Comment by zug_zug

11 hours ago

> I'd be curious to hear takes on what would make you think Astra is yet to be AGI, and what would still need to be achieved for this to effectively be AGI from this point forward.

To me AGI is all about the "G" general (we already had the AI part). General meaning universal, everything. It's not a function of knowledge or specific hardcoded tests, it's that you could give it a test it's never heard of before and never been trained on and it would ace it (it might need a lot of time).

Currently LLMs can't even really learn within a conversation, they can add a note to context and try to not drop it. Example things an AI cannot do yet (but maybe someday will):

- write a well-received book, write a best-seller

- come up with a new company idea, Run that company

- actually have a decent conversation, maybe someday talk somebody out of suicide effectively

- come up with its own ideas or theories that nobody else has presented

- understand the stock market well enough to trade better than an index fund

- be an expert Game Master in a TTRPG (making no mistakes, getting a read on the players' fantasies, calibrating difficulty in response to emotions)

- come up with a theory of what makes games fun, make a popular game

- be able to sort through research and come to conclusions on complex geopolitical/sociological topics (e.g. theorize on whether AGI will result in mass poverty or mass abundance and be able to argue persuasively)

- be able to articulate what it knows, what it doesn't know, and what information it would need to have to answer complex queries

- exhibit metacognition (thinking about its own thinking) and self-optimization

- wonder about things

- observe contradictions and ironies in the social-consciousness, do a standup routine that makes you rethink how you look at things

To me all this makes the label of AGI completely meaningless.

What AGI has always meant (eg. in 2019) is Artifical General Intelligence.

Artificial -- something made by humans instead of occurring naturally

General -- not confined by specialization or careful limitation

Intelligence -- the capacity to learn, reason, solve problems, think abstractly, and adapt to new situations

Basically, the metric was that any healthy adult human on the planet represents a general intelligence. This has certainly long been reached.

Also some of the stuff you're listing has long been solved as well, such as listing what it knows and what it doesn't know, and what information it would need. Other is just poorly defined: "be able to argue persuasively". AI can certainly write an argument on almost any topic that would pass any University homework in 2019.

By this definition, even most humans would not qualify as having AGI though.

  • However most humans can do at least some of the things given they spend the required effort.

    Some problems presented needs a very large context and some are not much solvable (e.g. trading) since market responds to traders' actions, as well, making it effectively an oracle problem (of computation).

    On the other hand, we must be aware that these models are static, and they indeed stop when nobody asks something or requests an action from them. However, brains in nature never stops. Wonder, daydream, sleep, self-evolve, clean up and eliminate memories and views and much more.

    • But this is assuming the model is the entire story. The original comment you were replying to pointed out that the harness is just as important.

      The hardware of human intelligence is not a singular thing that is uniform throughout. You cannot take the prefrontal cortex white matter out of someone's head and say you are holding a person. Much of the parts of our brains that enable much of our intelligence, is made of different specialized stuff. The visual cortex and sensorimotor regions aren't only there for input and output, they are used by the more thinky parts of the brain to do visualization and spatial reasoning. The cerebellum contains billions of neurons making little oscillator circuits and PID-like self-regulation machines that help make muscles do what they're supposed to, but also provide attention and time perception.

      Heck, our brains contain language models, that train themselves up based on a glut of data over a span of about 10 years, and then they become more or less set in stone for the rest of our lives. Of course we can learn languages, but the "Critical Period" is a very real thing that produces a permanent architecture for some grammatical structures, or things like the ability to partition a lexicon by gender for faster lexical access which cannot be learned as an adult if your native language did not have gender.

      I'm not trying to make a direct analogy, the point is that the language model doesn't need to be fully "generally intelligent" all on its own for there to exist a general intelligence, because the language model can be part of a generally intelligent system, which can do things like form, recall, and manage memories which are by now a standard feature in basically every chatbot.

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    • > On the other hand, we must be aware that these models are static, and they indeed stop when nobody asks something or requests an action from them

      The parent commenter noted:

      "if a harness alone can help the LLM saturate the benchmark with a near perfect score then the combination of the two must still be effectively AGI"

      Harnesses absolutely can enable models to continue thinking about things. And LLMs do wonder and explore weird ideas like daydreams when you allow them to do this.

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  • I'm guessing their defn of AGI is something like the sum total of all humans' abilities? Still though some of those tasks (e.g. beat an index fund) may very well be impossible, and worse yet a lot of those tasks are not coherently defined.

  • AGI has always been expected to outperform humans or else what is the point of it?

    • The point is replacing humans, and for that it only has to equal them at lower cost (including factors like not needing sleep and being easily clonable). The outperformance lies in the cost savings, not necessarily in the intelligence.

Your examples are things that most humans cannot do, or things that AI can already do. For example most humans, even most intelligent humans, could not write a well-received book, run a successful company, or make a popular game. On the other hand, AI can absolutely sort through research, draw conclusions on complex topics, and argue them persuasively. Likewise, I don't know what you mean by a "decent" conversation, but millions of people converse with chatbots daily, so I don't know why you say AI fails to meet that bar.

  • I fail to see how what you describe is any better than the old autocomplete-on-steroids comparison. Could the human mind learn to spell every word properly? Yes. Do most (or any) do it? No. Does that mean a human can't?

    I think what OP was drawing a comparison to is that AI right now could not come up with an award winning novel from the spark of some creative notion and working up from there, as opposed to just mashing together what has already been done and calling it a day.

