I mean you still gotta understand some shit for Ctrl+F to be helpful. If you’ve ever taken an open book quiz without prior study you’ll learn pretty quick that open book does NOT = easy A (depending on the class / prof I guess, but you get the gist).
So, open book Ctrl-F’able bar exam, I could probably get an okay score just on key word matching, not knowing jack shit about law; but it’d be far from a perfect score. Current state of machine learning appears to be in a comparable boat.
your post shows a serious lack of comprehension. just because so many of the posters in this thread are idiots didn’t mean you have to participate too.
(CPU time extremely counts, and resource-wise with these things it’s really quite a lot)
Steelmanning what this person said, I think the issue is that your ability to CTRL+F through a book during a time-limited exam is not as strong as even a single computer clocked at GHz doing the same thing. You can CTRL+F through a single book in the same time it takes it to CTRL+F through the entire body of knowledge.
But the AI isn’t “recalling” in the same way you do, it doesn’t “remember” what it “read”, it “reads” on demand and has instant access to essentially all of the information available online it was trained on (E: though it’s becoming more or less the same thing, and is definitely the same when it comes to law books for example), from which it collects the necessary details if and when it needs it.
So yes, it is literally “sat” there with all the books open in front of it, and the ability to pinpoint a bit of information in any one of all the books in milliseconds.
Yes, it does, from the information it was trained on (or - stored), which like you say, requires a lot of hardware power so it can be accessed on demand. It isn’t just manifesting the information out of thin air, and it definitely doesn’t “remember” in the same way we do (E: even the best photographic memory isn’t the same as an indexable one).
It’s definitely not indexed, we use RAG architectures to add indexing to data stores that we want the model to have direct access to, the relevant information is injected directly in the context (prompt). This can somewhat be equated to short term memory
The rest of the information is approximated in the weights of the neural network which gives the model general knowledge and intuition…akin to long term memory
or it can be equated to a shitty database and lossy compression (with artifacts in the form of “hallucinations”), but that doesn’t make the tech sound particularly smart, does it?
but half the posts in your history are in this thread and that’s too many already
but rofl holy shit at “glad to see someone else knows how they work” given the … depth of understanding, shall we say? that was demonstrated in this thread
that’s a misleading and meaningless way of putting it. if I rip a page out of my textbook and bring it into an exam room, I do not have with me all the data in my textbook. and yet
It doesn’t do that, either. LLMs retain the linguistic patterns found in textbooks, nothing more. It’s remarkable that they can do so much with this information alone, but it’s still a far cry from genuine intelligence.
It’s more like taking a digital copy into the test room with you and Ctrl+F’ing every question/answer.
Except it’s not, because they can’t perfectly recall everything.
It’s more like reading every book in the world, and someone asking you what comes next after “And I…”.
“will alwaaays love you…”
Easy. No other answer.
I mean you still gotta understand some shit for Ctrl+F to be helpful. If you’ve ever taken an open book quiz without prior study you’ll learn pretty quick that open book does NOT = easy A (depending on the class / prof I guess, but you get the gist).
So, open book Ctrl-F’able bar exam, I could probably get an okay score just on key word matching, not knowing jack shit about law; but it’d be far from a perfect score. Current state of machine learning appears to be in a comparable boat.
This is a computer. Time (in this aspect) isn’t an issue.
your post shows a serious lack of comprehension. just because so many of the posters in this thread are idiots didn’t mean you have to participate too.
(CPU time extremely counts, and resource-wise with these things it’s really quite a lot)
Steelmanning what this person said, I think the issue is that your ability to CTRL+F through a book during a time-limited exam is not as strong as even a single computer clocked at GHz doing the same thing. You can CTRL+F through a single book in the same time it takes it to CTRL+F through the entire body of knowledge.
But the AI isn’t “recalling” in the same way you do, it doesn’t “remember” what it “read”, it “reads” on demand and has instant access to essentially all of the information
available onlineit was trained on (E: though it’s becoming more or less the same thing, and is definitely the same when it comes to law books for example), from which it collects the necessary details if and when it needs it.So yes, it is literally “sat” there with all the books open in front of it, and the ability to pinpoint a bit of information in any one of all the books in milliseconds.
It doesn’t read on demand, it reads once when it’s being trained, and it later recalls what it learnt from that training.
Training LLMs takes a very long time and a lot of hardware power.
Yes, it does, from the information it was trained on (or - stored), which like you say, requires a lot of hardware power so it can be accessed on demand. It isn’t just manifesting the information out of thin air, and it definitely doesn’t “remember” in the same way we do (E: even the best photographic memory isn’t the same as an indexable one).
It’s definitely not indexed, we use RAG architectures to add indexing to data stores that we want the model to have direct access to, the relevant information is injected directly in the context (prompt). This can somewhat be equated to short term memory
The rest of the information is approximated in the weights of the neural network which gives the model general knowledge and intuition…akin to long term memory
or it can be equated to a shitty database and lossy compression (with artifacts in the form of “hallucinations”), but that doesn’t make the tech sound particularly smart, does it?
but half the posts in your history are in this thread and that’s too many already
People have such crazy misconceptions about AI. Glad to see someone else knows how it works at least.
oh do fuck off
awww, I just got another bowl of popcorn!
but rofl holy shit at “glad to see someone else knows how they work” given the … depth of understanding, shall we say? that was demonstrated in this thread
I’m not a big AI guy but it’s really not quite like that, models do NOT contain all the data they were trained on.
Edit: I have no idea what’s going on down below this comment
lol. at least you’re honest about it
that’s a misleading and meaningless way of putting it. if I rip a page out of my textbook and bring it into an exam room, I do not have with me all the data in my textbook. and yet
It doesn’t do that, either. LLMs retain the linguistic patterns found in textbooks, nothing more. It’s remarkable that they can do so much with this information alone, but it’s still a far cry from genuine intelligence.
we can tell
The guy above you is right though. So what are you on about?