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Comment by otabdeveloper4 | Hacker News Reader

ChatGPT relies very much on confirmation bias to do its magic. You ask something trivial you already know (and could have probably Googled in 15 seconds), you get back something glib and smooth in reply and you are wowed by how smart GPT seems to be.

It is significantly less impressive when you ask something you don't already know and can't Google easily.

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That's more or less my experience with code generation. To be fair, I haven't paid for ChatGPT-4, which I'm told is much better. Still, if I ask 3.5 a leetcode style problem I've done, it comes up with a good solution. If I ask it a leetcode style problem I just made up, it generally comes up with garbage -- the solution doesn't work, solves a different problem than I asked, or ignores a restriction I imposed.

The place where I've found it really handy is if I want to make stuff up. Things like "Give me a mundane event that could happen to a 25-year-old leatherworker for a story I am writing." or "What should I name a piece of software that allows people to collaboratively draw a landscape scene?"

> It is significantly less impressive when you ask something you don't already know and can't Google easily.

What's more, you absolutely cannot trust it with that kind of query.

Its insane to me that LLMs are primarily being pitched as fact givers. That is such a bad fit... They are so much better at writing poetry and fiction in chunks, or maybe analyzing stuff from the context.

I actually love bing bot when searching for something very nuanced ("no, not like that ... [explanation]"). I haven't used Google's AI search yet; why learn a new tool?

I use it mostly for complex queries I can't Google and that's where it excels for me.

I use it _after_ doing complex googling to get an answer, and it is almost universally wrong, or misses the point completely.

It often just takes a few minutes of verifying against your understanding and use case, and ask a few more questions, and you can identify incorrect answers and arrive at the verified correct answer, or useful answer if there is no correct answer, rather quickly- which should be how most people operate in most interactions with information. Not to mention it can now be forced to search the web and cite its sources.

I think at some point it just becomes a preference of your interface to the data your searching, and I've been enjoying natural language

How would you even know that it's less impressive if you don't know the subject matter?

Because it can be easy to test the result even if you don't know how to come up with a solution ?

If I asked you to build a light switch I don't need to know anything about EE to see that the light turns on/off when I flip the switch.

LLMs often fail to provide functional solutions for non trivial stuff (not impressive) - and once you know more about the domain, you usually figure out that the light switch will likely burn down your house in few hours because it's overheating.

Could you discern a good teacher from a bad teacher when you were in school and the topics were new? Did you ever find out someone was unreliable after they gave you some facts and later you discovered they were wrong? You won't have a 100% rate of detection and it'll be lower than in subjects you know about, but after a few times you can see if the new stuff it tells you is right or not.

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