5 ms·

These types of exams, and most benchmarks to date, seem to be very one dimensional in terms of measuring intelligence. For instance, if we transported a human f

These types of exams, and most benchmarks to date, seem to be very one dimensional in terms of measuring intelligence. For instance, if we transported a human from 2,000 years ago to present day and asked him to take this exam, he would likely get 0%, given that he couldn't read or write, let alone comprehend the concepts and context required to solve these questions. But, that man would still undoubtedly be far more intelligent than an ape on all dimensions. He would likely be more intelligent than a toddler on many dimensions. He might even be more intelligent than some high schools students on a few dimensions. I can't exactly articulate "what" is missing or how to measure it, but I can intuit that some things are in these benchmarks.

oersted 2y ago
"Intelligence" itself is very ill-defined and we've never been able to measure it properly, IQ is rife with issues. At some point, you just have to be pragmatic and measure the questions you want the AI to be good at answering, rather than trying to measure intelligence in general. In that sense, I see this as one more benchmark that collects questions that we want/expect AI to be good at, is not good at yet and have been underrepresented at previous benchmarks. That's obviously valuable, there's nothing "magical" about it. Although it is reasonable to be annoyed at the "Humanity's Last Exam" naming, of course they must have missed plenty of edge-cases like everyone else and it is very arrogant to claim it will be the "Last" one.
- esotericimpl 2y ago
  This is always the answer for anyone who thinks LLMs are capable of "intelligence". It's good at answering questions that its trained on, I would suggest general intelligence are things you didnt want/train the AI to be good at answering.
  - fooker 2y ago
    Are you good at answering questions you are not trained to answer? How about a middle school test in a language you don’t speak?
    - xanderlewis 2y ago
      Yes — reasonably so, anyway. I don't have to have seen millions of prior examples of exactly the same kind in order to tackle a novel problem in mathematics, say.
      - oersted 2y ago
        Well, LLMs are also remarkably good at generalizing. Look at the datasets, they don't literally train on every conceivable type of question the user might ask, the LLM can adapt just as you can. The actual challenge towards general intelligence is that LLMs struggle with certain types of questions even if you *do* train it on millions of examples of that type of question. Mostly questions that require complex logical reasoning, although consistent progress is being done in this direction.
        godelski 2y ago
        > Well, LLMs are also remarkably good at generalizing. Look at the datasets, they don't literally train on every conceivable type of question the user might ask, the LLM can adapt just as you can. Proof needed. I'm serious. We don't have the datasets. But we do know the size of the datasets. And the sizes suggest incredible amounts of information. Take an estimate of 100 tokens ~= 75 words[0]. What is a trillion tokens? Well, that's 750bn words. There are approximately 450 words on a page[1]. So that's 1.66... bn pages! If we put that in 500 page books, that would come out to 3.33... million books! Llama 3 has a pretraining size of 15T tokens[2] (this does not include training, so more info added later). So that comes to ~50m books. Then, keep in mind that this data is filtered and deduplicated. Even considering a high failure rate in deduplication, this an unimaginable amount of information. [0] https://help.openai.com/en/articles/4936856-what-are-tokens-and-how-to-count-them https://help.openai.com/en/articles/4936856-what-are-tokens-... [1] https://wordcounter.net/words-per-page https://wordcounter.net/words-per-page [2] https://ai.meta.com/blog/meta-llama-3/ https://ai.meta.com/blog/meta-llama-3/
        oersted 2y ago
        That’s a very good point. I just speak from my experience of fine-tuning pre-trained models. At least at that stage they can memorize new knowledge, that couldn’t have been in the training data, just by seeing it once during fine-tuning (one epoch), which seems magical. Most instruction-tuning datasets are also remarkably small (very roughly <100K samples). This is only possible if the model has internalized the knowledge quite deeply and generally, such that new knowledge is a tiny gradient update on top of existing expectations. But yes I see what you mean, they are dumping practically the whole internet at it, it’s not unreasonable to think that it has memorized a massive proportion of common question types the user might come up with, such that minimal generalization is needed.
- visarga 2y ago
  > "Intelligence" itself is very ill-defined and we've never been able to measure it properly, IQ is rife with issues. Yes, because it is 1st person exclusively. If you expand a bit, consider "search efficiency". It's no longer just 1st person, it can be social. And it doesn't hide the search space. Intelligence is partially undefined because it doesn't specify the problem space, it is left blank. But "search efficiency" is more scientific and concrete.
