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And yet It Understands

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Re: And yet It Understands

#121

Post by branko_d »

glenstein wrote: post #88
zetalyrae wrote: post #38

Earlier quoted context omitted.

I don't see the relevance. Natural intelligence has not been understood because if our brains were simple enough that we could understand them, we would be so simple we couldn't. This explains why it has not been reproduced. >There is no repeatable experiment going from inorganic matter to self-aware, self-replicating life. You can do the RNA world experiments in a lab, it would just take a lot of time and a lot of p…

>Natural intelligence has not been understood because if our brains were simple enough that we could understand them, we would be so simple we couldn't. This explains why it has not been reproduced I don't believe that it works this way, for two reasons. One, the logic would seem to work the other way as well, if our brains are so sophisticated that they make natural intelligence possible, then we should be so intell…

> if our brains are so sophisticated that they make natural intelligence possible, then we should be so intelligent that we would have the means to understand them

It may well be that building a brain is easier than understanding it.

Re: And yet It Understands

#122

Post by fwlr »

fwlr wrote: post #120

For me, the strongest argument in this article is “There is a point where it understands is the most parsimonious explanation, and we have clearly passed it”. Those who deny that ChatGPT understands have to move their goalposts every few weeks; OpenAI’s release schedule seems to be slightly faster, so in time it seems even the fastest-moving goalposts will be outrun by the LLMs. One specific flavor of “ChatGPT doesn’…

It occurred to me after writing that post that understanding is just what the algorithm feels like from the inside.

A human understands English instructions in a way that lets them apply those instructions to Chinese language tasks with the same meaning. We might ask, what is this in the physical structure of the human brain? What’s the specific arrangement of neurons and neuronal connections that is doing this? Assume neuroscience has the answer and can give you a picture of the neurons in question and detail their activation pattern. When we use understanding to do our language task, we don’t actually feel our neurons lighting up, we don’t feel an activation pattern rush through our brain. It just feels like we understand, because that’s what the algorithm feels like from the inside. https://www.lesswrong.com/posts/yA4gF5KrboK2m2Xu7/how-an-alg...

Re: And yet It Understands

#123

Post by famouswaffles »

civilized wrote: post #119
famouswaffles wrote: post #111

Earlier quoted context omitted.

Humans learn language and concepts through sentences, and in most cases semantic understanding can be built up just fine this way. It doesn't work quite the same way for math. When I look at the numbers in the example, I have no idea if they are prime or factors because they themselves don't have much semantic content. In order to understand whether they are those things or not actually requires to stop and perform s…

The issue I'm pointing to here doesn't have anything to do with deep understanding of primes built over years of education etc etc. All I'm saying is that ChatGPT doesn't know that 2^2 = 4 means 2^2 * a = 4 * a for any a. ChatGPT is often good at understanding patterns involving the substitution of one string for another. So you might hope that it could do well in a case like this. But it doesn't really. It is aware…

The point I'm making is that chatGPT doesn't know that because the model it has of arithmetic is faulty. It's really as simple as that.

The primes thing was just an illustrative example.

You want it to do large scale arithmetic with high accuracy? Describe arithmetic as an algorithm to be performed on two numbers. https://arxiv.org/abs/2211.09066

It's not about chatGPT not understanding anything. It's about chatGPT not understanding math very well. That bleeds into understanding of related concepts as well. LLMs build all these models of the world from the text they train on. Well not all if it is accurate.

Re: And yet It Understands

#124

Post by smitty1e »

branko_d wrote: post #121
glenstein wrote: post #88

Earlier quoted context omitted.

>Natural intelligence has not been understood because if our brains were simple enough that we could understand them, we would be so simple we couldn't. This explains why it has not been reproduced I don't believe that it works this way, for two reasons. One, the logic would seem to work the other way as well, if our brains are so sophisticated that they make natural intelligence possible, then we should be so intell…

> if our brains are so sophisticated that they make natural intelligence possible, then we should be so intelligent that we would have the means to understand them It may well be that building a brain is easier than understanding it.

If one has not understood the brain, then how would one be certain that such has been built?

Re: And yet It Understands

#125

Post by im3w1l »

espadrine wrote: post #85
the_gipsy wrote: post #69

Earlier quoted context omitted.

Maybe it is human like intelligence already. Maybe our internal monologue is just a better trained and refined ChatGPT. And maybe that is all the magic that is necessary for this holy grail of consciousness, there is no quantum brain, no nothing. Just a stream of the next word that says that we are there, therefore we are. That is what scares me.

