It's pretty close to how we measure IQ. The standard test is basically a series of spatial puzzles.
I know there's a lot of people who complain that we're moving goalposts, but I think that the progress in LLMs really just shows that we don't know how to really measure intelligence in the first place, if we understand it as "human-like agency / ingenuity / adaptability". For decades, we saw the Turing test as the proxy for AGI, but then early LLMs could easily pass for a human in a casual conversation while clearly not matching human performance on most other tasks.
Since then, every benchmark we come up with, it turns out that an LLM can be fine-tuned to solve it while still clearly lacking something. They make very non-human mistakes, are easily tricked because they have a pretty tenuous grasp of reality, etc. But I think this just shows that AGI is a meaningless marketing term. We could as well be arguing if they have souls.
IQ tests are incredibly good at what they're designed for, which is discriminating relatively higher intelligence humans from lower intelligence humans. Also discriminating within a single human - they are routinely and reliably used to track cognitive decline.
For these purposes they are highly reliable (repeatable, internally consistent) and valid (correlate with ~everything to about the degree one would reasonably expect).
They were never designed for machines or non-human animals.
Nor were they designed for rare ranges of intelligence - these are by definition hard to create tests for, since it's hard to gather the sample sizes you need. So they work well for the middle ~98% of humans but can't discriminate well among the most profoundly intellectually disabled nor among true geniuses.
When I was 18, my high school girlfriend took me to the local Mensa chapter’s New Year’s party because her mother was a member and she was used to hanging out there.
It was a useful lesson that whatever IQ tests measure, it is completely devoid of value or interest to me.
At the risk of sounding like one of those people at Mensa that annoyed you...
The people at Mensa aren't a valid sample of people who score high on IQ tests, because there is a such a strong selection effect for people with certain personality traits, such as wanting to join a club based on your IQ.
By looking at interactions of people in Mensa I feel like 2% of top IQ is actually too low bar to notice anything particular about "high" IQ people. We are still pretty random in our interests and performance.
Is it a serious question? IQ tries to quantify the positive correlation between the results of all intellectual tasks a person takes (AKA positive manifold).
Whatever the people who came up with IQ intended isn’t really relevant to the question of whether IQ measures intellect. At best is is loosely correlated. Very loosely.
IQ strongly correlates with many real world outcomes that people tend to associate with being more "intellectual".
IQ has precise definition. It's what the tests measure. Intellect has only fuzzy handwavey definition. Correlation between IQ and intellect is about as loose as the definition of the intellect. The way people make the correlation even looser is by defining intellect in even more fuzzy and nebulous manner.
I suspect my IQ isn’t quite high enough to join Mensa but I’ve always flirted with the idea of trying to join and getting in just to see what a group of Mensa people are like.
We are basically random. 2% of population by top IQ test result has pretty much very similar distribution in all aspects to 100% of the population. It's not a high bar to be fastest processing one among 50 people.
It might, but if there's one thing that hasn't changed since 2022, it's that the models tend to ace the tasks where you have gobs of training data and where verification loops are fast and cheap... and they are not nearly as amazing elsewhere. If it's close enough, they can generalize, e.g. translate one programming language to another. But there's a pretty steep cliff past a certain distance.
Case in point: you had hundreds of millions of JPEGs to vacuum up and bitmap image generation is amazing. But if you ask them to recreate the same scene as vector art, they will struggle to generate a decent SVG. Like, kindergarten-style pelicans on bicycles are the state of the art. It should generalize seamlessly, but somehow, doesn't?
I think it will happen, just like self-driving cars are happening, but it will probably be a slow process.
Nit: Turing’s actual imitation game is a party game (like Werewolf/Mafia) and nobody’s even trying to win at that. The LLM’s will just tell you they’re an AI.
This is an artifact of how we deliberately craft these models though. We could just as easily fine tune a model that will believe it is not an AI or will attempt to deceive users asking about it
There's a lot more to it. For example, its writing style would also have to improve so it doesn't immediately give itself away.
Also, the skill of the human opponents matters. You'd want to test it against people who have practiced playing the game. Otherwise, it's like the difference between building a chess bot that can win against random undergrads who don't normally play, versus winning against grandmasters. And it's not like there's a pool of skilled human players of the imitation game.
Their input and output interfaces are too different from human's and they're not nearly as smart to take our IQ tests, but both dolphins and octopuses can solve complex puzzles tailored for their environment. Those puzzles are the whole reason scientists know that dolphins and octopuses are more intelligent than other animals.