- JohnMakin 2y ago
  > IQ is rife with issues Indeed, and yet people are obsessed with the it and the idea of measuring their own intelligence - I completely do not understand it. I am in an extremely high percentile, but I am a total moron in a lot of areas and if you met me would likely think so as well. It's a poor predictor for just about everything except how good a person is at recognizing patterns (I know there are many different kinds of tests, but inevitably, it feels like this) and how quickly they can reason. But people are obsessed with it (Go on quora and search "IQ", you probably won't half to though, since half the questions there are seemingly about IQ). A thing I like to say is you didn't earn your intelligence any more than a 7'0" man earned his height - to some degree it seems innate (we don't even really know how). This all said, it seems even more pointless to try to "IQ" test an AI in this manner. What does it predict? What is it measuring? And you're not going to be able to use the same questions for more than 1 test, because the AI will "learn" the answers.
  - godelski 2y ago
    The lowest IQ thing you can do is be obsessed with IQ. There are known knowns, there are known unknowns, and there are unknown unknowns. The wise man knows he cannot know what he does not know and that it'd be naive to presume he knows when he cannot know how much he doesn't know. Therefore, only the unintelligent man really _knows_ anything.
    - dingnuts 2y ago
      IQ is compute speed, not storage. It has nothing to do with knowledge. IBM used to give one out as part of their hiring process, years ago, and even I took it the entire test was a timed multiple choice exam where every question was looking at an object made out of cubes and choosing the correct orientation of the object from the choices, after the object was arbitrarily rotated according to instructions in the question. Then, IQ can be derived by determining how quickly all participants can answer the questionnaire correctly, and ranking their speeds, and then normalizing the values so 100 is in the middle. Turns out, scores will fall along a bell curve if you do that. You can call that phenomenon whatever, but most people call it IQ and hopefully I've explained well why that has nothing at all to do with static knowledge in this comment.
- godelski 2y ago
  > "Intelligence" itself is very ill-defined While this is true, it is well agreed upon (by domain experts) that intelligence is distinct from knowledge recall. But that's what most of these tests... test. If you look at IQ tests you'll see that they are attempts to test things that aren't knowledge based. You'll also notice that the main critiques of IQ tests are about how they often actually measure knowledge and that there's bias in natural knowledge acquisition. So even the disagreements about the definition of intelligence make clear that knowledge and intelligence are distinct. I feel that often people conflate "intelligence is ill-defined" with "intelligence has no definition." These two are not in opposition. Being ill-defined is more like "I know I left my phone in the house, but I'm not sure where." This is entirely different from "I lost my phone, it is somewhere in California" or "It is somewhere on Earth" and clearly different from "I lost my phone. I'm unsure if I had a phone. What even is a phone?"
  - oersted 2y ago
    Yes agreed, there is indeed a rough consensus on what intelligence is and reasonable ways to approximately measure it. These standard tests have been applied to LLMs from the beginning, they have not proven to be the most helpful to guide research, but there's value to applying benchmarks that have been battle-tested with humans. It's just that OP was questioning this group's criteria for selecting the questions that determine intelligence. Then we get into endless discussions of semantics. At the end of the day, you are just testing which questions your AI performs well on, and you can describe how you chose those questions. Claiming it measures "general intelligence" is just unhelpful and frustrating.
    - godelski 2y ago
      They were applied in the beginning because we really weren't that good at solving the tasks. So like any good researchers, we break it down. But this is like trying to test an elephant but you can't get access to an elephant so you instead train a dog. But putting a dog in an elephant costume doesn't make it an elephant. Sure, dog training will likely mean you can learn to train an elephant faster had you not first trained a dog. Some things transfer, but others don't I also want to stress that there is a rough consensus. But the ML field (which I'm a part of) often ignores this. I'm not sure why. We should be leveraging the work of others, not trying to start from scratch (unless there's good reason, in which case we must be explicit. But I'm just seeing simple claims of "intelligence is ill-defined" and treating that as if that means no definition instead of fuzzy definition. Which gets extra weird when people talk about moving goal posts. That's how progress works? Especially when exploring into the unknown?)
