9 ms·

My initial impression: it's very impressive and very exciting. My skeptical impression: it's complete hubris to conflate ARC or any benchmark with truly genera

My initial impression: it's very impressive and very exciting. My skeptical impression: it's complete hubris to conflate ARC or any benchmark with truly general intelligence. I know my skepticism here is identical to moving goalposts. More and more I am shifting my personal understanding of general intelligence as a phenomenon we will only ever be able to identify with the benefit of substantial retrospect. As it is with any sufficiently complex program, if you could discern the result beforehand, you wouldn't have had to execute the program in the first place. I'm not trying to be a downer on the 12th day of Christmas. Perhaps because my first instinct is childlike excitement, I'm trying to temper it with a little reason.

amarcheschi 2y ago
I just googled arc agi questions, and it looks like it is similar to an iq test with raven matrix. Similar as in you have some examples of images before and after, then an image before and you have to guess the after. Could anyone confirm if this is the only kind of questions in the benchmark? If yes, how come there is such a direct connection to "oh this performs better than humans" when llm can be quite better than us in understanding and forecasting patterns? I'm just curious, not trying to stir up controversies
- zebomon 2y ago
  It's a test on which (apparently until now) the vast majority of humans have far outperformed all machine systems.
  - patrickhogan1 2y ago
    But it’s not a test that directly shows general intelligence. I am excited no less! This is huge improvement. How does this do on SWE Bench?
    - famouswaffles 2y ago
      >How does this do on SWE Bench? 71.7%
      - throwaway0123_5 2y ago
        I've seen this figure on a few tech news websites and reddit but can't find an official source. If it was in the video I must have missed it, where is this coming from?
        famouswaffles 2y ago
        It was in the video. I don't know if Open ai have a page up yet
- ALittleLight 2y ago
  Yes, it's pretty similar to Raven's. The reason it is an interesting benchmark is because humans, even very young humans, "get" the test in the sense of understanding what it's asking and being able to do pretty well on it - but LLMs have really struggled with the benchmark in the past. Chollett (one of the creators of the ARC benchmark) has been saying it proves LLMs can't reason. The test questions are supposed to be unique and not in the model's training set. The fact that LLMs struggled with the ARC challenge suggested (to Chollett and others) that models weren't "Truly reasoning" but rather just completing based on things they'd seen before - when the models were confronted with things they hadn't seen before, the novel visual patterns, they really struggled.
- Eridrus 2y ago
  ML is quite good at understanding and forecasting patterns when you train on the data you want to forecast. LLMs manage to do so much because we just decided to train on everything on the internet and hope that it included everything we ever wanted to know. This tries to create patterns that are intentionally not in the data and see if a system can generalize to them, which o3 super impressively does!
  - yunwal 2y ago
    ARC is in the dataset though? I mean I'm aware that there are new puzzles every day, but there's still a very specific format and set of skills required to solve it. I'd bet a decent amount of money that humans get better at ARC with practice, so it seems strange to suggest that AI wouldn't.
hansonkd 2y ago
It doesn't need to be general intelligence or perfectly map to human intelligence. All it needs to be is useful. Reading constant comments about LLMs can't be general intelligence or lack reasoning etc, to me seems like people witnessing the airplane and complaining that it isn't "real flying" because it isn't a bird flapping its wings (a large portion of the population held that point of view back then). It doesn't need to be general intelligence for the rapid advancement of LLM capabilities to be the most societal shifting development in the past decades.
- zebomon 2y ago
  I agree. If the LLMs we have today never got any smarter, the world would still be transformed over the next ten years.
- AyyEye 2y ago
  > Reading constant comments about LLMs can't be general intelligence or lack reasoning etc, to me seems like people witnessing the airplane and complaining that it isn't "real flying" because it isn't a bird flapping its wings (a large portion of the population held that point of view back then). That is a natural reaction to the incessant techbro, AIbro, marketing, and corporate lies that "AI" (or worse AGI) is a real thing, and can be directly compared to real humans. There are people on this very thread saying it's better at reasoning than real humans (LOL) because it scored higher on some benchmark than humans... Yet this technology still can't reliably determine what number is circled, if two lines intersect, or count the letters in a word. (That said behaviour may have been somewhat finetuned out of newer models only reinforces the fact that the technology inherently not capable of understanding anything.)
  - IanCal 2y ago
    I encounter "spicy auto complete" style comments far more often than techbro AI-everything comments and its frankly getting boring. I've been doing AI things for about 20+ years and llms are wild. We've gone from specialized things being pretty bad as those jobs to general purpose things better at that and everything else. The idea you could make and API call with "is this sarcasm?" and get a better than chance guess is incredible.
sigmoid10 2y ago
These comments are getting ridiculous. I remember when this test was first discussed here on HN and everyone agreed that it clearly proves current AI models are not "intelligent" (whatever that means). And people tried to talk me down when I theorised this test will get nuked soon - like all the ones before. It's time people woke up and realised that the old age of AI is over. This new kind is here to stay and it will take over the world. And you better guess it'll be sooner rather than later and start to prepare.
- samvher 2y ago
