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.
These models have so many parameters that, while insufficient to memorize all text it has ever seen, it can end up memorizing some of the content. It is the difference between being able to recall a random passage versus recalling the exact thing you need. Both allow you to spill content verbatim, but one is problematic while the other can be helpful.
There are techniques to allow it it ‘read on demand’, but they are not part of the core model (i.e. the autocmpletion model / LLM) and are tacked on top of it. For example, you can tie it search engine, which Microsoft’s copilot does, and is something which I don’t think is enabled for ChatGPT by default. Or allow it to query a external data bank (Retrieval Augmented Generation).
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
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.
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.
Yeah, even setting aside the intelligence claims, I know I’d be feeling a lot more positive about LLMs as a fun theoretical tool if they weren’t being sold as personal assistants or search engine replacements etc, which even the apologists here admit they’re really really bad at.
(Also I’d argue “linguistic patterns” is pushing it. “Textual patterns” more like, it’s not supposed to have any idea about grammar or even about what “text” is.) (I say “supposed to” because who knows what sort of hacks they’re running under the hood.)
I’m not even going to engage in this thread cause it’s a tar pit, but I do think I have the appropriate analogy.
When taking certain exams in my CS programme you were allowed to have notes but with two restrictions:
Have to be handwritten;
have to fit on a single A4 page.
The idea was that you needed to actually put a lot of work into making it, since the entire material was obviously the size of a fucking book and not an A4 page, and you couldn’t just print/copy it from somewhere. So you really needed to distill the information and make a thought map or an index for yourself.
Compare that to an ML model that is allowed to train on data however long it wants, as long as the result is a fixed-dimension matrix with parameters that helps it answer questions with high reliability.
It’s not the same as an open book, but it’s definitely not closed book either. And the LLMs have billions of parameters in the matrix, literal gigabytes of data on their notes. The entire text of War and Peace is ~3MB for comparison. An LLM is a library of trained notes.
My question to you is how is it different than a human in this regard? I would go to class, study the material, hope to retain it, so I could then apply that knowledge on the test.
The ai is trained on the data, “hopes” to retain it, so it can apply it on the test. It’s not storing the book, so what’s the actual difference?
And if you have an answer to that, my follow up would be “what’s the effective difference?” If we stick an ai and a human in a closed room and give them a test, why does it matter the intricacies of how they are storing and recalling the data?
I’m not sure what you even mean by “how is it different”, but for starters a human can actually get a good mark at the bar and spicy autocomplete clearly cannot.
What you are basing this “it clearly cannot” on? Because an early iteration of it was mediocre at it? The first ICE cars were slower than horses, I’m afraid this statement may be the equivalent of someone pointing at that and saying “cars can’t get good at going fast.”
But I specifically asked “in this regard”, referring to taking a test after previously having trained yourself on the data.
Give Ken Thompson and Dennis Ritchie billions of dollars
I mean, if we took all net worth of Sam Altman and split it between these two guys who at least benefited humanity with their work we’d get at least a step closer to justice in the universe.
Getting a Turing award: $1M
Dropping out of Stanford to work on something unironically called “Loopt”: Priceless
Me, about to suggest some actually really good, thought provoking Marvel comics that somehow got made alongside the relentless superhero soap opera: oh wait now isn’t the time, we’re dunking on the AI bro
The word parameters here must be defined. Is it the weight they are talking about or the input being used to answer the question? For the former, yeah, it’s like a person was reading a book and not an open book at all. But if it were used in the input, then it is practically an open book. They have the context on the same input.
That’s like saying a person reading a book before a quiz is doing it open book because they have the memory of reading that book.
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.
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.
If it doesn’t read it on demand, how does it sometimes spill its training data verbatim then?
The trained model shouldn’t have that, right? But it does?
https://m.slashdot.org/story/422185
These models have so many parameters that, while insufficient to memorize all text it has ever seen, it can end up memorizing some of the content. It is the difference between being able to recall a random passage versus recalling the exact thing you need. Both allow you to spill content verbatim, but one is problematic while the other can be helpful.