famouswaffles 2y ago
This is true but that's because it's gotten hard to do much else. LLMs are eating up everything else that don't require long horizon planning or multimodality. If you created a new benchmark today that didn't lean on the things I've mentioned or esoteric/super specialized domain knowledge (that would actually require some sort of super-human performance to ace) like this or Frontier Math, LLMs would probably do pretty well.
WanderPanda 2y ago
I mean it is humanity’s LAST exam. Humanity’s first exam would probably be something about communication? Or about building and predicting effects of certain tools?
golol 2y ago
The things that are missing are what stops us from having useful agents so far: Agency, judgement, sense of time, long horizon planning, not being gullible. I kinda feel like some amount of ego is necessary to get a model to behave like that.
fooker 2y ago
Put ‘em in diverse simulations and see how long they survive. I can imagine a dystopian world where people are subject to this for training and testing AI.
modeless 2y ago
ARC-AGI is a benchmark with no language that could plausibly be solved by primitive humans, assuming only intelligence.
godelski 2y ago
> seem to be very one dimensional in terms of measuring intelligence. I would argue that they DON'T measure intelligence, rather they test knowledge. Frustratingly, I think we have a society greatly focused on knowledge based testing due to its correlation with intelligence and that it is exponentially easier to test knowledge. But this is easy to hack. Being in CS it feels very odd since we all know a great way to get hired is to study leetcode questions. That is, study to the test. This is critical to recognize this difference as what we know for certain is that LLMs and other ML systems are analogous to a database with a human language interface[0]. What we DO NOT KNOW is if these systems are intelligent. That is, that they can use their exploit their knowledge to unfamiliar territories. Then there's the whole question of wisdom... This stuff is highly abstract and we can get fuzzy so it is natural to go for the simple thing but we need to graduate. Don't avoid the tough questions, dig in. As we advance in any study nuance takes over. This should be obvious. If we approximate things, to improve we need to tackle higher order terms, and that almost always becomes exponentially more difficult with each step. And come on, is this benchmark not obvious bait? Calling it "humanity's last exam" is extremely arrogant. Definitions: Knowledge: Awareness of facts. The ability to recall information. Intelligence: Ability to exploit knowledge to new settings. To be able to plan and reason. (Definitions of intelligence are much more debated than knowledge but what is far less controversial is that intelligence is about the way one uses knowledge. These two are distinct. This is fairly well agreed upon throughout history and within modern literature around psychology and cognitive science.) Wisdom: The efficient use of one's knowledge https://en.wikipedia.org/wiki/Knowledge https://en.wikipedia.org/wiki/Intelligence https://en.wikipedia.org/wiki/Wisdom There is a implicit hierarchy here[1] where knowledge is something to be had, intelligence is the utilization of that, and wisdom is about efficiency. There's a decent analogy to this hierarchy. Knowledge is like having a tool. Intelligence is like using it, a craftsman[2]. Wisdom is akin to being a master craftsman. [0] I mean that they fit the data. A database is discrete, but these curve fit, so that will be a continuous function (in most cases). Thus it won't be exact retrieval nor does this mean information can't be interpolated. But that gets to be a deeper and much more complex conversation that I think we like to admit. [1] This is clearly multi-dimensional. You can organize hierarchies in multiple ways, I'm not suggesting this is the only way or "the right way" [2] What is argued is what is a sufficient threshold. An armchair expert might know how to use a lathe because they read about its usage but does that mean they can use it? What about a novice who you can show something to and they can repeat it? Monkey see monkey do style. An apprentice? A craftsman? There's a lot of gray area between being able to recall something from a book and being a wizard (gray beard).
tkgally 2y ago
I agree that many aspects of intelligence—and of the lack of intelligence—are not being measured by such benchmarks. One issue is they are only examining problems that have right answers. One of the most powerful uses of LLMs for me, at least, is brainstorming: having them suggest possible avenues for me to pursue with specific projects I am working on. If I give Claude or ChatGPT or Gemini enough context about my problems, they usually come up with useful suggestions—sometimes amazingly well. Are they better at that than the smartest human? I don't know. How do you quantify the quality of an idea? But those ideas often seem really, really good to me. Another difficult-to-measure capability is interaction. Back-and-forth conversations with models don't always go well, but when they work they frequently blow me away. But those successes are dependent partly on the model, partly on me, and partly on how the conversation happens to unfold. Again, that success or failure doesn't seem measurable with benchmarks that require objectively right answers.