> Maybe it is human like intelligence already. It objectively is not. First, intelligence (human or otherwise) is typically defined as the sum of value functions of a given policy across all states, divided by an exponential of the complexity of the environment[0] (page 23). The GPT-4 technical report[1] specifically points out that it is unable to make money when given an initial amount and AWS access (appendix H §…

That isn't true at all. Maybe some narrow field defines it in that way but people in general do not. Traditionally intelligence has been fuzzily defined as that mental thing which humans have that other things do not.

If you go back in time you will see that people have associated it with both our ability to breath and later the beating of the heart. We have looked at animals and said we can count and they cannot that is the nature of intelligence. We told ourselves that we have a complex language and they do not and that is the nature of intelligence. We have noticed that we use tools and they do not and that is the nature of intelligence. We have seen that we can play chess and they cannot and that is the nature of intelligence.

Now with the advent of computers they have increasingly forced us to reconsider these things. Computers can play chess better than us so that is not intelligence. They are as verbal as us so that is not intelligence.

Humorously, because of this reevaluation and redrawing of the boundaries we now seem to feel more of a kinship with animals.

But anyway, intelligence is clearly a complex mixture of many things, and crucially those aspects must be integrated and be able to feed into and support each other.

Re: And yet It Understands

#126

Post by _dain_ »

ivanbakel wrote: post #114
_dain_ wrote: post #110

Earlier quoted context omitted.

No, you're the one who's begging the question. Why can't a "purely statistical" process have an understanding? If you a priori assume it can't, then nothing could ever persuade you GPT understood anything, no matter how it performed. And again, this magical word "just". "Just highly correlated", "just probabilities". Putting the word "just" in front of something doesn't mean you've explained it.

>No, you're the one who's begging the question. Why can't a "purely statistical" process have an understanding? This is a related, but fundamentally different thing to the point I replied to in your original comment. You asked: > I don't see how it can [apply training across languages] unless it really has some kind of understanding. I provided a potential explanation that is in line with how we think GPT works, and…

What would convince you? Give an example of something that would show beyond a shadow of a doubt that it understands.

Re: And yet It Understands

#127

Post by _xnmw »

I still hold that it doesn't "understand". Even if it answered all questions perfectly, stopped making mistakes, and produced fully working programs better than the best crack developer teams, that still doesn't mean it "understands". "Understanding" is not an output, it's a process, that is sometimes (but not always) measured by its output.

Re: And yet It Understands

#128

Post by im3w1l »

glenstein wrote: post #65
raincole wrote: post #42

Earlier quoted context omitted.

I don't know. I've been using Copilot, ChatGPT, and Bing Chat intensively in the past month. So far I still think the metaphor "you can’t get to the Moon by piling up chairs" aged very well. > A criticism that would make more sense would be something along the lines of "piling up colors you won't get you any closer to the Moon", since colors aren't even the right kind of thing, and you can't aggregate them in a way t…

>means that even chairs and rockets share some attributes (helping you get higher), the difference between them is still qualitative, not quantitve. I don't think so, because the needed 'quality' is the ability to traverse space. So I don't think I agree that the qualitative piece is missing. Perhaps the moon example is helpful here because the real solution, a rocket ship, uses propulsion rather than sheer mass, and…

The quote isn't talking about physical distance. It's talking about "close" in the sense of progress. You haven't made any progress towards walking on the moon even if the pile of chairs is as big as Mount Everest. There isn't just the question of toppling either, the chairs would start physically crushing each other and then they are no longer chairs.

Re: And yet It Understands

#129

Post by _dain_ »

_xnmw wrote: post #127

I still hold that it doesn't "understand". Even if it answered all questions perfectly, stopped making mistakes, and produced fully working programs better than the best crack developer teams, that still doesn't mean it "understands". "Understanding" is not an output, it's a process, that is sometimes (but not always) measured by its output.

By that standard, how do you know another human being understands anything? All you see is their behaviour. You don't have access to their internals, you don't really know what "process" is going on in there. This road leads to solipsism.

Re: And yet It Understands

#130

Post by ilaksh »

glenstein wrote: post #71
MrScruff wrote: post #37

This article lines up well with my feelings on the matter. In general, people seem to understate the emergent behaviours of ML models, while overstating the uniqueness of human intelligence. I think a lot of this is down to the fact that although both systems exhibit a form of intelligence, they’re very different. LLMs deliver mastery of natural language that would normally be a signal for a highly intelligent human.…

>LLMs deliver mastery of natural language that would normally be a signal for a highly intelligent human. While in other ways they’re less intelligent than a cat. Just as an example to illustrate your point, yesterday saw a Twitter meme that had multiple overlapping Venn diagrams, where Chicago was not only in a Venn diagram for a type of deep dish pizza, but is also a city, and is also a play, and also a format for…

Did you try asking GPT-4? It has a significantly higher IQ.
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