But we do know they're "intelligent" and also smart in an important capacity. So how gives we don't measure them by IQ? Because the IQ is not a good measure of intelligence or smarts.
> No, it is just because they have difficulties at the bench.
I'll put it in another way. A "gifted kid" can be measured incredibly well on an IQ test, but fail miserably at incredibly normal but very difficult tasks such as consoling someone for their loss and managing family crisis. This is a clear example where an IQ measure doesn't translate to a person being capable of meaningfully changing their environments for good which is one way we define intelligence.
On the other hand saying "the gifted person is highly intelligent/smart just not good at some things" really diminishes the other tasks, because they really are very difficult tasks but are not measured by an IQ test.
There's currently a big market for figuring out ways to measure intelligence. With a particular interest in ways that humans can score much higher than LLMs. If you have some ideas please do share!
I think children having learning abilities exceeding LLM test-time learning (currently only happens in-context). But it's unethical to determine the true baseline of a child age 6 spending 6 years learning a radically new skill to mastery--and besides if you apply RL pressure to the AIs it would be able to surpass it. I guess I still believe future AIs should have some form of continual learning at test-time.
Why? Seems like benchmarks that closely mirror the tasks you'd want an LLM to help with would be a lot more useful than some general intelligence benchmark.
Give away access to the model and go ask people from time to time if the model was of use to the person and if they were able to make the model work with them.
This is like arguing about whether a hot dog is a sandwich (of course it is) or whether the chicken or the egg was first (obviously the egg since all chickens come from eggs). Intelligence is just problem solving in the context of self-awareness. Machines don't have it and never will but they can simulate the process given inputs. You can argue whether humans and animals truly possess self-awareness and in what degree, but the definition of intelligence is as simple as the hot dog debate.
It was defined in Animal Intelligence by George John Ramones in 1882 as "intelligence is the capacity to do the right thing at the right time. It is the ability to respond to the opportunities and challenges presented by a context"
I'm also unclear as to how basic inferential logic puzzles spells out intelligence
I think if you summed up measures of intelligence as 'can it do basic symbolic logic in a chain with memory' then yes, you've now achieved the intelligence of an e. coli colony [0], congratulations
so give it an IQ test and call it AGI. these weird little puzzles are grounded in no research with no replication or mechanistic chain to practical use
You should read more on the ARC prize, it actually has a pretty long history. We're on the 3rd iteration because they keep getting saturated. If you look at the score history over time on ARC AGI 1, 2 and 3 it's pretty impressive.
No, but figuring out that you're playing a snake-like puzzle game at all in an extremely general input domain and then solving it in the least number of moves definitely feels like evidence of intelligence.
You forget the benchmark. The human subjects were told they were being timed. If you believe the lowest time is the primary metric you will absolutely trial and error at speed instead of meticulously plan out your moves to minimize that metric.
LLMs are not timed and given that it costs tens of thousands of dollars to run this test they're not optimizing for speed.
So you've got a deceptive test, with one metric being told to humans and not applied to LLM and a hidden metric humans aren't aware of but LLMs are as the test.
This is flawed from the get go. It almost seems like this was deliberately setup to be able to claim AGI and superiority of LLMs
Not fully relevant: timing is crucial in all-pass tests, not crucial in pass-or-fail tests. I.e.: first of all, they have to be able to reach the goal, and that is already an achievement. Then - and in parallel - the problem solving must also be optimized for efficiency. But "solving" and "efficiency" are non coincident dimensions.
It's pretty close to how we measure IQ. The standard test is basically a series of spatial puzzles.
I know there's a lot of people who complain that we're moving goalposts, but I think that the progress in LLMs really just shows that we don't know how to really measure intelligence in the first place, if we understand it as "human-like agency / ingenuity / adaptability". For decades, we saw the Turing test as the proxy for AGI, but then early LLMs could easily pass for a human in a casual conversation while clearly not matching human performance on most other tasks.
Since then, every benchmark we come up with, it turns out that an LLM can be fine-tuned to solve it while still clearly lacking something. They make very non-human mistakes, are easily tricked because they have a pretty tenuous grasp of reality, etc. But I think this just shows that AGI is a meaningless marketing term. We could as well be arguing if they have souls.
IQ tests are incredibly good at what they're designed for, which is discriminating relatively higher intelligence humans from lower intelligence humans. Also discriminating within a single human - they are routinely and reliably used to track cognitive decline.