taeric 2y ago
I'm curious why you are confident they would be more intelligent than a modern toddler? I largely empathize with your point. But, as I can recognize there are some out there far better at problem solving than I am, I am growing ok with the idea that intelligence can be measured. Not to a single number, most likely, but to a variety of different aspects. Similarly, I'd imagine that a human from 2000 years ago is probably more hardy than one from the modern age. If only because of selection effects at play. Obviously, you can't extrapolate a straight line between either measurement and expect it to continue in either direction. But I don't know why you couldn't build up a measurement for it? (And it should go without saying that you shouldn't be judging worth using this sort of measurement.)
- ianburrell 2y ago
  Adults from 2000 years ago would absolutely be smarter than toddlers. Adults back then watched and out thought their toddlers. Do you think toddlers now are much smarter? Especially when toddlers are from before they get educated. Remember that 2000 years ago is 24AD, the middle of the Roman empire and Han dynasty which covered half of the world population. Nobles would be literate and well educated, artisans and soldiers would be skilled, and I bet there were lots of smart peasants that got ignored. They wouldn't do well on intelligence tests because not used to it, but that is more about tests than their intelligence. I'm sure that the average intelligence is lower than now from lack of education and malnutrition. Smart ones would still be smart. Also, I bet people from now would do poorly in their environment.
  - taeric 2y ago
    Ok, fair, 2000 wasn't that long ago. :D I was assuming it was a placeholder for "very distantly old humans." Such that my question mostly still stands? Again, I'm largely inline with the view that this will be difficult to test. However, I'm also comfortable in saying that you can tell intelligence levels between people. Again, with a caveat that I don't think it is reducible to a single number. (Such that I think I also think it is fair to say most views of intelligence, in the colloquial sense, are not transitive.) As an example, as much as I loved my grandparents, I have zero difficulty saying that a few of them would never be able to score as well on some problem solving tests as a few of the kids in the current generation. At the same time I know some people in their 80s that I will never be able to compare with. Again, I don't expect it is a straight line, along the time axis. I also don't know that I agree that every person 2000 years ago just didn't do calculus because they weren't taught it.
munchbunny 2y ago
I think the concept you're dancing around the edges of is the nature of what parts of "intelligence" are driven by: 1. Language and how interrelated it is to our ability to transfer knowledge and experience, as well as its role in structuring our internal thinking. I haven't seen any academic research on the matter, but there are more and less concrete instances of this throughout history. This Wikipedia article about the history of Algebra is a great example of how 2000 years of evolution led to a formulation of the same concepts, but with a reduced cognitive load that 10-12 years olds learn today as a matter of course. (https://en.wikipedia.org/wiki/History_of_algebra#Stages_of_algebra https://en.wikipedia.org/wiki/History_of_algebra#Stages_of_a...). 2. Knowledge, transferred through language, education, and culture. Calculus in the early 1600's is a great example, without it and subsequent developments, probably 80% of the college/post-grad math/science/physics education wouldn't even exist. The stuff we teach our 18 year olds today required the 1600s' greatest minds to figure out. 3. The capacity of our human wetware. It's hard to treat #3 in isolation because our modern concept of intelligence is inextricably tied to #1 and #2. Also it's hard to place where "critical thinking" and "creativity" enter the picture, since they both rely heavily on all three aspects above.
turbojet1321 2y ago
I think you're under-selling your point. Forget highschool students - some of the greatest thinkers in human history lived 2000+ years ago.
barnabyjones 2y ago
>He would likely be more intelligent than a toddler I think you are falling into the trap of "we have technology and are therefore smarter." I would expect an average Roman senator could formulate far better speeches off the top of his head than 99% of modern people, and also in excess of anything an LLM is capable of. And that's supposed to be an LLM's specialty, there's no comparison when it comes to organizing actual projects like construction or campaigns.