  What kind of preparation are you suggesting?
  - sigmoid10 2y ago
    This is far too broad to summarise here. You can read up on Sutskever or Bostrom or hell even Steven Hawking's ideas (going in order from really deep to general topics). We need to discuss everything - from education over jobs and taxes all the way to the principles of politics, our economy and even the military. If we fail at this as a society, we will at the very least create a world where the people who own capital today massively benefit and become rich beyond imagination (despite having contributed nothing to it), while the majority of the population will be unemployable and forever left behind. And the worst case probably falls somewhere between the end of human civilisation and the end of our species.
    - kelseyfrog 2y ago
      What we're going to do is punt the questions and then convince ourselves the outcome was inevitable and if anything it's actually our fault.
    - astrange 2y ago
      One way you can tell this isn't realistic is that it's the plot of Atlas Shrugged. If your economic intuitions produce that book it means they are wrong. > while the majority of the population will be unemployable and forever left behind Productivity improvements increase employment. A superhuman AI is a productivity improvement.
FrustratedMonky 2y ago
" it's complete hubris to conflate ARC or any benchmark with truly general intelligence." Maybe it would help to include some human results in the AI ranking. I think we'd find that Humans score lower?
- zamadatix 2y ago
  I'm not sure it'd help what they are talking about much. E.g. go back in time and imagine you didn't know there are ways for computers to be really good at performing integration yet as nobody had tried to make them. If someone asked you how to tell if something is intelligent "the ability to easily reason integrations or calculate extremely large multiplications in mathematics" might seem like a great test to make. Skip forward to the modern era and it's blatantly obvious CASes like Mathematica on a modern computer range between "ridiculously better than the average person" to "impossibly better than the best person" depending on the test. At the same time, it becomes painfully obvious a CAS is wholly unrelated to general intelligence and just because your test might have been solvable by an AGI doesn't mean solving it proves something must have been an AGI. So you come up with a new test... but you have the same problem as originally, it seems like anything non-human completely bombs and an AGI would do well... but how do you know the thing that solves it will have been an AGI for sure and not just another system clearly unrelated? Short of a more clever way what GP is saying is the goalposts must keep being moved until it's not so obvious the thing isn't AGI, not that the average human gets a certain score which is worse. . All that aside, to answer your original question, in the presentation it was said the average human gets 85% and this was the first model to beat that. It was also said a second version is being worked on. They have some papers on their site about clear examples of why the current test clearly has a lot of testing unrelated to whether something is really AGI (a brute force method was shown to get >50% in 2020) so their aim is to create a new goalpost test and see how things shake out this time.
  - FrustratedMonky 2y ago
    "Short of a more clever way what GP is saying is the goalposts must keep being moved until it's not so obvious the thing isn't AGI, not that the average human gets a certain score which is worse." Best way of stating that I've heard. The Goal Post must keep moving, until we understand enough what is happening. I usually poo-poo the goal post moving, but this makes sense.
m3kw9 2y ago
From the statement where - this is a pretty tough test where AI scores low vs humans just last year, and AI can do it as good as humans may not be AGI which I agree, but it means something with all caps
- manmal 2y ago
  Obviously, the multi billion dollar companies will try to satisfy the benchmarks they are not yet good in, as has always been the case.
  - m3kw9 2y ago
    A valid conspiracy theory but I’ve heard that one everystep of the way to this point
    - manmal 2y ago
      What made you write this comment, I have a hard time understanding your point.
wslh 2y ago
> My skeptical impression: it's complete hubris to conflate ARC or any benchmark with truly general intelligence. But isn’t it interesting to have several benchmarks? Even if it’s not about passing the Turing test, benchmarks serve a purpose—similar to how we measure microprocessors or other devices. Intelligence may be more elusive, but even if we had an oracle delivering the ultimate intelligence benchmark, we'd still argue about its limitations. Perhaps we'd claim it doesn't measure creativity well, and we'd find ourselves revisiting the same debates about different kinds of intelligences.
- zebomon 2y ago
  It's certainly interesting. I'm just not convinced it's a test of general intelligence, and I don't think we'll know whether or not it is until it's been able to operate in the real world to the same degree that our general intelligence does.
kelseyfrog 2y ago
> truly general intelligence Indistinguishable from goalpost moving like you said, but also no true Scotsman. I'm curious what would happen in your eyes if we misattributed general intelligence to an AI model? What are the consequences of a false positive and how would they affect your life? It's really clear to me how intelligence fits into our reality as part of our social ontology. The attributes and their expression that each of us uses to ground our concept of the intelligent predicate differs wildly. My personal theory is that we tend to have an exemplar-based dataset of intelligence, and each of us attempts to construct a parsimonious model of intelligence, but like all (mental) models, they can be useful but wrong. These models operate in a space where the trade off is completeness or consistency, and most folks, uncomfortable saying "I don't know" lean toward being complete in their specification rather than consistent. The unfortunate side-effect is that we're able to easily generate test data that highlights our model inconsistency - AI being a case in point.
