The ARC Prize organization designs benchmarks which are specifically crafted to demonstrate tasks that humans complete easily, but are difficult for AIs like LLMs, “Reasoning” models, and Agentic frameworks.
ARC-AGI-3 is the first fully interactive benchmark in the ARC-AGI series. ARC-AGI-3 represents hundreds of original turn-based environments, each handcrafted by a team of human game designers. There are no instructions, no rules, and no stated goals. To succeed, an AI agent must explore each environment on its own, figure out how it works, discover what winning looks like, and carry what it learns forward across increasingly difficult levels.
Previous ARC-AGI benchmarks predicted and tracked major AI breakthroughs, from reasoning models to coding agents. ARC-AGI-3 points to what’s next: the gap between AI that can follow instructions and AI that can genuinely explore, learn, and adapt in unfamiliar situations.
You can try the tasks yourself here: https://arcprize.org/arc-agi/3
Here is the current leaderboard for ARC-AGI 3, using state of the art models
- OpenAI GPT-5.4 High - 0.3% success rate at $5.2K
- Google Gemini 3.1 Pro - 0.2% success rate at $2.2K
- Anthropic Opus 4.6 Max - 0.2% success rate at $8.9K
- xAI Grok 4.20 Reasoning - 0.0% success rate $3.8K.
(Logarithmic cost on the horizontal axis. Note that the vertical scale goes from 0% to 3% in this graph. If human scores were included, they would be at 100%, at the cost of approximately $250.)
https://arcprize.org/leaderboard
Technical report: https://arcprize.org/media/ARC_AGI_3_Technical_Report.pdf
In order for an environment to be included in ARC-AGI-3, it needs to pass the minimum “easy for humans” threshold. Each environment was attempted by 10 people. Only environments that could be fully solved by at least two human participants (independently) were considered for inclusion in the public, semi-private and fully-private sets. Many environments were solved by six or more people. As a reminder, an environment is considered solved only if the test taker was able to complete all levels, upon seeing the environment for the very first time. As such, all ARC-AGI-3 environments are verified to be 100% solvable by humans with no prior task-specific training
As a psychiatrist, I have a theory about what’s missing in AI. First, it lacks childhood dependency and attachments. Second, it struggles to overcome repeated pain and suffering. Third, it lacks regular eating and restroom breaks. Fourth, it struggles to accept loss in everyday situations. Finally, it lacks the concept of our inevitable death. Without these nagging memories and concepts, machines will simply revert to the simpler concepts we use them for in our recent times, such as stealing cryptocurrency. After all, we live in a world run by capitalism, so it’s only logical. ¯\(ツ)/¯
Here is a way of describing what I see as ‘the problem’:
An LLM cannot forget things in its base training data set.
Its permanent memory… is totally permanent.
And this memory has a bunch of wrong ideas, a bunch of nonsensical associations, a bunch of false facts, a bunch of meaningless gibberish.
It has no way of evaluating its own knowledge set for consistency, coherence, and stability.
It literally cannot learn and grow, because it cannot realize why it made mistakes, it cannot discard or ammend in a permanent way, concepts that are incoherent, faulty ways of reasoning (associating) things.
Seriously, ask an LLM a trick question, then tell it it was wrong, explain the correct answer, then ask it to determine why it was wrong.
Then give it another similar category of trick question, but that is specifically different, repeat.
The closer you try to get it toward reworking a fundamental axiom it holds to that is flawed, the closer it gets to responding in totally paradoxical, illogical gibberish, or just stuck in some kind of repetetive loop.
… Learning is as much building new ideas and experiences, as it is reevaluating your old ideas and experiences, and discarding concepts that are wrong or insufficient.
Biological brains have neuroplasticity.
So far, silicon ones do not.
As a technologist, I have to remind everyone that AI is not intelligence. It’s a word prediction/statistical machine. It’s guessing at a surprisingly good rate what words follow the words before it.
It’s math. All the way down.
We as humans have simply taken these words and have said that it is “intelligence”.
Few of countless dictionary definitions for intelligence:
There isn’t even concensus on what intelligence actually means yet here you are declaring “AI is not intelligence” what ever that even means.
Artificial Intelligence is a term in computer science that describes a system that’s able to perform any task that would normally require human intelligence. Atari chess engine is an intelligent system. It’s narrowly intelligent as opposed to humans that are generally intelligent but it’s intelligent nevertheless.