oersted 2y ago

"Intelligence" itself is very ill-defined and we've never been able to measure it properly, IQ is rife with issues. At some point, you just have to be pragmatic and measure the questions you want the AI to be good at answering, rather than trying to measure intelligence in general. In that sense, I see this as one more benchmark that collects questions that we want/expect AI to be good at, is not good at yet and have been underrepresented at previous benchmarks. That's obviously valuable, there's nothing "magical" about it. Although it is reasonable to be annoyed at the "Humanity's Last Exam" naming, of course they must have missed plenty of edge-cases like everyone else and it is very arrogant to claim it will be the "Last" one.

esotericimpl 2y ago
This is always the answer for anyone who thinks LLMs are capable of "intelligence". It's good at answering questions that its trained on, I would suggest general intelligence are things you didnt want/train the AI to be good at answering.
- fooker 2y ago
  Are you good at answering questions you are not trained to answer? How about a middle school test in a language you don’t speak?
  - xanderlewis 2y ago
    Yes — reasonably so, anyway. I don't have to have seen millions of prior examples of exactly the same kind in order to tackle a novel problem in mathematics, say.
    - oersted 2y ago
      Well, LLMs are also remarkably good at generalizing. Look at the datasets, they don't literally train on every conceivable type of question the user might ask, the LLM can adapt just as you can. The actual challenge towards general intelligence is that LLMs struggle with certain types of questions even if you *do* train it on millions of examples of that type of question. Mostly questions that require complex logical reasoning, although consistent progress is being done in this direction.
      - godelski 2y ago
        > Well, LLMs are also remarkably good at generalizing. Look at the datasets, they don't literally train on every conceivable type of question the user might ask, the LLM can adapt just as you can. Proof needed. I'm serious. We don't have the datasets. But we do know the size of the datasets. And the sizes suggest incredible amounts of information. Take an estimate of 100 tokens ~= 75 words[0]. What is a trillion tokens? Well, that's 750bn words. There are approximately 450 words on a page[1]. So that's 1.66... bn pages! If we put that in 500 page books, that would come out to 3.33... million books! Llama 3 has a pretraining size of 15T tokens[2] (this does not include training, so more info added later). So that comes to ~50m books. Then, keep in mind that this data is filtered and deduplicated. Even considering a high failure rate in deduplication, this an unimaginable amount of information. [0] https://help.openai.com/en/articles/4936856-what-are-tokens-and-how-to-count-them https://help.openai.com/en/articles/4936856-what-are-tokens-... [1] https://wordcounter.net/words-per-page https://wordcounter.net/words-per-page [2] https://ai.meta.com/blog/meta-llama-3/ https://ai.meta.com/blog/meta-llama-3/
        oersted 2y ago
        That’s a very good point. I just speak from my experience of fine-tuning pre-trained models. At least at that stage they can memorize new knowledge, that couldn’t have been in the training data, just by seeing it once during fine-tuning (one epoch), which seems magical. Most instruction-tuning datasets are also remarkably small (very roughly <100K samples). This is only possible if the model has internalized the knowledge quite deeply and generally, such that new knowledge is a tiny gradient update on top of existing expectations. But yes I see what you mean, they are dumping practically the whole internet at it, it’s not unreasonable to think that it has memorized a massive proportion of common question types the user might come up with, such that minimal generalization is needed.
visarga 2y ago
> "Intelligence" itself is very ill-defined and we've never been able to measure it properly, IQ is rife with issues. Yes, because it is 1st person exclusively. If you expand a bit, consider "search efficiency". It's no longer just 1st person, it can be social. And it doesn't hide the search space. Intelligence is partially undefined because it doesn't specify the problem space, it is left blank. But "search efficiency" is more scientific and concrete.
JohnMakin 2y ago
> IQ is rife with issues Indeed, and yet people are obsessed with the it and the idea of measuring their own intelligence - I completely do not understand it. I am in an extremely high percentile, but I am a total moron in a lot of areas and if you met me would likely think so as well. It's a poor predictor for just about everything except how good a person is at recognizing patterns (I know there are many different kinds of tests, but inevitably, it feels like this) and how quickly they can reason. But people are obsessed with it (Go on quora and search "IQ", you probably won't half to though, since half the questions there are seemingly about IQ). A thing I like to say is you didn't earn your intelligence any more than a 7'0" man earned his height - to some degree it seems innate (we don't even really know how). This all said, it seems even more pointless to try to "IQ" test an AI in this manner. What does it predict? What is it measuring? And you're not going to be able to use the same questions for more than 1 test, because the AI will "learn" the answers.
