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There is one clear (albeit somewhat boring) application of LLM: data extraction from structured documents.

That field has made a leap forward with LLMs.

Positive impact on society includes automated extraction in healthcare pipelines.



Healthcare pipelines! All well and good until hallucinations cause death or what not!

And why is this better than employing a human. Or reducing complexity. It's not as if human wages are what causes hyper expensive US healthcare costs.

This seems like a negative.


Right now there is no human, the data just goes nowhere (i.e. it is not used).

At some point we need to be optimistic and look for incremental progress.


Unstructured*


No, I really meant structured. Extracting data from structured documents is surprisingly hard when you need very high accuracy.

What I mean by structured is: invoices, documents containing tables, etc.

Extracting useful data from fully unstructured content is very hard IMO and potentially above the capacity of LLMs (depending on your definition of "useful" and "unstructured")


But this is why I made my complexity statement in my other reply.

Why are firms sending around invoices, tables instead of parseable data. Oh I know the argument, because "so hard to cooperate" on standards, etc.

Madness.


Partly because the standards, such as X12, have a high startup cost to use them, they aren't very opinionated about the actual content, and you have to get the counterparty on board to use them.




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