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Thought the same. It's kind of infuriating to see people bashing SoTA LLMs and AI while referring to chatbots from previous era using a completely different types of technology.

And it's not like customer service of the same service providers without this tech was appreciated by people before these chatbots. I kind of imagine someone like OP bashing the human as well for incompetence if there wasn't a chatbot.



> And it's not like customer service of the same service providers without this tech was appreciated by people before these chatbots.

This is just "but humans also".

I wish our industry's collective standards didn't allow for just replacing one subpar experience with a very similar one that has less empathy and is lots cheaper.


What would your ideal proposed solution be like?

If you owned a telecom company that provided internet services and mobile plans for everyday people?


I would have thought that was obvious from my comment.

I'm with Jeff on this one.

LLMs are an obviously terrible solution for any problem that actually has a complex but invariant solution.

Personally I prefer rigid, automated questionnaire filtering that gets you to a real person as soon as possible.

I also thoroughly believe in a) human support chats and b) believing the people answering them to be decent human beings who deserve my clarity, preparedness, politeness and empathy, and I think more should be done on chat interfaces to make them slightly less amenable to stupid unstructured queries. You help people ask the question right.


But what Jeff was facing wasn't an LLM. As far as I saw it was pattern matching with hardcoded responses. Hence it had a hardcoded response about WiFi, after saying "Not WiFi". ChatGPT etc wouldn't make such a mistake.

And the final human also didn't understand the request correctly.

ChatGPT wouldn't respond with "I see you have a question about your Wi-Fi" after "Slow Internet, not slow WiFi".

I think this pattern matching was more like "automated questionnaire filtering" that you were suggesting. It's just it's very hard to do this filtering, to account for differences between "not WiFi" vs "WiFi", while it's easy with LLMs.




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