For these purposes they are highly reliable (repeatable, internally consistent) and valid (correlate with ~everything to about the degree one would reasonably expect).
They were never designed for machines or non-human animals.
Nor were they designed for rare ranges of intelligence - these are by definition hard to create tests for, since it's hard to gather the sample sizes you need. So they work well for the middle ~98% of humans but can't discriminate well among the most profoundly intellectually disabled nor among true geniuses.
When I was 18, my high school girlfriend took me to the local Mensa chapter’s New Year’s party because her mother was a member and she was used to hanging out there.
It was a useful lesson that whatever IQ tests measure, it is completely devoid of value or interest to me.
At the risk of sounding like one of those people at Mensa that annoyed you...
The people at Mensa aren't a valid sample of people who score high on IQ tests, because there is a such a strong selection effect for people with certain personality traits, such as wanting to join a club based on your IQ.
Or, to put it as Groucho Marx did:
"Please accept my resignation, I don't want to belong to any club that would have me as a member".
https://www.youtube.com/watch?v=kJHUres_2xU&t=228s
By looking at interactions of people in Mensa I feel like 2% of top IQ is actually too low bar to notice anything particular about "high" IQ people. We are still pretty random in our interests and performance.
What does having value or interest to you have to do with intelligence?
What does IQ have to do with intelligence?
(Please forgive the flippant response. I believe it cuts to the core of what the parent was intending.)
Is it a serious question? IQ tries to quantify the positive correlation between the results of all intellectual tasks a person takes (AKA positive manifold).
Whatever the people who came up with IQ intended isn’t really relevant to the question of whether IQ measures intellect. At best is is loosely correlated. Very loosely.
OK. Demonstrate it. BTW, you can easily read critiques of "The mismeasure of Man" if you want to.
IQ strongly correlates with many real world outcomes that people tend to associate with being more "intellectual".
IQ has precise definition. It's what the tests measure. Intellect has only fuzzy handwavey definition. Correlation between IQ and intellect is about as loose as the definition of the intellect. The way people make the correlation even looser is by defining intellect in even more fuzzy and nebulous manner.
To be fair, Mensa is a Venn diagram between IQ and being a douche.
I suspect my IQ isn’t quite high enough to join Mensa but I’ve always flirted with the idea of trying to join and getting in just to see what a group of Mensa people are like.
We are basically random. 2% of population by top IQ test result has pretty much very similar distribution in all aspects to 100% of the population. It's not a high bar to be fastest processing one among 50 people.
Pure software benchmarks might be getting saturated, but physical ones aren't.
Let LLM control a physical robot to perform tasks that average human can do.
What makes you think this task won't fall quickly too?
It might, but if there's one thing that hasn't changed since 2022, it's that the models tend to ace the tasks where you have gobs of training data and where verification loops are fast and cheap... and they are not nearly as amazing elsewhere. If it's close enough, they can generalize, e.g. translate one programming language to another. But there's a pretty steep cliff past a certain distance.
Case in point: you had hundreds of millions of JPEGs to vacuum up and bitmap image generation is amazing. But if you ask them to recreate the same scene as vector art, they will struggle to generate a decent SVG. Like, kindergarten-style pelicans on bicycles are the state of the art. It should generalize seamlessly, but somehow, doesn't?
I think it will happen, just like self-driving cars are happening, but it will probably be a slow process.
Nit: Turing’s actual imitation game is a party game (like Werewolf/Mafia) and nobody’s even trying to win at that. The LLM’s will just tell you they’re an AI.
This is an artifact of how we deliberately craft these models though. We could just as easily fine tune a model that will believe it is not an AI or will attempt to deceive users asking about it
There's a lot more to it. For example, its writing style would also have to improve so it doesn't immediately give itself away.
Also, the skill of the human opponents matters. You'd want to test it against people who have practiced playing the game. Otherwise, it's like the difference between building a chess bot that can win against random undergrads who don't normally play, versus winning against grandmasters. And it's not like there's a pool of skilled human players of the imitation game.
I don't think IQ is a good measure for intelligence at all. Neither dolphins or octopuses can solve IQ tests.
Their input and output interfaces are too different from human's and they're not nearly as smart to take our IQ tests, but both dolphins and octopuses can solve complex puzzles tailored for their environment. Those puzzles are the whole reason scientists know that dolphins and octopuses are more intelligent than other animals.