- godelski 2y ago
  The lowest IQ thing you can do is be obsessed with IQ. There are known knowns, there are known unknowns, and there are unknown unknowns. The wise man knows he cannot know what he does not know and that it'd be naive to presume he knows when he cannot know how much he doesn't know. Therefore, only the unintelligent man really _knows_ anything.
  - dingnuts 2y ago
    IQ is compute speed, not storage. It has nothing to do with knowledge. IBM used to give one out as part of their hiring process, years ago, and even I took it the entire test was a timed multiple choice exam where every question was looking at an object made out of cubes and choosing the correct orientation of the object from the choices, after the object was arbitrarily rotated according to instructions in the question. Then, IQ can be derived by determining how quickly all participants can answer the questionnaire correctly, and ranking their speeds, and then normalizing the values so 100 is in the middle. Turns out, scores will fall along a bell curve if you do that. You can call that phenomenon whatever, but most people call it IQ and hopefully I've explained well why that has nothing at all to do with static knowledge in this comment.
godelski 2y ago
> "Intelligence" itself is very ill-defined While this is true, it is well agreed upon (by domain experts) that intelligence is distinct from knowledge recall. But that's what most of these tests... test. If you look at IQ tests you'll see that they are attempts to test things that aren't knowledge based. You'll also notice that the main critiques of IQ tests are about how they often actually measure knowledge and that there's bias in natural knowledge acquisition. So even the disagreements about the definition of intelligence make clear that knowledge and intelligence are distinct. I feel that often people conflate "intelligence is ill-defined" with "intelligence has no definition." These two are not in opposition. Being ill-defined is more like "I know I left my phone in the house, but I'm not sure where." This is entirely different from "I lost my phone, it is somewhere in California" or "It is somewhere on Earth" and clearly different from "I lost my phone. I'm unsure if I had a phone. What even is a phone?"
- oersted 2y ago
  Yes agreed, there is indeed a rough consensus on what intelligence is and reasonable ways to approximately measure it. These standard tests have been applied to LLMs from the beginning, they have not proven to be the most helpful to guide research, but there's value to applying benchmarks that have been battle-tested with humans. It's just that OP was questioning this group's criteria for selecting the questions that determine intelligence. Then we get into endless discussions of semantics. At the end of the day, you are just testing which questions your AI performs well on, and you can describe how you chose those questions. Claiming it measures "general intelligence" is just unhelpful and frustrating.
  - godelski 2y ago
    They were applied in the beginning because we really weren't that good at solving the tasks. So like any good researchers, we break it down. But this is like trying to test an elephant but you can't get access to an elephant so you instead train a dog. But putting a dog in an elephant costume doesn't make it an elephant. Sure, dog training will likely mean you can learn to train an elephant faster had you not first trained a dog. Some things transfer, but others don't I also want to stress that there is a rough consensus. But the ML field (which I'm a part of) often ignores this. I'm not sure why. We should be leveraging the work of others, not trying to start from scratch (unless there's good reason, in which case we must be explicit. But I'm just seeing simple claims of "intelligence is ill-defined" and treating that as if that means no definition instead of fuzzy definition. Which gets extra weird when people talk about moving goal posts. That's how progress works? Especially when exploring into the unknown?)

famouswaffles 2y ago

This is true but that's because it's gotten hard to do much else. LLMs are eating up everything else that don't require long horizon planning or multimodality. If you created a new benchmark today that didn't lean on the things I've mentioned or esoteric/super specialized domain knowledge (that would actually require some sort of super-human performance to ace) like this or Frontier Math, LLMs would probably do pretty well.

