam

I agree that the state of the art isn't ready yet for general consumption. I think GPT-3, etc are good enough to help with a wide range of tasks with guardrails. To clear, I don't mean guardrails around racist language, etc which is a separate topic. Rather guardrails around when to use the results because of limitations and accuracy.

For example, let's say you have a website that sells clothes and you want to make the site search engine better. Let's also say that a lot of work has been done to make the top 100 queries return relevant results. But the effort required to get the same relevance for the long tail of unique queries, think misspellings and unusual keywords, doesn't make sense. However you still want to provide a good search experience so you can turn to ML for that. Even if the model only has a 60% accuracy, that's still a lot better than 0% accuracy. So applying ML queries outside the top 100, should improve the overall search experience.

ChatGPT/GPT-3 has an increased the number of areas where ML can be used but it still has plenty of limitations.