But we do know they're "intelligent" and also smart in an important capacity. So how gives we don't measure them by IQ? Because the IQ is not a good measure of intelligence or smarts.
> Because the IQ is
No, it is just because they have difficulties at the bench.
> how gives we don't measure them by
We'd measure them by all the tests available. Not all test are usable in all circumstances.
> No, it is just because they have difficulties at the bench.
I'll put it in another way. A "gifted kid" can be measured incredibly well on an IQ test, but fail miserably at incredibly normal but very difficult tasks such as consoling someone for their loss and managing family crisis. This is a clear example where an IQ measure doesn't translate to a person being capable of meaningfully changing their environments for good which is one way we define intelligence.
On the other hand saying "the gifted person is highly intelligent/smart just not good at some things" really diminishes the other tasks, because they really are very difficult tasks but are not measured by an IQ test.
We have always been very aware that IQ does not measure all skills - nonetheless, it does measure one.
Nobody says that the IQ test would "measure intelligence". We know it does test a form of it.
I said it's a bad measure of intelligence and it seems that we agree.
There's currently a big market for figuring out ways to measure intelligence. With a particular interest in ways that humans can score much higher than LLMs. If you have some ideas please do share!
I think children having learning abilities exceeding LLM test-time learning (currently only happens in-context). But it's unethical to determine the true baseline of a child age 6 spending 6 years learning a radically new skill to mastery--and besides if you apply RL pressure to the AIs it would be able to surpass it. I guess I still believe future AIs should have some form of continual learning at test-time.
Why? Seems like benchmarks that closely mirror the tasks you'd want an LLM to help with would be a lot more useful than some general intelligence benchmark.
Give away access to the model and go ask people from time to time if the model was of use to the person and if they were able to make the model work with them.
I am no where close to qualified to do that. Hell, experts can't even define what intelligence is, much less define a test for it
This is like arguing about whether a hot dog is a sandwich (of course it is) or whether the chicken or the egg was first (obviously the egg since all chickens come from eggs). Intelligence is just problem solving in the context of self-awareness. Machines don't have it and never will but they can simulate the process given inputs. You can argue whether humans and animals truly possess self-awareness and in what degree, but the definition of intelligence is as simple as the hot dog debate.
It was defined in Animal Intelligence by George John Ramones in 1882 as "intelligence is the capacity to do the right thing at the right time. It is the ability to respond to the opportunities and challenges presented by a context"
I'm also unclear as to how basic inferential logic puzzles spells out intelligence
I think if you summed up measures of intelligence as 'can it do basic symbolic logic in a chain with memory' then yes, you've now achieved the intelligence of an e. coli colony [0], congratulations
[0] https://journals.aps.org/prx/abstract/10.1103/PhysRevX.10.03...
> basic inferential logic puzzles spells out
It spells out a form of intelligence - some can and some cannot.
Those puzzles are an abstraction of a skill which is thought to be exportable in other domains.
so give it an IQ test and call it AGI. these weird little puzzles are grounded in no research with no replication or mechanistic chain to practical use
You should read more on the ARC prize, it actually has a pretty long history. We're on the 3rd iteration because they keep getting saturated. If you look at the score history over time on ARC AGI 1, 2 and 3 it's pretty impressive.
https://arcprize.org/
No, but figuring out that you're playing a snake-like puzzle game at all in an extremely general input domain and then solving it in the least number of moves definitely feels like evidence of intelligence.
You forget the benchmark. The human subjects were told they were being timed. If you believe the lowest time is the primary metric you will absolutely trial and error at speed instead of meticulously plan out your moves to minimize that metric.
LLMs are not timed and given that it costs tens of thousands of dollars to run this test they're not optimizing for speed.
So you've got a deceptive test, with one metric being told to humans and not applied to LLM and a hidden metric humans aren't aware of but LLMs are as the test.
This is flawed from the get go. It almost seems like this was deliberately setup to be able to claim AGI and superiority of LLMs
> LLMs are not timed
Not fully relevant: timing is crucial in all-pass tests, not crucial in pass-or-fail tests. I.e.: first of all, they have to be able to reach the goal, and that is already an achievement. Then - and in parallel - the problem solving must also be optimized for efficiency. But "solving" and "efficiency" are non coincident dimensions.
1.5 years ago Gemini Pro 2.5 needed 1 page of thinking for every move in tic-tac-toe.
Playing tic-tac-toe or snake does not imply AGI, but is required to claim AGI.
If you have never seen the game before probably.
[dead]