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AI is 'not smart' so what's next in artificial intelligence?

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Re: AI is 'not smart' so what's next in artificial intelligence?

#71

Post by threethirtytwo »

guenthert wrote: post #50
threethirtytwo wrote: post #42

Earlier quoted context omitted.

this is profoundly false. AI not only can learn, it is built entirely from learning. The field is called machine learning after all. Not only that... AI is NOT only learning during the training phase... LLMs learn in real time the minute you talk to it. It learns something and saves those learnings in a context window or somewhere else if you want it to exist beyond the context window. All of the above runs on static…

Correct me if I'm wrong, but if a profound insight is gathered in session 1 with user A and stored in context A1, this might be available to user A in session 2, if that still has access to context A1, but won't be available to user B in any of his/her sessions until that NN is retrained with input which includes at least some of the information from context A1.

You are wrong again in every possible count. Since you think in terms of algebra think like this: there is context SP which is context window shared between all sessions, that is called the system prompt. Then there is the context window called memory M which is shared between all sessions under a user and then finally there context CW (current window) which is the context comprised of the queries from the current chat session. Total context = SP + CW + M.

M is the context window that doesn’t require retraining that allows the LLM to “learn” in the same way humans do. This is the usual set up. But nothing prevents someone from adding a GM (general memory) shared between all users. Under this set up the LLM and harness fits and is virtually identical to how humans learn at a high level.

But this is besides the point because even if none of this was done. Just a context window or just training is in itself a form of learning. There was no action taken in your algebraic example where learning did not occur.

Re: AI is 'not smart' so what's next in artificial intelligence?

#72

Post by cindyllm »

card_zero wrote: post #60
SwellJoe wrote: post #23

Earlier quoted context omitted.

We're past the point where there's a feasible argument that there is an AI winter coming. The models work remarkably well for several classes of problem that seemed impossible a few years ago. They're not going away. There will still absolutely be a lot of ups and down and crazy stuff that happens in AI, but it won't be that AI almost completely stops being developed/funded for a decade or more. The biggest risk, I t…

They're not going away, in the same sense that Henry Winkler is still alive and working.

[dead]

Re: AI is 'not smart' so what's next in artificial intelligence?

#73

Post by dagss »

cauch wrote: post #70
dagss wrote: post #65

Earlier quoted context omitted.

Humans don't make the exact same errors of LLMs of course. Humans are very different beings. So you recognize that Claude is not a human. Humans make mistakes as well "inconsistent with the understanding mechanism", but they have a very different form, and you are so used to the particular failure mode of humans, that you don't think about it. But aliens visiting earth likely would find some aspects of human mind ver…

I find this kind of reasoning a bit pointless and unfalsifiable. Someone says "LLMs fail at this", and you say "but humans also sometimes fail", then they says "but we are not talking about the same thing", and you answer "this difference does not matter because aliens may be totally different". My point is that what we observe with LLMs does not require any understanding. And in some cases, it is clear the answer of…

I didn't really try to argue that LLMs "have understanding".

I am more, in a sense, arguing that "understanding" isn't clearly defined and sceptical about your confidence that this is an obvious quality of humans.

I'm not getting what this "understanding" thing is in humans that you are talking about. But I feel if anyone you are the one making the unfalsifiable statements here. You are the one talking about an inner quality within the reasoning that only humans possess and not LLMs.

If I re-read your post and replace the word "understanding" with "consciousness" then it makes a lot more sense to me. Yes, humans can be conscious that they understand something, while LLMs are very very probably not conscious of anything at all. If that is what you mean, I can easily agree with that. I would never argue LLMs are conscious.

But at least my original post had nothing to do with consciousness.

If I'm coding, I'd definitely pick the "understanding" of Fable over a junior engineer's "understanding" any day, for purely pragmatic reasons. When I say that, I simply mean that the rate of mistakes in junior humans is way higher than in best trained LLMs for most coding tasks.

I'm guessing this is not using the word "understanding" in a way you are happy with, and probably because you define the word "understanding" as being related to consciousness?

Re: AI is 'not smart' so what's next in artificial intelligence?

#74

Post by cauch »

dagss wrote: post #73
cauch wrote: post #70

Earlier quoted context omitted.