- PaulDavisThe1st 2y ago
  > I'm curious what would happen in your eyes if we misattributed general intelligence to an AI model? What are the consequences of a false positive and how would they affect your life? Rich people will think they can use the AI model instead of paying other people to do certain tasks. The consequences could range from brilliant to utterly catastrophic, depending on the context and precise way in which this is done. But I'd lean toward the catastrophic.
  - kelseyfrog 2y ago
    Any specifics? It's difficult to separate this from generalized concern.
    - PaulDavisThe1st 2y ago
      someone wants a "personal assistant" and believes that the LLM has AGI ... someone wants a "planning officer" and believes that the LLM has AGI ... someone wants a "hiring consultant" and believes that the LLM has AGI ... etc. etc.
Agentus 2y ago
how about a extra large dose of your skepticism. is true intelligence really a thing and not just a vague human construct that tries to point out the mysterious unquantifiable combination of human behaviors? humans clearly dont know what intelligence is unambiguously. theres also no divinely ordained objective dictionary that one can point at to reference what true intelligence is. a deep reflection of trying to pattern associate different human cognitive abilities indicates human cognitive capabilities arent that spectacular really.
- MVissers 2y ago
  My guess as an amateur neuroscientist is that what we call intelligence is just a 'measurement' of problem solving ability in different domains. Can be emotional, spatial, motor, reasoning, etc etc. There is no special sauce in our brain. And we know how much compute there is in our brain– So we can roughly estimate when we'll hit that with these 'LLMs'. Language is important in a human brain development as well. Kids who grow up deaf grow up vastly less intelligent unless they learn sign language. Language allow us to process complex concepts that our brain can learn to solve, without having to be in those complex environments. So in hindsight, it's easy to see why it took a language model to be able to solve general tasks and other types deep learning networks couldn't. I don't really see any limits on these models.
  - Agentus 2y ago
    interesting point about language. but i wonder if people misattribute the reason why language is pivotal to human development. your points are valid. i see human behavior with regard to learning as 90% mimicry and 10% autonomous learning. most of what humans believe in is taken on faith and passed on from the tribe to the individual. rarely is it verified even partially let alone fully. humans simple dont have the time or processing power to do that. learning a thing without outside aid is vastly slower and more energy or brain intensive process than copy learning or learning through social institutions by dissemination. the stunted development from lack of language might come more from the less ability to access the collective learning process that language enables and or greatly enhances. i think a lot of learning even when combined with reasoning, deduction, etc really is at the mercy of brute force exploration to find a solution, which individuals are bad at but a society that collects random experienced “ah hah!” occurrences and passes them along is actually okay at. i wonder if llms and language dont as so much allow us to process these complex environments but instead preload our brains to get a head start in processing those complex environments once we arrive in them. i think llms store compressed relationships of the world which obviously has information loss from a neural mapping of the world that isnt just language based. but that compressed relationships ie knowledge doesnt exactly backwardly map onto the world without it having a reverse key. like artificially learning about real world stuff in school abstractly and then going into the real world, it takes time for that abstraction to snap fit upon the real world. could you further elaborate on what you mean by limits, because im happy to play contrarian on what i think i interpret you to be saying there. also to your main point: what intelligence is. yeah you sort of hit up my thoughts on intelligence. its a combination of problem solving abilities in different domains. its like an amalgam of cognitive processes that achieve an amalgam of capabilities. while we can label alllllll that with a singular word, doesnt mean its all a singular process. seems like its a composite. moreover i think a big chunk of intelligence (but not all) is just brute forcing finding associations and then encoding those by some reflexive search/retrieval. a different part of intelligence of course is adaptibility and pattern finding.
Bjorkbat 2y ago
I think it's still an interesting way to measure general intellience, it's just that o3 has demonstrated that you can actually achieve human performance on it by training it on the public training set and giving it ridiculous amounts of compute, which I imagine equates to ludicrously long chains-of-thought, and if I understand correctly more than one chain-of-thought per task (they mention sample sizes in the blog post, with o3-low using 6 and o3-high using 1024. Not sure if these are chains-of-thought per task or what). Once you look at it that way it the approach really doesn't look like intelligence that's able to generalize to novel domains. It doesn't pass the sniff test. It looks a lot more like brute-forcing. Which is probably why, in order to actually qualify for the leaderboard, they stipulate that you can't use more than $10k more of compute. Otherwise, it just sounds like brute-forcing.
- BriggyDwiggs42 2y ago
  I disagree. It’s vastly inefficient, but it is managing to actually solve these problems with a vast search space. If we extrapolate this approach into the future and assume that the search becomes better as the underlying model improves, and assume that the architecture grows more efficient, and assume that the type of parallel computing used here grows cheaper, isn’t it possible that this is a lot more than brute-forcing in terms of what it will achieve? In other words, is it maybe just a really ugly way of doing something functionally equivalent to reasoning?
deleted 2y ago
[deleted]

