> Generation: producing outputs such as text, speech and actions
> Attention: focusing cognitive resources on what matters
> Learning: acquiring new knowledge through experience and instruction
> Memory: storing and retrieving information over time
> Reasoning: drawing valid conclusions through logical inference
> Metacognition: knowledge and monitoring of one's own cognitive processes
> Executive functions: planning, inhibition and cognitive flexibility
> Problem solving: finding effective solutions to domain-specific problems
> Social cognition: processing and interpreting social information and responding appropriately in social situations
--------------------
I prefer:
a) working memory (hold & manipulate information in mind simultaneously)
b) processing speed (how quickly & efficiently execute basic cognitive operations, leaving more resources for complex tasks)
c) fluid intelligence (ability to reason through novel problems without relying on prior knowledge)
d) crystallized intelligence (accumulated knowledge and ability to apply learned skills)
e) attentional control / executive function (focus, suppress irrelevant information, switch between tasks, inhibit impulsive responses)
f) long-term memory and retrieval (ability to form strong associations and retrieve them fluently)
g) spatial / visuospatial reasoning (mental rotation, visualization, navigating abstract spatial relationships)
h) pattern recognition & inductive reasoning (this is the most primitive and universal expression of intelligence across species, the ability to extract regularities from noisy data, to generalized from examples to rules)
What counts as 'in mind' is undefined. You can succeed by declaring anything manipulatable counts as in.
>c) fluid intelligence (ability to reason through novel problems without relying on prior knowledge)
reasoning presupposes the conclusion. Solve is better. When a solution is given you cannot declare it to be not a solution. People can and do argue about if a answer was arrived at by reasoning even when they agree on the correctness.
>g) spatial / visuospatial reasoning (mental rotation, visualization, navigating abstract spatial relationships)
I have aphantasia, why should you exclude something from being intelligent because it cannot do something that I also cannot do.
How will they measure wisdom or common sense (ability to make an exception)?
To be clear, I think we've seen very fast progress, certainly faster than I would have expected, I'm not trying to peddle some "wall" rhetoric here, but I struggle to see how this isn't just the SWE-bench du jour.
I feel like an average human wouldn't pass some of these metrics yet they are "generally intelligent". On the other hand they also wouldn't pass a lot of the expert questions that AI is good at.
We're measuring something, and I think optimizing it is useful, I'd even say it is "intelligent" in some ways, but it doesn't seem "intelligent" in the same way that humans are.
However I must admit that including the last point that is partially hinting at the emotional or rather social intelligence surprised me. It makes this list go beyond usual understanding of AGI and moves it toward something like AGI-we-actually-want. But for that purpose this last point isn't ok narrow, too specific. And so is the whole list.
To be actually useful the AGI-we-actually-want benchmark should not only include positive indicators but also a list of unwanted behaviors to ensure this thing that used to be called alignment I guess.
Stalin was AGI-level.
Is social cognition really a measure of intelligence for non-social entities?
Who cares about AGI? Honestlky what's the gain.
Maybe Google could actually make Gemini good instead of being about 10 miles behind Claude instead of trying to make AGI because of - well some reason - cause they want to be famous.
What does "making a framework" even mean, it feels like a nothing post.
When I think of what real AGI would be I think:
- Passes the turing test
- Writes a New York Times Bestseller without revealing it was written by AI
- Writes journal articles that pass peer review
- Wins a Nobel Prize
- Writes a successful comedy routine
- Creates a new invention
And no, nobody is going to make an automated kaggle benchmark to verify these. Which is fine, because an LLM will never be AGI. An LLM can't even learn mid-conversation.
If an LLM like this is really intelligent, at the very least, I’d expect it to be able to invent.
For example, train an LLM on a dataset only containing knowledge from before nuclear energy was invented, and see if it can invent nuclear energy.
But that’s the problem: they’re not really training the model on intelligence, they’re training it on knowledge. So if you strip away the knowledge, you’re left with almost nothing.
That's not what's happening here, and it's worth remembering: A caveman from 200K years ago would have been just as intelligent as any of us here today, despite not having language or technology, or any knowledge.
In Carolyn Porco's words: "These beings, with soaring imagination, eventually flung themselves and their machines into interplanetary space."
When you think of it that way, it should be obvious that LLMs are not AGI. And that's OK! They're a remarkable piece of technology anyway! It turns out that LLMs are actually good enough for a lot of use cases that would otherwise have required human intelligence.
And I echo ArekDymalski's sentiment that it's good to have benchmarks to structure the discussions around the "intelligence level" of LLMs. That _is_ useful, and the more progress we make, the better. But we're not on the way to AGI.
It's interesting to me how much effort the AI companies (and bloggers) put into claiming they can do things they can't, when there's almost an unlimited list of things they actually can do.
Claiming they can give safe, regulated financial advice. [2]
Claiming you can put your whole operation on autopilot with minimal oversight and no negative consequences. [3]
[1] https://www.ftc.gov/news-events/news/press-releases/2024/09/...
[2] https://www.businessinsider.com/generative-ai-exaggeration-o...