I find this kind of reasoning a bit pointless and unfalsifiable. Someone says "LLMs fail at this", and you say "but humans also sometimes fail", then they says "but we are not talking about the same thing", and you answer "this difference does not matter because aliens may be totally different". My point is that what we observe with LLMs does not require any understanding. And in some cases, it is clear the answer of…

I didn't really try to argue that LLMs "have understanding". I am more, in a sense, arguing that "understanding" isn't clearly defined and sceptical about your confidence that this is an obvious quality of humans. I'm not getting what this "understanding" thing is in humans that you are talking about. But I feel if anyone you are the one making the unfalsifiable statements here. You are the one talking about an inner…

> I am more, in a sense, arguing that "understanding" isn't clearly defined and sceptical about your confidence that this is an obvious quality of humans.

I did not do that, because it is not what I believe. I don't have any problems with the concept of having non-human being intelligent. It is just that LLMs are not that.

> I'm not getting what this "understanding" thing is in humans that you are talking about

Then that's fine. Other people have a better understanding of the notion. Just simply avoid the conversation if you don't know, it just feels like you are muddying it by not getting the concepts.

> If I re-read your post and replace the word "understanding" with "consciousness" ...

No, I'm not talking about "consciousness". I'm talking about "perceiving the underlying meaning or concept". LLMs don't create their answers by relying on the abstract concepts of the objects they are using, they just have meaningless rules linking the different objects, without grasping the abstract concepts explaining these links.

> I'd definitely pick the "understanding" of Fable over a junior engineer's "understanding" any day

Similarly, I trust better my pocket calculator than a human, but it does not mean that the calculator "understand math", it just has the "math rules" hardcoded without grasping the abstract concepts. In LLMs, the rules are not hardcoded, just extracted from the data, but the LLM doesn't understand any more than a pocket calculator understand math.

Re: AI is 'not smart' so what's next in artificial intelligence?

#75

Post by krackers »

yread wrote: post #66
dagss wrote: post #10

The article seems to define "smart" as being good at spatial awareness and navigating a body through 3D space and such. Thus, a mice is smarter than an LLM. That's the first time in my life I hear this definition. Until now, the word "smart" has meant doing exactly the things LLMs do, and mice don't. I guess it is a sign we are re-evaluating what makes humans special.

I still remember when "smart" meant knowing the number of Rs in strawberry

Was that ever solved? It seems that entire retort faded overnight, yet to my knowledge there was never any systematic analysis on cause or tokenizer change that fixed it. Maybe we just decided that this failure mode doesn't have any practical bearing given the existence of tool-use?

Re: AI is 'not smart' so what's next in artificial intelligence?

#76

Post by dagss »

cauch wrote: post #74
dagss wrote: post #73

Earlier quoted context omitted.

I didn't really try to argue that LLMs "have understanding". I am more, in a sense, arguing that "understanding" isn't clearly defined and sceptical about your confidence that this is an obvious quality of humans. I'm not getting what this "understanding" thing is in humans that you are talking about. But I feel if anyone you are the one making the unfalsifiable statements here. You are the one talking about an inner…

> I am more, in a sense, arguing that "understanding" isn't clearly defined and sceptical about your confidence that this is an obvious quality of humans. I did not do that, because it is not what I believe. I don't have any problems with the concept of having non-human being intelligent. It is just that LLMs are not that. > I'm not getting what this "understanding" thing is in humans that you are talking about Then…

Thank you that was clearer.

So, I have a PhD in Astrophysics so I am not a total stranger to doing some thinking. And I would say "create (...) answers by relying on the abstract concepts of the objects they are using" is a lofty goal for humans, something to aspire to more than something that typically goes on. We go by habits and intuition and allegories and quite muddy concepts most of the time. Concepts are malleable and evolve in clarity. And in creating new mathematics etc., intuition, inspiration, "flashes of insights" etc after absorbing oneself in the problem has an important role.

Are these things we have in our minds, whether concepts or habits or intuitions or flashes of insights, better or worse than whatever patterns could potentially be found in the LLM weights?

I struggle to label one of them "understanding" and the other not, at least without involving consciousness somehow.

Obviously you can define "understand" as "understand as a human would" but that is circular and uninteresting.