amarcheschi 2y ago

I just googled arc agi questions, and it looks like it is similar to an iq test with raven matrix. Similar as in you have some examples of images before and after, then an image before and you have to guess the after. Could anyone confirm if this is the only kind of questions in the benchmark? If yes, how come there is such a direct connection to "oh this performs better than humans" when llm can be quite better than us in understanding and forecasting patterns? I'm just curious, not trying to stir up controversies

zebomon 2y ago
It's a test on which (apparently until now) the vast majority of humans have far outperformed all machine systems.
- patrickhogan1 2y ago
  But it’s not a test that directly shows general intelligence. I am excited no less! This is huge improvement. How does this do on SWE Bench?
  - famouswaffles 2y ago
    >How does this do on SWE Bench? 71.7%
    - throwaway0123_5 2y ago
      I've seen this figure on a few tech news websites and reddit but can't find an official source. If it was in the video I must have missed it, where is this coming from?
      - famouswaffles 2y ago
        It was in the video. I don't know if Open ai have a page up yet
ALittleLight 2y ago
Yes, it's pretty similar to Raven's. The reason it is an interesting benchmark is because humans, even very young humans, "get" the test in the sense of understanding what it's asking and being able to do pretty well on it - but LLMs have really struggled with the benchmark in the past. Chollett (one of the creators of the ARC benchmark) has been saying it proves LLMs can't reason. The test questions are supposed to be unique and not in the model's training set. The fact that LLMs struggled with the ARC challenge suggested (to Chollett and others) that models weren't "Truly reasoning" but rather just completing based on things they'd seen before - when the models were confronted with things they hadn't seen before, the novel visual patterns, they really struggled.
Eridrus 2y ago
ML is quite good at understanding and forecasting patterns when you train on the data you want to forecast. LLMs manage to do so much because we just decided to train on everything on the internet and hope that it included everything we ever wanted to know. This tries to create patterns that are intentionally not in the data and see if a system can generalize to them, which o3 super impressively does!
- yunwal 2y ago
  ARC is in the dataset though? I mean I'm aware that there are new puzzles every day, but there's still a very specific format and set of skills required to solve it. I'd bet a decent amount of money that humans get better at ARC with practice, so it seems strange to suggest that AI wouldn't.

