Uh, I understand the sentiment, but the model doesn’t know anything. And it’s legit really hard to differentiate between factual things and random bullshit it made up.
It “knows” as in it has access to the information and the ability to provide the right info for the right context.
Any part of that process the AI can just “bullshit” and fills in the gaps with random stuff.
Which is what you want when it’s “learning”. You want it to try so it’s attempt can be rated, and the relevant info added to its “knowledge”.
But when consumers are using it, you want it to say “I can’t answer that”. But consumers are usually stupid and will buy/use the one that says “I can’t answer that” the least.
And it’s legit really hard to differentiate between factual things and random bullshit it made up.
Which is why AI should tell end users “I don’t know” more often.
Do you not understand how “answer unavailable” is a better answer than taking a small percent of strips of paper at random and filling in the rest with words that sound relevant?
taking a small percent of strips of paper at random and filling in the rest with words that sound relevant?
It’s like a mad libs
Right. They’re text generators. That’s the technology. It can’t do what you’re demanding because that’s not how it works. LLMs aren’t magic answer machines. They don’t know when to say “answer not available”. They don’t know what they’re being asked. They don’t know anything.
Yeah, no one can make it say “I don’t know” because it is not really AI. Business bros decided to call it that and everyone smiled and nodded. LLMs are 1 small component (maybe) of AI. Maybe 1/80th of a true AI or AGI.
Honestly the most impressive part of LLMs is the tokenizer that breaks down the request, not the predictive text button masher that comes up with the response.
Honestly the most impressive part of LLMs is the tokenizer that breaks down the request, not the predictive text button masher that comes up with the response.
Yes, exactly! It’s ability to parse the input is incredible. It’s the thing that has that “wow” factor, and it feels downright magical.
Unfortunately, that also makes people intuitively trust its output.
Uh, I understand the sentiment, but the model doesn’t know anything. And it’s legit really hard to differentiate between factual things and random bullshit it made up.
It “knows” as in it has access to the information and the ability to provide the right info for the right context.
Any part of that process the AI can just “bullshit” and fills in the gaps with random stuff.
Which is what you want when it’s “learning”. You want it to try so it’s attempt can be rated, and the relevant info added to its “knowledge”.
But when consumers are using it, you want it to say “I can’t answer that”. But consumers are usually stupid and will buy/use the one that says “I can’t answer that” the least.
Which is why AI should tell end users “I don’t know” more often.
It doesn’t, though, any more than you have access to the information in a pile of 10 million shredded documents.
Right, in this case that we’re talking about…
Do you not understand how “answer unavailable” is a better answer than taking a small percent of strips of paper at random and filling in the rest with words that sound relevant?
It’s like a mad libs
Right. They’re text generators. That’s the technology. It can’t do what you’re demanding because that’s not how it works. LLMs aren’t magic answer machines. They don’t know when to say “answer not available”. They don’t know what they’re being asked. They don’t know anything.
If you feel this is a simple solution, I strongly suggest you write up exactly how you do this and make yourself a billion dollars.
Yeah, no one can make it say “I don’t know” because it is not really AI. Business bros decided to call it that and everyone smiled and nodded. LLMs are 1 small component (maybe) of AI. Maybe 1/80th of a true AI or AGI.
Honestly the most impressive part of LLMs is the tokenizer that breaks down the request, not the predictive text button masher that comes up with the response.
Yes, exactly! It’s ability to parse the input is incredible. It’s the thing that has that “wow” factor, and it feels downright magical.
Unfortunately, that also makes people intuitively trust its output.