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What you’re missing is that with LLMs the chief obstacle with voice assistants changed overnight from “how do we develop a system that can easily interact in natural language” (at the time, a very hard and possibly unsolvable problem) to “how do we expose our systems to API-driven input/output” (a solvable problem that just takes time).

Case in point, I asked Siri to change my work address. She stated that I needed to use the Contacts app to do that. This is not very helpful. The issue here is not Siri’s inability to understand what I want, it is that the Contacts app does not support this method of data input. Siri is also probably not very good at extracting structured address information from me via natural language, but the new LLMs can do this easily.



> The issue here is not Siri’s inability to understand what I want, it is that the Contacts app does not support this method of data input

…which is something an LLM won’t help with.

“Just design an open ended API capable of doing absolutely anything someone might ask ChatGPT to do” is not the simple task you’re making it out to be!

There's a reason why people describe ChatGPT as a "research tool": you often need to do a bunch of iterations to get it to do the correct thing. And that's fine because it's non-destructive. But it's very far from a world where you can let it loose on a production, writable database and trust that it's going to do the correct thing.


I'm sure I've seen a headlock that someone connected their screen reader to GPT and it totally could do that kind of thing…

No idea how well, so I assume "badly"; but the API is already there.


(headline, not headlock; and now too late to edit)


50% of the time Siri’s inability to understand what I want is the issue, and I don’t even try that much, given the bad experience.




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