[3] https://www.answerconnect.com/blog/business-tips/ai-customer...
They had ridiculous demos of Devin e.g. working as a freelancer and supposedly earning money from it.
What they can't they do? Pretty much anything reliably or unsupervised. But then again, who can?
They also tend to fail creatively, given their synthesize existing ideas. And with things involving physical intuition. And tasks involving meta-knowlege of their tokens (like asking them how long a given word is). And they tend to yap too much for my liking (perhaps this could be fixed with an additional thinking stage to increase terseness before reporting to the user)
In other words, intelligence offers zero evolutionary advantage?
With everything wrong and sick with today's world, let's not take the achievements of our species for granted.
In that sense, we have just enough collective intelligence to be dangerous and not enough intelligence to moderate ourselves, which may very well result in an evolutionary deadend that has caused untold damage to life on Earth.
Doubt. If we would teleport cavemen babies right out of the womb to our times, I don't think they'd turn into high IQ individuals. People knowledgeable on human history / human evolution might now the correct answer.
We all come from monke, monkey from 10 million years ago would definitely be unable to even learn spoken language at a basic level. Would he even have the anatomy to produce the required sounds? I don't think so.
What about monke from 1 million years ago? 200 thousand years ago?
ChatGpt says spoken language only emerged 50k - 200k years ago and that a cavemen baby from 200k years ago could learn spoken language if brought up by modern parents.
But I prefer human answers over AI slop.
Nowadays humans have smaller brains on average, though that is almost certainly not correlated with a lower skill in computer programming, but with lower skills in the techniques that one needed to survive as a hunter of big animals.
A human being has the potential for intelligence. For that to get realized, you need circumstances, you need culture aka "societal" software and the resources to suspend the grind of work in formative years and allow for the speed-running of the process of knowledge preloading before the brain gets stable.
The parents then must support this endeavor under sacrifices.
There is also a ton of chicken-egg catch22s buried in this whole thing.
If the society is not rich then no school, instead childlabour. If child-labour society is pre-industrial ineffective and thus, no riches to support and redistribute.
Also is your societies culture root-hardened. Means - on a collapse of complexity in bad times, can it recover even powering through the usual "redistribute the nuts and bolts from the bakery" sentiments rampant in bad times. Can it stay organize and organize centralizing of funds for new endeavors. Organizing a sailing ship in a medieval society, means in every village 1 person starves to death. Can your society accomplish that without riots?
Thus.
Were we "human" 200.000 years ago the way we are now?
Was the required brain and vocal hardware present?
>That's not what's happening here ...
On the contrary, it very much is. We're in the early phases of the singularity now.
I'd argue AGI is already achieved via LLMs today, provided they've excellent supporting cognitive infrastructure.
However, the gap from AGI to ASI is perhaps longer than anticipated such that we're not seeing a hard takeoff immediately after achieving AGI.
Just, you know, impending mass unemployment on a scale never seen before. When you frame it that way, whether LLMs qualify as AGI is largely semantics.
That said, I really hope you're right and I'm wrong.
It's pretty easy for these people to pull something like this out of their collective asses, but it's much harder (maybe impossible) to rigorously define the how and why.
Hear me out.
I love AI and have been using it since ChatGPT 3.5. The obvious question when I first used it was "does this qualify as sentience?" The answer is less obvious. Over the next 3 years we saw EXPONENTIAL intelligence gains where intelligence has now become a commodity, yet we are still unable to determine what qualifies as "AGI".
My thoughts: As humans, we possess our own internal drive and our own perspective. Think of humans as distilled intelligence, we each have our own specialty and motivations. Einstein was a genius physicist but you wouldn't ask him for his expertise on medicine.
What people are describing as AGI is essentially a godlike human. What would make more sense is if the AGI spawned a "distilled" version with a focused agenda/motivation to behave autonomously. But even then, there are limitations. What is the solution? A trillion tokens of system prompt to act as the "soul"/consciousness of this AI agent?
This goes back to my original statement, what is missing is a level of consciousness. Unless this AGI can power itself and somehow the universe recognizes its complexity and existence and bestows it with consciousness I don't think this is phsyically attainable.
A follow up is maybe this is a feature not a bug: Do we want AI to have its own intrinsic goals, motivations, and desires, i.e. conciousness
Im imagining having to ask ChatGPT how its day was and respect its emotions before I can ask it about what I want.
Scaling LLMs will not lead to AGI.
LLMs are already pretty general. They've got the multimodal ones, and aren't they using some sort of language-action-model to drive cars now? Who is to say AGI doesn't already exist?
At some point you have to throw in the towel when these things are going to be walking and talking around us. Some people move the goalposts of "AGI" to mean that the machine totally emulates a person. Including curiosity and creativity, of which these models are currently lacking.
wcgan7•1h ago
quantummagic•1h ago
Schlagbohrer•1h ago
(and I wonder what my ADHD friends would think of the Executive Function requirement as well...)
beeflet•13m ago
In the same way that studying alien life would reveal more about how life in general canonicially forms and exists. Studying this artificial intellegence could unlock a new understanding of our own minds.