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This is a really interesting use-case

Applying "transformations" or classifying data in this way without having to setup a lot of detail-work seems like a real labor-saver/multiplier

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My company has gone years wanting our product catalog to have structured data around our products but not going through the tedium of extracting it all. about an hour of prompt tweaking and it can pull, normalize, summarize and output valid json from all of our products. Basically pulling it out of a big unstructured html blob.

I've started thinking about LLMs as a "universal coupling", if that makes sense? It's wild to be able to conceive of APIs to plain text, and natural language queries on structured APIs, but that's what we've got.
My mind was really opened by Nat Friedman's work in GPT for browser automation: https://github.com/nat/natbot
And of course using langchain/ReACT.
So different from ChatGPT and (imo) way more intriguing.

mentioned in this blog post: https://interconnected.org/home/2023/02/07/braggoscope

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