So, imagine you need to evaluate applications for some line of credit by reading the documents associated and classifying the businesses in a taxonomy of busine

So, imagine you need to evaluate applications for some line of credit by reading the documents associated and classifying the businesses in a taxonomy of business types. Depending on volume this could be millions of documents. You can prime an LLM context with the taxonomy and examples of each, then evaluate each document in a clean primed context asking for a classification if it’s clear and a request for review if it’s not clear. This works exceptionally well in practice, almost double the precision and recall of humans. Businesses are replete with similar relatively trivial classification problems that often require armies of low paid low skill workers but are fairly crucial to the ongoing operations of the business. Chat bots are the default thing people gravitate to with LLMs because they’re the example in chatgpt. But that’s a really uncreative use of the tech, and the domain they’re exposed to is pretty open ended leaving them subject to hallucination, prompt injection, etc. A more constrained domain with more business impact is where I see meaningful applications happening.