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>Any number of systems might deliver the empirical result you measured Like what ? What exactly would give similar empirical results over the wide number of t

>Any number of systems might deliver the empirical result you measured Like what ? What exactly would give similar empirical results over the wide number of tests LLMs have been subjected to ? >and many of them would involve none of that. Oh? How would you know that? Did I miss the breakthrough Intellisense-o-meter that can measure the intelligence flowing through a system ? I guess I'm just not sure what point you're trying to make here. Empirically assessing the result after the fact is how we determine intelligence and reasoning in.. anything humans included. How do you determine a piece of metal is real gold ? By comparing the results of a series of tests against the properties of gold you have outlined. The metal is a black box. You don't need to understand every interaction occuring in your tests to determine whether it is gold or not.

swatcoder 2y ago
> >Any number of systems might deliver the empirical result you measured > Like what ? What exactly would give similar empirical results over the wide number of tests... The GP gave a single trivial example and my reply was highlighting how that example didn't inform the question at hand in any way. That example might be just as well be exhibited by a lookup table, a lucky random output, a modified markov chain, a Chinese Box, a trivial small language model trained on the right corpus, etc. That certain LLM's or chatbots might also be able to deliver on more sophisticated examples that those systems cannot is not what they or I were talking about here. It was a discussion about obviousness from trivial samples, and about the deeper semantic dependencies hidden the GP's definition. Such trivial samples don't hold up to scrutiny as their definition recurses down through concepts that are not at all demonstrated in these trivial cases. Their attempt at rhetoric just fails. > Empirically assessing the result after the fact is how we determine intelligence and reasoning in.. anything humans included. No. We project intelligence onto humans inductively by identifying our own experience as intelligence and assuming that other things that are almost identical to us are very likely to be working in the same way. In recent decades, there's been growing acceptance that other systems approximately like us (animals of certain kinds) exhibit it to various degrees as well, but even this itself was a formally rejected concept during the early 20th century when "intelligence" first became treated as something measurable and quantifiable at all. The concept of intelligence is a wholly cultural one and its definition and applicability moves around over time. Yet there are currently very few people who would apply the word to a lookup table, a random output, a Chinese Room, a modified markov chain, etc and a smattering-but-growing number of people who are comfortable applying it to LLM's and chatbots as we see them today. As this happens and its use expands, the sense of the word changes, as it has been doing for hundreds of years. At this point, we mostly can't yet rely on chatbots to fulfill roles that require interesting human intelligence. They can pass some benchmark tests to greater or less degrees, but also happen to be excellent benchmark optimizers (that's the essence of their design), so it remains hard to know what that really means. If and when they become reliable substitutes for human intelligence in general tasks, or become interestingly independent in the way we see certain animals, the prior-yet-modern senses of intelligence will be easier to apply. But we're not there yet.
- famouswaffles 2y ago
  >That example might be just as well be exhibited by a lookup table, a lucky random output, a modified markov chain, a Chinese Box, a trivial small language model trained on the right corpus, etc. Basically No-one who argues LLMs are intelligent does so from the results of a single query. That is simply the example he used to demonstrate what he believes is an instance of reasoning. And If i said, show me the lookup table or random string generator or simple markov chain etc that would reply correctly to any question like that, would you be able to do so ? No. because you're hinging on random chance being your savior. If there's one property of Intelligence everybody can agree on, it's that it works better than chance. Small tangent but the Chinese room is a nonsensical thought experiment. Can you demonstrate which neuron/synapse/cell/atom etc "understands" English. No? then your brain is a "Chinese Room" >No. We project intelligence onto humans inductively by identifying our own experience as intelligence and assuming that other things that are almost identical to us are very likely to be working in the same way. Really? History would certainly seem to argue otherwise. Wonder why all those African slaves and Jews were missing this projection. Seems to me there isn't necessarily any logic to what properties we project on others. Leaving that aside. That's not what i was getting at. Why are we tested in schools? Why do IQ tests still exist today? Because we attempt to measure reasoning, intelligence and understanding through tests. The fact of the matter is that this is how we assess intelligence today. And I'm not sure why you brought up what people centuries or decades ago thought of intelligence but for as long as intelligence has been something to gatekeep (a very very long time), tests have been used to assess it even if the form and shape of these tests have changed over thousands of years. >At this point, we mostly can't yet rely on chatbots to fulfill roles that require interesting human intelligence. So? I'm not arguing about whether LLMs are Humans. How many animals can fulfill roles requiring "human intelligence" never mind "interesting" human intelligence (lol at the goalposts. I suppose when that bar is cleared, we'll move on to "very interesting" human intelligence and restart this conversation).
NateEag 2y ago
> Empirically assessing the result after the fact is how we determine intelligence and reasoning in.. anything humans included. It isn't, though. At least not exclusively, I'd argue not even primarily. We look instead at how someone describes their thought process to see if it seems reasonable, whether they're using logically-valid reasoning forms, and whether their arguments bback up their claims. It's common to say that someone's _reasoning_ is sound but their _conclusion_ is incorrect, due to <subtle observation they missed> or <invalid premise>. This is why math teachers always tell students to show their work, and give out 0s for correct answers with no steps.
- famouswaffles 2y ago
  All of that is simply part of the "result" here though. Result in this discussion is the output of the black box, whether that's a machine or a human brain. I don't mean it in the "final answer" sense. For example, all the conclusions the math teacher made are still ultimately from assessing the "result" of the student only.