We just have to agree to find each others position incredible I am afraid :)

Re: AI is 'not smart' so what's next in artificial intelligence?

#77

Post by Wowfunhappy »

krackers wrote: post #75
yread wrote: post #66

Earlier quoted context omitted.

I still remember when "smart" meant knowing the number of Rs in strawberry

Was that ever solved? It seems that entire retort faded overnight, yet to my knowledge there was never any systematic analysis on cause or tokenizer change that fixed it. Maybe we just decided that this failure mode doesn't have any practical bearing given the existence of tool-use?

...I think it really is irrelevant, isn't it? The LLM gets words as tokens, not strings of letters. If you asked me how many of the letter s is in Mississippi, but said I'm not allowed to spell out the word in my head and count the letters, I don't think I could do it.

This isn't a great analogy, because part of the challenge would be preventing myself from picturing the spelling in my head. But my point is, the AI is not getting the words as letters. The correct solution is tool use.

Re: AI is 'not smart' so what's next in artificial intelligence?

#78

Post by cauch »

dagss wrote: post #76
cauch wrote: post #74

Earlier quoted context omitted.

> I am more, in a sense, arguing that "understanding" isn't clearly defined and sceptical about your confidence that this is an obvious quality of humans. I did not do that, because it is not what I believe. I don't have any problems with the concept of having non-human being intelligent. It is just that LLMs are not that. > I'm not getting what this "understanding" thing is in humans that you are talking about Then…

Thank you that was clearer. So, I have a PhD in Astrophysics so I am not a total stranger to doing some thinking. And I would say "create (...) answers by relying on the abstract concepts of the objects they are using" is a lofty goal for humans, something to aspire to more than something that typically goes on. We go by habits and intuition and allegories and quite muddy concepts most of the time. Concepts are malle…

> ... is a lofty goal for humans, ... We go by habits and intuition and allegories and quite muddy concepts most of the time

Those are already concepts. For LLMs, the word X is just an object linked to the words W, Y, Z, with no meaning to it. Habits, intuition and allegories are using objects to which we are attributing meaning.

Just to clarify, the links that LLMs create are complex, for example depend on all the surrounding other words, but they are still meaningless. If 2 totally different semantic sets of words happen to have exactly the same graphs of links, then you can swap the sets of word together, it does not matter for the LLM. To use a simplified example where you reduce a set to just 2 words, if "garden" and "pea" are linked the same way that "quantum" and "mechanic", then the relationship are the same for the LLM, without the LLM understanding that "garden pea" is a different concept than "quantum mechanic".

That's what I mean by "understanding": humans understand "garden pea" and "quantum mechanic" as concepts (even if they don't know biology or physics enough to even explain how they work), LLMs just use these objects as meaningless entities. All there is is a graph of links used to generate a sentence, but without knowing what the sentence means. A bit like if someone was giving you all the words of a language you don't know and the exact rules of how to build an answer given an input, but that you don't know what each word means.

Of course, the relationship learnt by the LLMs are very complex, allowing big changes based on the surrounding other 100'000 words. But learning this relationship is still more straightforward than to leap into a conceptual world model (especially because there is nothing to guide the LLM. If "garden pea" and "quantum mechanic" have the same graph geometry, then the world model where "garden pea" is an abstract field of study and "quantum mechanic" is a material object is as probable than the opposite).

Re: AI is 'not smart' so what's next in artificial intelligence?

#80

Post by krackers »

Wowfunhappy wrote: post #77
krackers wrote: post #75

Earlier quoted context omitted.

Was that ever solved? It seems that entire retort faded overnight, yet to my knowledge there was never any systematic analysis on cause or tokenizer change that fixed it. Maybe we just decided that this failure mode doesn't have any practical bearing given the existence of tool-use?

...I think it really is irrelevant, isn't it? The LLM gets words as tokens, not strings of letters. If you asked me how many of the letter s is in Mississippi, but said I'm not allowed to spell out the word in my head and count the letters, I don't think I could do it. This isn't a great analogy, because part of the challenge would be preventing myself from picturing the spelling in my head. But my point is, the AI i…

LLMs can learn to do arithmetic (without tool use), and they can learn a mapping from tokens to the letter counts contained therein (you could imagine trivially training on synthetic data). So there doesn't seem to be any fundamental barrier.
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