hansonkd 2y ago

It doesn't need to be general intelligence or perfectly map to human intelligence. All it needs to be is useful. Reading constant comments about LLMs can't be general intelligence or lack reasoning etc, to me seems like people witnessing the airplane and complaining that it isn't "real flying" because it isn't a bird flapping its wings (a large portion of the population held that point of view back then). It doesn't need to be general intelligence for the rapid advancement of LLM capabilities to be the most societal shifting development in the past decades.

zebomon 2y ago
I agree. If the LLMs we have today never got any smarter, the world would still be transformed over the next ten years.
AyyEye 2y ago
> Reading constant comments about LLMs can't be general intelligence or lack reasoning etc, to me seems like people witnessing the airplane and complaining that it isn't "real flying" because it isn't a bird flapping its wings (a large portion of the population held that point of view back then). That is a natural reaction to the incessant techbro, AIbro, marketing, and corporate lies that "AI" (or worse AGI) is a real thing, and can be directly compared to real humans. There are people on this very thread saying it's better at reasoning than real humans (LOL) because it scored higher on some benchmark than humans... Yet this technology still can't reliably determine what number is circled, if two lines intersect, or count the letters in a word. (That said behaviour may have been somewhat finetuned out of newer models only reinforces the fact that the technology inherently not capable of understanding anything.)
- IanCal 2y ago
  I encounter "spicy auto complete" style comments far more often than techbro AI-everything comments and its frankly getting boring. I've been doing AI things for about 20+ years and llms are wild. We've gone from specialized things being pretty bad as those jobs to general purpose things better at that and everything else. The idea you could make and API call with "is this sarcasm?" and get a better than chance guess is incredible.

sigmoid10 2y ago

These comments are getting ridiculous. I remember when this test was first discussed here on HN and everyone agreed that it clearly proves current AI models are not "intelligent" (whatever that means). And people tried to talk me down when I theorised this test will get nuked soon - like all the ones before. It's time people woke up and realised that the old age of AI is over. This new kind is here to stay and it will take over the world. And you better guess it'll be sooner rather than later and start to prepare.

samvher 2y ago
What kind of preparation are you suggesting?
- sigmoid10 2y ago
  This is far too broad to summarise here. You can read up on Sutskever or Bostrom or hell even Steven Hawking's ideas (going in order from really deep to general topics). We need to discuss everything - from education over jobs and taxes all the way to the principles of politics, our economy and even the military. If we fail at this as a society, we will at the very least create a world where the people who own capital today massively benefit and become rich beyond imagination (despite having contributed nothing to it), while the majority of the population will be unemployable and forever left behind. And the worst case probably falls somewhere between the end of human civilisation and the end of our species.
  - kelseyfrog 2y ago
    What we're going to do is punt the questions and then convince ourselves the outcome was inevitable and if anything it's actually our fault.
  - astrange 2y ago
    One way you can tell this isn't realistic is that it's the plot of Atlas Shrugged. If your economic intuitions produce that book it means they are wrong. > while the majority of the population will be unemployable and forever left behind Productivity improvements increase employment. A superhuman AI is a productivity improvement.