swatcoder 2y ago

> >Any number of systems might deliver the empirical result you measured > Like what ? What exactly would give similar empirical results over the wide number of tests... The GP gave a single trivial example and my reply was highlighting how that example didn't inform the question at hand in any way. That example might be just as well be exhibited by a lookup table, a lucky random output, a modified markov chain, a Chinese Box, a trivial small language model trained on the right corpus, etc. That certain LLM's or chatbots might also be able to deliver on more sophisticated examples that those systems cannot is not what they or I were talking about here. It was a discussion about obviousness from trivial samples, and about the deeper semantic dependencies hidden the GP's definition. Such trivial samples don't hold up to scrutiny as their definition recurses down through concepts that are not at all demonstrated in these trivial cases. Their attempt at rhetoric just fails. > Empirically assessing the result after the fact is how we determine intelligence and reasoning in.. anything humans included. No. We project intelligence onto humans inductively by identifying our own experience as intelligence and assuming that other things that are almost identical to us are very likely to be working in the same way. In recent decades, there's been growing acceptance that other systems approximately like us (animals of certain kinds) exhibit it to various degrees as well, but even this itself was a formally rejected concept during the early 20th century when "intelligence" first became treated as something measurable and quantifiable at all. The concept of intelligence is a wholly cultural one and its definition and applicability moves around over time. Yet there are currently very few people who would apply the word to a lookup table, a random output, a Chinese Room, a modified markov chain, etc and a smattering-but-growing number of people who are comfortable applying it to LLM's and chatbots as we see them today. As this happens and its use expands, the sense of the word changes, as it has been doing for hundreds of years. At this point, we mostly can't yet rely on chatbots to fulfill roles that require interesting human intelligence. They can pass some benchmark tests to greater or less degrees, but also happen to be excellent benchmark optimizers (that's the essence of their design), so it remains hard to know what that really means. If and when they become reliable substitutes for human intelligence in general tasks, or become interestingly independent in the way we see certain animals, the prior-yet-modern senses of intelligence will be easier to apply. But we're not there yet.

famouswaffles 2y ago
>That example might be just as well be exhibited by a lookup table, a lucky random output, a modified markov chain, a Chinese Box, a trivial small language model trained on the right corpus, etc. Basically No-one who argues LLMs are intelligent does so from the results of a single query. That is simply the example he used to demonstrate what he believes is an instance of reasoning. And If i said, show me the lookup table or random string generator or simple markov chain etc that would reply correctly to any question like that, would you be able to do so ? No. because you're hinging on random chance being your savior. If there's one property of Intelligence everybody can agree on, it's that it works better than chance. Small tangent but the Chinese room is a nonsensical thought experiment. Can you demonstrate which neuron/synapse/cell/atom etc "understands" English. No? then your brain is a "Chinese Room" >No. We project intelligence onto humans inductively by identifying our own experience as intelligence and assuming that other things that are almost identical to us are very likely to be working in the same way. Really? History would certainly seem to argue otherwise. Wonder why all those African slaves and Jews were missing this projection. Seems to me there isn't necessarily any logic to what properties we project on others. Leaving that aside. That's not what i was getting at. Why are we tested in schools? Why do IQ tests still exist today? Because we attempt to measure reasoning, intelligence and understanding through tests. The fact of the matter is that this is how we assess intelligence today. And I'm not sure why you brought up what people centuries or decades ago thought of intelligence but for as long as intelligence has been something to gatekeep (a very very long time), tests have been used to assess it even if the form and shape of these tests have changed over thousands of years. >At this point, we mostly can't yet rely on chatbots to fulfill roles that require interesting human intelligence. So? I'm not arguing about whether LLMs are Humans. How many animals can fulfill roles requiring "human intelligence" never mind "interesting" human intelligence (lol at the goalposts. I suppose when that bar is cleared, we'll move on to "very interesting" human intelligence and restart this conversation).

NateEag 2y ago

> Empirically assessing the result after the fact is how we determine intelligence and reasoning in.. anything humans included. It isn't, though. At least not exclusively, I'd argue not even primarily. We look instead at how someone describes their thought process to see if it seems reasonable, whether they're using logically-valid reasoning forms, and whether their arguments bback up their claims. It's common to say that someone's _reasoning_ is sound but their _conclusion_ is incorrect, due to <subtle observation they missed> or <invalid premise>. This is why math teachers always tell students to show their work, and give out 0s for correct answers with no steps.

famouswaffles 2y ago
All of that is simply part of the "result" here though. Result in this discussion is the output of the black box, whether that's a machine or a human brain. I don't mean it in the "final answer" sense. For example, all the conclusions the math teacher made are still ultimately from assessing the "result" of the student only.