How many times have you asked a co-worker about something and they gave you a convincing answer that was totally wrong? Did it make you stop asking co-workers for help?
Conversely, there are people who I will go to for topics that they are not the SME in, maybe their teammate even is, but I trust their ability to do quality research and intelligently interpret that research for case specific nuances. Like I'll go to the networking guy to talk about some DB thing because the DB guys are morons and live and die by junk SEO sites but the networking guy can think analytically and find the source of truth documentation and provide excerpts from it.
These chat bots "know" a shit ton and a half of stuff in that they are connected to the largest collection of knowledge known to man, the Internet. But "knowing" and "understanding" are two different things. The various search engines also "know" a ton about where to find things online, that doesn't mean they know shit about those things. And as we're seeing here: without the context to know that when someone wants an IP scanner, they want something good, that won't give their computer malware, that'll be reasonably priced or even open source, or even what platform, it just gives an answer based on a search.
You could just search for ip scanning software and gotten all the information BingGPT shared with the author of the piece.
And like, if you wanted to be charitable, you could say "well the author should've given more information about what they wanted" but again, that's not different from an existing search engine and more crucially: the AI didn't ask questions. Didn't ask for platform, how much they wanted to spend, if they preferred open source, or even something more general like what they were trying to accomplish. Nada. Just did a search, and reported results.
I'm sorry, but that's a stellar example of holding an LLM wrong. These models are frozen in time.
> But "knowing" and "understanding" are two different things.
Indeed, and that is a big part of misunderstanding. GPT-4 is, on many topics, closer to understanding than knowing (note that neither is a subset of the other). The conceptual patterns are there, even if sometimes are easy to accidentally overpower by the prompt, or by the sequence of tokens already emitted.
Y'all keep throwing out these gotcha statements that just make the technology you're trying to tell me is great seem more and more useless.
How can you even attempt to call something artificial intelligence if it doesn't even know the year it is!?
> Indeed, and that is a big part of misunderstanding. GPT-4 is, on many topics, closer to understanding than knowing (note that neither is a subset of the other). The conceptual patterns are there, even if sometimes are easy to accidentally overpower by the prompt, or by the sequence of tokens already emitted.
I don't think it's either understanding or knowing. Someone who knows something isn't going to spontaneously forget it because someone asked them a question incorrectly.
That specific unreliable coworker who doesn’t properly qualify that they aren’t completely certain … I believe for most people, yes.
We tend not to trust bullshitters.
Never actually. My coworkers have never told me something with confidence that they just made up. If they don't know an answer, they may provide hints and directions, but it will be clear they don't know.
i mean, in many circumstances, we absolutely stop asking them...
when i ask a trustworthy human a question, they will absolutely tell me if it is out their depths. they understand their own limits on around the subject and say so. and if they understand a little, they’ll help point towards people who would be a better authority on the subject.
that’s basic level human connection stuff.
if someone confidently gives you the wrong answer, refuses to know their own limits, and repeatedly leads you astray you don’t trust them after this do you?
One usually stops asking the bullshitter, yes.