Real estate's a big one. If you wanted to find publicly-available historical information about who owned a house and how many times it changed hands, the format of the data will change completely from state to state and country to country. An LLM that can rip through millions of these documents (both digital and on paper with GPT-4V) and generate clean, normalized and structured JSON will be absolutely huge.
Healthcare's another. Exchanging information between benefits brokers is madness because of inconsistent data formats.
A more consumer-facing example: exporting/joining data from one or more apps to migrate into another app. This is a hellish process most of the time that an LLM could, theoretically, reduce to seconds (not counting execution time).
Healthcare's another. Exchanging information between benefits brokers is madness because of inconsistent data formats.
A more consumer-facing example: exporting/joining data from one or more apps to migrate into another app. This is a hellish process most of the time that an LLM could, theoretically, reduce to seconds (not counting execution time).