$360 per puzzle. When they tested people it took about 10 minutes per puzzle. If price/performance keeps falling at the same rate it has been, this will cost less than US minimum wage humans within two years. Three for Phillipines minimum wage.
Was OpenAI able to run ARC-AGI-3 tests previously so that they could build a custom harness for the specific tests in the set? Even with the standard harness, if they knew the problems ahead of them they could have used supervised reinforcement learning to teach the model how to solve these specific tests.
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.
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.
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.
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!
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"
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.
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
"For a cost comparison, during our controlled testing, human participants were paid $115 per 90-minute session, plus $5 per game completed. Participants attempted approximately nine games per session, roughly $12.78 per attempted game before bonuses.
Most of this fee pays for the participant’s time and willingness to take the test, rather than the energy their brain uses (a closer proxy to compare with AI). If we look at only the brain’s energy, and price it as electricity, the estimate drops to about 0.6 cents per session, or 0.067 cents per game attempted."
Well I dont know about all of you, but I am celebrating meat based humans...
I think raw brain energy is not a fair comparison. Humans are not willing and able to serve requests at identical competence all hours of the day. You have to invest considerable resources to get a person to even do so for part of the day.
“AGI” never made sense to me. It’s a purely marketing term right?
I’ve ignored it thinking it would go away, but it keeps coming up.
I get that consciousness differs from intelligence and that our waking awareness of life is a complete mystery.
Knowledge and thus intelligence however I consider as actively being solved by these large ML models. That is, with the right combination of machinery and know-how, you’ll get it.
But you’d be no nearer to solving consciousness.
Given this thought trajectory - what is AGI supposed to be?
Not sure why you are bringing up consciousness, that’s largely orthogonal to intelligence. AGI is usually taken to mean the capability to match or surpass human intelligence across all conceivable cognitive tasks, as opposed to being limited to certain kinds of tasks, or to not matching the general level of human intelligence in some respect.
Intelligence, and hence AGI, doesn’t require consciousness or emotions or sentience.
I like recursive self improvement instead. It seems like something that is actually quantifiable and kinda “the point” of why consciousness is important to humans.
So basically, being able to set it free on some long running goal and it sort of “lives” and autonomously does its own tasks?
I wonder at what point consciousness is necessary… that is, if you can have anything like that without it.
To the point that solving consciousness (and combining it with intelligence) is what gives you the autonomous, recursive, self-improving thing otherwise it can only drive in the dark and make big mistakes.
To your point I think - it’s why we don’t see too many non-conscious advanced biology (it rarely survives against those with it).
> Astra’s progress helps clarify which AI capabilities are out of reach and which questions remain open.
Okay. But I don't think this entire article at all explained which AI capabilities remain out of reach. Did I miss something? Other than "oh I guess it could still get even more superhuman on ARC-AGI-3 than it is?"
Since low scored much lower than none, and none scored ~ around medium, could none default to medium in the API? I don't think the new models can even have "instant" via API, unless they train them for that (there was one gpt5 variant called instant or something).
Doesn't "saturated" mean that essentially there won't be any more progress in the benchmarch? Also of note is that two of your points only mean something on an occidental capitalist system.
Perhaps, but I think a bigger problem than lack of compute is the cost of rewards. Games like Chess and Go were solved long before self-driving, partly because it's incredibly cheap to acquire the reward of a bad board game decision, relatively to how expensive it is to acquire the cost of a bad driving decision. With driving, acquiring the reward can cost you $20/hr for human supervisors to generate disengagements, or $100k if you crash, or $30B if you crash the car into a person in a way that causes your company to collapse (e.g., Cruise).
yeah but I think you may be underestimating the amount of capital available for compute. if AGI is possible through some 5 trillion of expenditure on computers, there will be money for it.
also, you are underestimating how short a 10 year time frame is. we are close to self driving, the first neural net image model was in 2013. 13 years is a blink of an eye
So, you’re telling me I need to start a benchmark as a side gig to get a bunch of free compute.
Astra please create a benchmark that’s favorable to your reasoning skills with a human interface but don’t make the score too attainable add some small issues that keep you below 100% to look sensible and to keep my evaluation metric side gig going.
99.9% with the right harness? Ok, we're at AGI then.
Prediction:
We will now see the goalposts moved towards "well, a human costs less / is more efficient" - that will prevail for a few months until they come up with some other test that humans can do easily but is hard for the bots. This cycle will continue for ever and in 25 years, despite having hyper intelligent embodied robots or whatever, we'll still be arguing about if the singularity is here and if we're at AGI for the rest of my life most likely.
TLDR: The official ARC harness throws away old context and reasoning. No real-world harness is this bad, the model has to re-learn the game repeatedly. OpenAI basically just added standard compaction. Their harness is still "general".
I agree, like the average human isn't generally intelligent.