WanderPanda 2y ago

I mean it is humanity’s LAST exam. Humanity’s first exam would probably be something about communication? Or about building and predicting effects of certain tools?

golol 2y ago

The things that are missing are what stops us from having useful agents so far: Agency, judgement, sense of time, long horizon planning, not being gullible. I kinda feel like some amount of ego is necessary to get a model to behave like that.

fooker 2y ago

Put ‘em in diverse simulations and see how long they survive. I can imagine a dystopian world where people are subject to this for training and testing AI.

modeless 2y ago

ARC-AGI is a benchmark with no language that could plausibly be solved by primitive humans, assuming only intelligence.

godelski 2y ago

> seem to be very one dimensional in terms of measuring intelligence. I would argue that they DON'T measure intelligence, rather they test knowledge. Frustratingly, I think we have a society greatly focused on knowledge based testing due to its correlation with intelligence and that it is exponentially easier to test knowledge. But this is easy to hack. Being in CS it feels very odd since we all know a great way to get hired is to study leetcode questions. That is, study to the test. This is critical to recognize this difference as what we know for certain is that LLMs and other ML systems are analogous to a database with a human language interface[0]. What we DO NOT KNOW is if these systems are intelligent. That is, that they can use their exploit their knowledge to unfamiliar territories. Then there's the whole question of wisdom... This stuff is highly abstract and we can get fuzzy so it is natural to go for the simple thing but we need to graduate. Don't avoid the tough questions, dig in. As we advance in any study nuance takes over. This should be obvious. If we approximate things, to improve we need to tackle higher order terms, and that almost always becomes exponentially more difficult with each step. And come on, is this benchmark not obvious bait? Calling it "humanity's last exam" is extremely arrogant. Definitions: Knowledge: Awareness of facts. The ability to recall information. Intelligence: Ability to exploit knowledge to new settings. To be able to plan and reason. (Definitions of intelligence are much more debated than knowledge but what is far less controversial is that intelligence is about the way one uses knowledge. These two are distinct. This is fairly well agreed upon throughout history and within modern literature around psychology and cognitive science.) Wisdom: The efficient use of one's knowledge https://en.wikipedia.org/wiki/Knowledge https://en.wikipedia.org/wiki/Intelligence https://en.wikipedia.org/wiki/Wisdom There is a implicit hierarchy here[1] where knowledge is something to be had, intelligence is the utilization of that, and wisdom is about efficiency. There's a decent analogy to this hierarchy. Knowledge is like having a tool. Intelligence is like using it, a craftsman[2]. Wisdom is akin to being a master craftsman. [0] I mean that they fit the data. A database is discrete, but these curve fit, so that will be a continuous function (in most cases). Thus it won't be exact retrieval nor does this mean information can't be interpolated. But that gets to be a deeper and much more complex conversation that I think we like to admit. [1] This is clearly multi-dimensional. You can organize hierarchies in multiple ways, I'm not suggesting this is the only way or "the right way" [2] What is argued is what is a sufficient threshold. An armchair expert might know how to use a lathe because they read about its usage but does that mean they can use it? What about a novice who you can show something to and they can repeat it? Monkey see monkey do style. An apprentice? A craftsman? There's a lot of gray area between being able to recall something from a book and being a wizard (gray beard).

tkgally 2y ago

I agree that many aspects of intelligence—and of the lack of intelligence—are not being measured by such benchmarks. One issue is they are only examining problems that have right answers. One of the most powerful uses of LLMs for me, at least, is brainstorming: having them suggest possible avenues for me to pursue with specific projects I am working on. If I give Claude or ChatGPT or Gemini enough context about my problems, they usually come up with useful suggestions—sometimes amazingly well. Are they better at that than the smartest human? I don't know. How do you quantify the quality of an idea? But those ideas often seem really, really good to me. Another difficult-to-measure capability is interaction. Back-and-forth conversations with models don't always go well, but when they work they frequently blow me away. But those successes are dependent partly on the model, partly on me, and partly on how the conversation happens to unfold. Again, that success or failure doesn't seem measurable with benchmarks that require objectively right answers.