FrustratedMonky 2y ago

" it's complete hubris to conflate ARC or any benchmark with truly general intelligence." Maybe it would help to include some human results in the AI ranking. I think we'd find that Humans score lower?

zamadatix 2y ago
I'm not sure it'd help what they are talking about much. E.g. go back in time and imagine you didn't know there are ways for computers to be really good at performing integration yet as nobody had tried to make them. If someone asked you how to tell if something is intelligent "the ability to easily reason integrations or calculate extremely large multiplications in mathematics" might seem like a great test to make. Skip forward to the modern era and it's blatantly obvious CASes like Mathematica on a modern computer range between "ridiculously better than the average person" to "impossibly better than the best person" depending on the test. At the same time, it becomes painfully obvious a CAS is wholly unrelated to general intelligence and just because your test might have been solvable by an AGI doesn't mean solving it proves something must have been an AGI. So you come up with a new test... but you have the same problem as originally, it seems like anything non-human completely bombs and an AGI would do well... but how do you know the thing that solves it will have been an AGI for sure and not just another system clearly unrelated? Short of a more clever way what GP is saying is the goalposts must keep being moved until it's not so obvious the thing isn't AGI, not that the average human gets a certain score which is worse. . All that aside, to answer your original question, in the presentation it was said the average human gets 85% and this was the first model to beat that. It was also said a second version is being worked on. They have some papers on their site about clear examples of why the current test clearly has a lot of testing unrelated to whether something is really AGI (a brute force method was shown to get >50% in 2020) so their aim is to create a new goalpost test and see how things shake out this time.
- FrustratedMonky 2y ago
  "Short of a more clever way what GP is saying is the goalposts must keep being moved until it's not so obvious the thing isn't AGI, not that the average human gets a certain score which is worse." Best way of stating that I've heard. The Goal Post must keep moving, until we understand enough what is happening. I usually poo-poo the goal post moving, but this makes sense.

m3kw9 2y ago

From the statement where - this is a pretty tough test where AI scores low vs humans just last year, and AI can do it as good as humans may not be AGI which I agree, but it means something with all caps

manmal 2y ago
Obviously, the multi billion dollar companies will try to satisfy the benchmarks they are not yet good in, as has always been the case.
- m3kw9 2y ago
  A valid conspiracy theory but I’ve heard that one everystep of the way to this point
  - manmal 2y ago
    What made you write this comment, I have a hard time understanding your point.

wslh 2y ago

> My skeptical impression: it's complete hubris to conflate ARC or any benchmark with truly general intelligence. But isn’t it interesting to have several benchmarks? Even if it’s not about passing the Turing test, benchmarks serve a purpose—similar to how we measure microprocessors or other devices. Intelligence may be more elusive, but even if we had an oracle delivering the ultimate intelligence benchmark, we'd still argue about its limitations. Perhaps we'd claim it doesn't measure creativity well, and we'd find ourselves revisiting the same debates about different kinds of intelligences.

zebomon 2y ago
It's certainly interesting. I'm just not convinced it's a test of general intelligence, and I don't think we'll know whether or not it is until it's been able to operate in the real world to the same degree that our general intelligence does.

kelseyfrog 2y ago

> truly general intelligence Indistinguishable from goalpost moving like you said, but also no true Scotsman. I'm curious what would happen in your eyes if we misattributed general intelligence to an AI model? What are the consequences of a false positive and how would they affect your life? It's really clear to me how intelligence fits into our reality as part of our social ontology. The attributes and their expression that each of us uses to ground our concept of the intelligent predicate differs wildly. My personal theory is that we tend to have an exemplar-based dataset of intelligence, and each of us attempts to construct a parsimonious model of intelligence, but like all (mental) models, they can be useful but wrong. These models operate in a space where the trade off is completeness or consistency, and most folks, uncomfortable saying "I don't know" lean toward being complete in their specification rather than consistent. The unfortunate side-effect is that we're able to easily generate test data that highlights our model inconsistency - AI being a case in point.

PaulDavisThe1st 2y ago
> I'm curious what would happen in your eyes if we misattributed general intelligence to an AI model? What are the consequences of a false positive and how would they affect your life? Rich people will think they can use the AI model instead of paying other people to do certain tasks. The consequences could range from brilliant to utterly catastrophic, depending on the context and precise way in which this is done. But I'd lean toward the catastrophic.
- kelseyfrog 2y ago
  Any specifics? It's difficult to separate this from generalized concern.
  - PaulDavisThe1st 2y ago
    someone wants a "personal assistant" and believes that the LLM has AGI ... someone wants a "planning officer" and believes that the LLM has AGI ... someone wants a "hiring consultant" and believes that the LLM has AGI ... etc. etc.