IMO, AGI is literally no different from ASI, though people think it is. Like, Imagine you have 1,000 generally intelligent humans working for you (which nobody is really) and you were to point them at your pet project. That would be amazing!
It’s not that different than a lot of real world economies. Often paying for someone or something with better quality can reduce total costs. You have less failures, less mistakes, so on, so while the expertise or quality of the product is higher than cheaper solutions, they can be more reliable and over time ultimately cheaper.
The question I have is how far back that curve can go without relying on economies of scale to just drag all the points back to the left. And without overfitting a specific metric that I don’t need (like this test).
Yep. In particular, ARC-AGI-3 is a series of games where if you fail, you keep trying again (until eventually hitting a timeout). So the sooner you succeed, the sooner you stop spending tokens retrying. If it was a benchmark where everyone got one attempt with no retries, you wouldn't see it bend backward.
Wake me when it's going to spontaneously fix my leaky faucet because if it doesn't do it nobody else will. Until it has that capability I don't really care.
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.
It was a useful lesson that whatever IQ tests measure, it is completely devoid of value or interest to me.
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.
"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
(Please forgive the flippant response. I believe it cuts to the core of what the parent was intending.)
Let LLM control a physical robot to perform tasks that average human can do.
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.
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.
https://arcprize.org/
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.
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...
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.
Playing tic-tac-toe or snake does not imply AGI, but is required to claim AGI.
Most of this fee pays for the participant’s time and willingness to take the test, rather than the energy their brain uses (a closer proxy to compare with AI). If we look at only the brain’s energy, and price it as electricity, the estimate drops to about 0.6 cents per session, or 0.067 cents per game attempted."
Well I dont know about all of you, but I am celebrating meat based humans...
I’ve ignored it thinking it would go away, but it keeps coming up.
I get that consciousness differs from intelligence and that our waking awareness of life is a complete mystery.
Knowledge and thus intelligence however I consider as actively being solved by these large ML models. That is, with the right combination of machinery and know-how, you’ll get it.
But you’d be no nearer to solving consciousness.
Given this thought trajectory - what is AGI supposed to be?
Intelligence, and hence AGI, doesn’t require consciousness or emotions or sentience.
What human intelligence do you mean? Genius? Professional? Educated? Random person? “Dumb” person?
"highly autonomous systems that outperform humans at most economically valuable work"
https://time.com/article/2026/08/26/openai-sam-altman-interv...
I wonder at what point consciousness is necessary… that is, if you can have anything like that without it.
To the point that solving consciousness (and combining it with intelligence) is what gives you the autonomous, recursive, self-improving thing otherwise it can only drive in the dark and make big mistakes.
To your point I think - it’s why we don’t see too many non-conscious advanced biology (it rarely survives against those with it).
Okay. But I don't think this entire article at all explained which AI capabilities remain out of reach. Did I miss something? Other than "oh I guess it could still get even more superhuman on ARC-AGI-3 than it is?"
Examples:
- predict a coinflip: easy to verify, hard to learn
- earn $100: easy to verify, hard to learn
- increase paid subscriptions in an A/B test: easy to verify, hard to learn
I won't get into it, but there are many properties beyond verifiability that are needed to saturate a benchmark.
- earn $100: easy to verify, hard to learn
- increase paid subscriptions in an A/B test: easy to verify, hard to learn
but we both know these examples go against the spirit of my point
also, you are underestimating how short a 10 year time frame is. we are close to self driving, the first neural net image model was in 2013. 13 years is a blink of an eye
Give a number in the replies to this comment and we will check the answers when AGI is here (if so...)
Astra please create a benchmark that’s favorable to your reasoning skills with a human interface but don’t make the score too attainable add some small issues that keep you below 100% to look sensible and to keep my evaluation metric side gig going.
Alignment++
Prediction:
We will now see the goalposts moved towards "well, a human costs less / is more efficient" - that will prevail for a few months until they come up with some other test that humans can do easily but is hard for the bots. This cycle will continue for ever and in 25 years, despite having hyper intelligent embodied robots or whatever, we'll still be arguing about if the singularity is here and if we're at AGI for the rest of my life most likely.
TLDR: The official ARC harness throws away old context and reasoning. No real-world harness is this bad, the model has to re-learn the game repeatedly. OpenAI basically just added standard compaction. Their harness is still "general".
https://www.lisep.org/tru
(I have not gone down the rabbit hole to understand how they achieve that 24% number)
IMO, AGI is literally no different from ASI, though people think it is. Like, Imagine you have 1,000 generally intelligent humans working for you (which nobody is really) and you were to point them at your pet project. That would be amazing!
It's already happening :)
The question I have is how far back that curve can go without relying on economies of scale to just drag all the points back to the left. And without overfitting a specific metric that I don’t need (like this test).