[ToucanLoucan]

I VERY much more trust a coworker to know things than I do this AI, especially given not just the subject of this thread, but the larger conversation around it. ChatGPT has a reputation already for just spewing out complete nonsense. Didn't Bing's implementation argue with someone about what freaking year it was not awfully long ago?

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.

[TeMPOraL]

> Didn't Bing's implementation argue with someone about what freaking year it was not awfully long ago?

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.

[ToucanLoucan]

> I'm sorry, but that's a stellar example of holding an LLM wrong. These models are frozen in time.

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.