Agentus 2y ago

how about a extra large dose of your skepticism. is true intelligence really a thing and not just a vague human construct that tries to point out the mysterious unquantifiable combination of human behaviors? humans clearly dont know what intelligence is unambiguously. theres also no divinely ordained objective dictionary that one can point at to reference what true intelligence is. a deep reflection of trying to pattern associate different human cognitive abilities indicates human cognitive capabilities arent that spectacular really.

MVissers 2y ago
My guess as an amateur neuroscientist is that what we call intelligence is just a 'measurement' of problem solving ability in different domains. Can be emotional, spatial, motor, reasoning, etc etc. There is no special sauce in our brain. And we know how much compute there is in our brain– So we can roughly estimate when we'll hit that with these 'LLMs'. Language is important in a human brain development as well. Kids who grow up deaf grow up vastly less intelligent unless they learn sign language. Language allow us to process complex concepts that our brain can learn to solve, without having to be in those complex environments. So in hindsight, it's easy to see why it took a language model to be able to solve general tasks and other types deep learning networks couldn't. I don't really see any limits on these models.
- Agentus 2y ago
  interesting point about language. but i wonder if people misattribute the reason why language is pivotal to human development. your points are valid. i see human behavior with regard to learning as 90% mimicry and 10% autonomous learning. most of what humans believe in is taken on faith and passed on from the tribe to the individual. rarely is it verified even partially let alone fully. humans simple dont have the time or processing power to do that. learning a thing without outside aid is vastly slower and more energy or brain intensive process than copy learning or learning through social institutions by dissemination. the stunted development from lack of language might come more from the less ability to access the collective learning process that language enables and or greatly enhances. i think a lot of learning even when combined with reasoning, deduction, etc really is at the mercy of brute force exploration to find a solution, which individuals are bad at but a society that collects random experienced “ah hah!” occurrences and passes them along is actually okay at. i wonder if llms and language dont as so much allow us to process these complex environments but instead preload our brains to get a head start in processing those complex environments once we arrive in them. i think llms store compressed relationships of the world which obviously has information loss from a neural mapping of the world that isnt just language based. but that compressed relationships ie knowledge doesnt exactly backwardly map onto the world without it having a reverse key. like artificially learning about real world stuff in school abstractly and then going into the real world, it takes time for that abstraction to snap fit upon the real world. could you further elaborate on what you mean by limits, because im happy to play contrarian on what i think i interpret you to be saying there. also to your main point: what intelligence is. yeah you sort of hit up my thoughts on intelligence. its a combination of problem solving abilities in different domains. its like an amalgam of cognitive processes that achieve an amalgam of capabilities. while we can label alllllll that with a singular word, doesnt mean its all a singular process. seems like its a composite. moreover i think a big chunk of intelligence (but not all) is just brute forcing finding associations and then encoding those by some reflexive search/retrieval. a different part of intelligence of course is adaptibility and pattern finding.

Bjorkbat 2y ago

I think it's still an interesting way to measure general intellience, it's just that o3 has demonstrated that you can actually achieve human performance on it by training it on the public training set and giving it ridiculous amounts of compute, which I imagine equates to ludicrously long chains-of-thought, and if I understand correctly more than one chain-of-thought per task (they mention sample sizes in the blog post, with o3-low using 6 and o3-high using 1024. Not sure if these are chains-of-thought per task or what). Once you look at it that way it the approach really doesn't look like intelligence that's able to generalize to novel domains. It doesn't pass the sniff test. It looks a lot more like brute-forcing. Which is probably why, in order to actually qualify for the leaderboard, they stipulate that you can't use more than $10k more of compute. Otherwise, it just sounds like brute-forcing.

BriggyDwiggs42 2y ago
I disagree. It’s vastly inefficient, but it is managing to actually solve these problems with a vast search space. If we extrapolate this approach into the future and assume that the search becomes better as the underlying model improves, and assume that the architecture grows more efficient, and assume that the type of parallel computing used here grows cheaper, isn’t it possible that this is a lot more than brute-forcing in terms of what it will achieve? In other words, is it maybe just a really ugly way of doing something functionally equivalent to reasoning?

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