People pointing out NLP are missing the point — pulling and crafting rules to run effective NLP is time consuming and technical. With an LLM you can just ask it exactly what you want and it interprets. That's the value; and as this deal just proved it's worth the scaling costs.

The point that is missed isn't about LLMs adequacy as a NLP technique, it's that they cost you 10000 times more for the same effect (after the upfront set-up), which is why I have my doubts that they will be used at scale, at the center of some large data ingestion pipeline. The benefit will probably be for the out of ordinary tasks and outliers.