taeric 2y ago

I'm curious why you are confident they would be more intelligent than a modern toddler? I largely empathize with your point. But, as I can recognize there are some out there far better at problem solving than I am, I am growing ok with the idea that intelligence can be measured. Not to a single number, most likely, but to a variety of different aspects. Similarly, I'd imagine that a human from 2000 years ago is probably more hardy than one from the modern age. If only because of selection effects at play. Obviously, you can't extrapolate a straight line between either measurement and expect it to continue in either direction. But I don't know why you couldn't build up a measurement for it? (And it should go without saying that you shouldn't be judging worth using this sort of measurement.)

ianburrell 2y ago
Adults from 2000 years ago would absolutely be smarter than toddlers. Adults back then watched and out thought their toddlers. Do you think toddlers now are much smarter? Especially when toddlers are from before they get educated. Remember that 2000 years ago is 24AD, the middle of the Roman empire and Han dynasty which covered half of the world population. Nobles would be literate and well educated, artisans and soldiers would be skilled, and I bet there were lots of smart peasants that got ignored. They wouldn't do well on intelligence tests because not used to it, but that is more about tests than their intelligence. I'm sure that the average intelligence is lower than now from lack of education and malnutrition. Smart ones would still be smart. Also, I bet people from now would do poorly in their environment.
- taeric 2y ago
  Ok, fair, 2000 wasn't that long ago. :D I was assuming it was a placeholder for "very distantly old humans." Such that my question mostly still stands? Again, I'm largely inline with the view that this will be difficult to test. However, I'm also comfortable in saying that you can tell intelligence levels between people. Again, with a caveat that I don't think it is reducible to a single number. (Such that I think I also think it is fair to say most views of intelligence, in the colloquial sense, are not transitive.) As an example, as much as I loved my grandparents, I have zero difficulty saying that a few of them would never be able to score as well on some problem solving tests as a few of the kids in the current generation. At the same time I know some people in their 80s that I will never be able to compare with. Again, I don't expect it is a straight line, along the time axis. I also don't know that I agree that every person 2000 years ago just didn't do calculus because they weren't taught it.

munchbunny 2y ago

I think the concept you're dancing around the edges of is the nature of what parts of "intelligence" are driven by: 1. Language and how interrelated it is to our ability to transfer knowledge and experience, as well as its role in structuring our internal thinking. I haven't seen any academic research on the matter, but there are more and less concrete instances of this throughout history. This Wikipedia article about the history of Algebra is a great example of how 2000 years of evolution led to a formulation of the same concepts, but with a reduced cognitive load that 10-12 years olds learn today as a matter of course. (https://en.wikipedia.org/wiki/History_of_algebra#Stages_of_algebra https://en.wikipedia.org/wiki/History_of_algebra#Stages_of_a...). 2. Knowledge, transferred through language, education, and culture. Calculus in the early 1600's is a great example, without it and subsequent developments, probably 80% of the college/post-grad math/science/physics education wouldn't even exist. The stuff we teach our 18 year olds today required the 1600s' greatest minds to figure out. 3. The capacity of our human wetware. It's hard to treat #3 in isolation because our modern concept of intelligence is inextricably tied to #1 and #2. Also it's hard to place where "critical thinking" and "creativity" enter the picture, since they both rely heavily on all three aspects above.

turbojet1321 2y ago

I think you're under-selling your point. Forget highschool students - some of the greatest thinkers in human history lived 2000+ years ago.

barnabyjones 2y ago

>He would likely be more intelligent than a toddler I think you are falling into the trap of "we have technology and are therefore smarter." I would expect an average Roman senator could formulate far better speeches off the top of his head than 99% of modern people, and also in excess of anything an LLM is capable of. And that's supposed to be an LLM's specialty, there's no comparison when it comes to organizing actual projects like construction or campaigns.