As a therapist, I can tell you the only thing holding LLMs back from true intelligence is having to pee and poop. Peeing and pooping is the foundation of all higher level operations. I poured water on my PC and the LLM I was running said “I think” right before committing suicide
I was arguing against it being an intelligence because it lacked the suffering and past experiences that define intelligence. Without pain and suffering, what are we? Not for it being intelligent.
I think you’re conflating intelligence and consciousness. Pain and suffering requires consciousness but intelligence does not imply pain or suffering or happiness. LLMs are already “intelligent” to a certain degree in some aspects, though not generally intelligent like humans. But there is no reason to believe that you couldn’t have a generally intelligent artificial agent that lacks consciousness and thus can feel no pain or suffering.
As another technologist, I have to remind everyone that unless you subscribe to some rather fringe theories, humans are also based on standard physics.
Which is math. All the way down.
As a philosopher, I have to remind you that humans invented math and physics to model reality.
Humans are not based on physics or math. That would be like saying the earth is based on a globe.
As a mathematician, it should be noted that the mathematics of physics aren’t laws of the universe, they are models of the laws of the universe. They’re useful for understanding and predicting, but are purely descriptive, not prescriptive. And as they say, all models are wrong, but some are useful
As a random person on the Internet I don’t actually have anything to add but felt it would be nice to jump in.
That’s true, but that doesn’t contradict the above comment. Unless you believe in something like a spirit or soul, you must concede that human intelligence ultimately arises from physical matter (whatever your model of physics is). From what we know of science right now, there are no direct reasons for thinking that true intelligence or even consciousness is limited to biological organisms based on carbon and could not arise in silicon.
It could also be that it lacks the machinery to feel any emotions at all. You don’t (normally) have to train people to be afraid of bears or heights or loneliness or boredom. You also don’t (normally) have to train people to have empathy or compassion.
I argue that our obsession with AI is, itself, a misalignment with our environment; it disproportionately tickles psychological reward centers which evolved under unrecognizably different circumstances.
So what are you implying about people who don’t experience these?
What am I implying? That their machinery is abnormal and they likely need assistance to live normal, healthy lives. That’s literally why the fields of psychiatry and psychology exist: healthy people don’t need doctors and therapists. Do you disagree?
Introverts exist, and are… very often fine with solitude, prefer it generally over socializing.
But they are generally fine at participating in society and living normal lives.
Healthy people… do need doctors … and therapists.
A person can outwardly appear to be healthy… and actually not be.
Preventative medicine, regular checkups, your body changes as you grow, and habits you develop in your youth may need significant reworking.
Therapy can give otherwise healthy people a method of exploring their inner selves more fully or more consistently… they can teach them frameworks for understanding and dealing with other kinds of people, for being better able to deal with kinds of trauma they have not yet experienced.
Also… same with physical health… people with some nascent mental problems or patterns forming… probably won’t be obvious to a non specialist, untill it gets more severe.
Definitely! I am one :) but I still desire the presence of friends from time to time (and usually in small groups).
Yup! There’s always a nonzero chance you’re not as healthy as you think you are (let’s call it the quantum theory of health: everyone is in a superposition of being both healthy and unhealthy at the same time), especially as we change due to age, making us unfamiliar with our own bodies… I’d tell you about my own challenges here, but that’d be TMI.
And, yes, that’s why we go to regular checkups with someone who has a better perspective to judge “healthiness” (side note: doctors aren’t perfect, so visiting them too frequently can be worse than never at all; there’s a “healthy” cadence to checkups).
This boils down to the definition of “healthy”. It even becomes a philosophical question that’s really hard to answer… Is it healthy to live a sedentary lifestyle? Is it healthy to exercise too much? Is it healthy to not know TIPP, in case you (or a loved one) gets a panic attack? Is it healthy to ignore yourself? Ignore others? Is it healthy to mention quantum superposition in a conversation about health? ;)
But, yes, I agree. Life’s as messy and diverse and as hard to sum up as everybody whose ever lived, but yet we carry on … I hope that’s healthy.
Edit: typo, and missing a hint that I’m making a joke about me over-generalizing physics concepts
My entire point is that you are just overgeneralizing, in general, and saying rather silly things.
Fair enough; the Internet is a silly place full of distracted, armchair philosophers. However, my entire point was that an LLM doesn’t rely on machinery in the same way that a human brain does. That doesn’t make AI “worse” or “better” overall, but it does make it an awful replacement for humans.