In general I would agree, however the resulting systems of such an approach tend to be "just" expensive workflow systems, which could be done with old tech as well... Where is the real need for anything LLM here?
Extracting structured data from unstructured text comes to mind. We’ve built workflows that we couldn’t before by bridging a non deterministic gap. It’s a business SaaS but the folks using our software seem to be really happy with the result.
you are 100% right. LLMs are perfect for anything that required heuristics. "is that project a good fit for client A given the following specifications ... rate it from 1-10". stuff like that. I use it as a solution for an undefined search space/problem essentially.
it would take months with old tech to create a bot that can check multiple websites for specific data or information? so LLM reduces the time a lot? am I wrong?
Months? Scraping wasn’t a hard problem then. Classifying information is a different and more complex thing, which is what these models are very good at. Then again we had other means of classification before LLMs without having to go through chat bots.
I think classical ML should still be compared when you use an LLM as a classifier. some problems are so well defined you can just drop an SVM on it and be done with it. the biggest benefit of LLMs I think is you can get results that are ok quite fast. no need to split or clean data, compare metrics etc. etc.