There are techniques to allow it it ‘read on demand’, but they are not part of the core model (i.e. the autocmpletion model / LLM) and are tacked on top of it. For example, you can tie it search engine, which Microsoft’s copilot does, and is something which I don’t think is enabled for ChatGPT by default. Or allow it to query a external data bank (Retrieval Augmented Generation).
Do you read a song on demand when you are singing the lyrics verbatim?
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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
deleted by creator
and in conclusion an AI is very like an elephant, particularly the back end
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.
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
we can tell
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.
And yet they can spit out copyrighted material verbatim, or near-verbatim, how strange and peculiar.
so weird!!!
Yeah, even setting aside the intelligence claims, I know I’d be feeling a lot more positive about LLMs as a fun theoretical tool if they weren’t being sold as personal assistants or search engine replacements etc, which even the apologists here admit they’re really really bad at.
(Also I’d argue “linguistic patterns” is pushing it. “Textual patterns” more like, it’s not supposed to have any idea about grammar or even about what “text” is.) (I say “supposed to” because who knows what sort of hacks they’re running under the hood.)
lol. at least you’re honest about it
I’m not even going to engage in this thread cause it’s a tar pit, but I do think I have the appropriate analogy.
When taking certain exams in my CS programme you were allowed to have notes but with two restrictions:
The idea was that you needed to actually put a lot of work into making it, since the entire material was obviously the size of a fucking book and not an A4 page, and you couldn’t just print/copy it from somewhere. So you really needed to distill the information and make a thought map or an index for yourself.
Compare that to an ML model that is allowed to train on data however long it wants, as long as the result is a fixed-dimension matrix with parameters that helps it answer questions with high reliability.
It’s not the same as an open book, but it’s definitely not closed book either. And the LLMs have billions of parameters in the matrix, literal gigabytes of data on their notes. The entire text of War and Peace is ~3MB for comparison. An LLM is a library of trained notes.
Proceeds to actively engage in the thread multiple times
I never claimed to be good at self-restraint okay, everyone has their vices
You’re acting as if you never ate a full bar of chocolate after you told yourself you wouldn’t
amazed that that one reply was what they felt their contribution here had to be
My question to you is how is it different than a human in this regard? I would go to class, study the material, hope to retain it, so I could then apply that knowledge on the test.
The ai is trained on the data, “hopes” to retain it, so it can apply it on the test. It’s not storing the book, so what’s the actual difference?
And if you have an answer to that, my follow up would be “what’s the effective difference?” If we stick an ai and a human in a closed room and give them a test, why does it matter the intricacies of how they are storing and recalling the data?
I’m not sure what you even mean by “how is it different”, but for starters a human can actually get a good mark at the bar and spicy autocomplete clearly cannot.
What you are basing this “it clearly cannot” on? Because an early iteration of it was mediocre at it? The first ICE cars were slower than horses, I’m afraid this statement may be the equivalent of someone pointing at that and saying “cars can’t get good at going fast.”
But I specifically asked “in this regard”, referring to taking a test after previously having trained yourself on the data.
I asked Gemini and it told me that ChatGPT can’t do shit, I’m not gonna question it.
So, it’s either perfect right now, or never capable of anything. Great critical and nuanced thinking.
Thanks!
do you see why I take the shortcut?
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I mean, if we took all net worth of Sam Altman and split it between these two guys who at least benefited humanity with their work we’d get at least a step closer to justice in the universe.
Getting a Turing award: $1M
Dropping out of Stanford to work on something unironically called “Loopt”: Priceless
holy fuck you’re a moron
please go read a book, and look at some art. no, marvel media doesn’t count.
Me, about to suggest some actually really good, thought provoking Marvel comics that somehow got made alongside the relentless superhero soap opera: oh wait now isn’t the time, we’re dunking on the AI bro
The word parameters here must be defined. Is it the weight they are talking about or the input being used to answer the question? For the former, yeah, it’s like a person was reading a book and not an open book at all. But if it were used in the input, then it is practically an open book. They have the context on the same input.