    • > AI right now could not come up with an award winning novel from the spark of some creative notion

      I agree, but in this field we value evidence. So there needs to be some test of novel-writing abilities.

      Once there is, AI companies will be out to score highly on it.

      Wait for a resurgence of Philip K Dick-style novels as humans desperately try to write things LLMs cannot.

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It also cannot do tasks it wasn't trained for. It can extend texts, read images and click on a desktop, but only because it's made for that.

  • I don't think that's strictly true, as I can give it a new gui or tui program it wasn't trained on and it will learn it. Unless you're talking about general abilities like sight, but the same is somewhat true of humans.

    • If you consider the data on which an LLM was trained on to be points on a very highly multidimensional object, the claim is that the LLM can interpolate a convex hull spanned by those points, therefore recovering a subset of consequences attainable from those points. Obviously this hull includes completely novel points that were not present in the initial data set, so the output of the LLM goes beyond its initial training. And yet, there are clearly points outside a convex hull spanned by any finite number of points, such that we can imagine not all possible outputs are attainable using this method.

      The claim is furthermore that truly original thinking, the infamous leaps in understanding and creativity, happen by attaining points outside such a convex hull.

      It's hard to rigorously verify or disprove this claim. Hopefully this helps build an intuition of why the claim is not as shallow and obviously wrong as it may seem initially.

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    • This makes me realize there is a higher bar we need to achieve with AI still. The ability for the model to evolve through interactions more on a hourly or daily basis. The models are accelerating but inference doesn’t modify the model.

Most of humans don’t reach any of these levels.

  • But you have to acknowledge how uneven the playing field is. The AI has read every book that's ever been written, and can spend hours of compute time in a few seconds.

    I think if a person had those same advantages (e.g. could spend 5 hours thinking about what to say next) we could all hold outstanding conversations, or if we had read every book ever written I think many of us could write a very popular book, if we could read every singe company's P&L statement in a few seconds we could invest better than an index fund.

    What I'm pointing out here is that these models appear to be intelligent when they really are simply unimagineably knowledgeable. When you drop the time-constraints it starts to become more and more apparent that human intelligence scales better with time than AI does (much in the same way AI can burp out tons of code but make your codebase entirely illegible within a matter of months).

    Perhaps to simplify: my notion of intelligence is how much can you deduce with a constant set of starting context

    • > I think if a person had those same advantages (e.g. could spend 5 hours thinking about what to say next) we could all hold outstanding conversations, or if we had read every book ever written I think many of us could write a very popular book, if we could read every singe company's P&L statement in a few seconds we could invest better than an index fund

      I’m not so sure of that - to get average outcomes in these fields it’s a matter of time, to get above average or extraordinary, you need talent/intelligence/taste.

      And the bar the parent set is at extraordinary.

  • I would be willing to bet that any human for which we spend $100billion - $3 trillion (depending if you want to count single corporations or global totals) on in an attempt to make them as capable as possible would be able to reach all of those levels.

    • You'd get rapidly diminishing to zero returns after the cost of university a few times over. Every dollar past that would produce no performance gain beyond that.

    • Are you imagining artificial augmentation somehow? Purely through tutors or training programs we seem pretty limited. Otherwise billionaires (or even multimillionaires) could have far more consistently successful kids.

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>be able to sort through research and come to conclusions on complex geopolitical/sociological topics (e.g. theorize on whether AGI will result in mass poverty or mass abundance and be able to argue persuasively)

i'm not sure what makes you think AI cannot do this already. in my experience, this sort of deep research is something AI is quite good at.

example i just tested: https://chatgpt.com/share/6a9a20e3-1d20-83ea-a125-31aa240c74...

  • I understand that what it came up with sounds impressive (especially since I know 0 about Myanmar), but on the topics I do know about its analysis routinely have very fundamental problems (even this Myanmar analysis has % that add up to > 100). There's a chance it's just parroting the majority opinion on Myanmar, or making stuff up (and perhaps you could ask it to write a strongly worded opinion in the other direction that would sound equally plausible).

    For example I asked it to do a full analysis on the AI bubble, and a full analysis on the risks of Glyphosate, and it came up with a lot of things that sounded credible, but within a few minutes of questing was admitting it hadn't even really checked for internal consistency in its positions, and even doing a 180. It certainly was much faster at gathering sources and reading but it fundamentally doesn't seem very effective at creating a consistent worldview.

    And of course the funny thing is it says it did a 180 on one of these topics, great, except whatever it concluded will be discarded because it cannot learn. It's just bonkers to me pretend this is AGI, it probably couldn't even hold its own in this very discussion.

    • I claim that the percentages add up to more than 100% because the first described case overlaps with the second.

You want a computer program to be able to take a single phrase and execute decade long journies?

Who will be responsible for the outputs and side effects of such a closed loop system?

Half of those the agent fleet systems can do right now.

These are things it cant do and will not be able to do without human labor and long running human vision:

https://rcsnyder.github.io/open-frontier-curriculum/05-front...

https://rcsnyder.github.io/open-frontier-curriculum/05-front...

  • > You want a computer program to be able to take a single phrase and execute decade long journies?

    In my opinion that is exactly the point missing from AGI: the fact that you still need to prompt it. As long as you have to ask for something, is not general.

    • Autonomy is not the same as general intelligence. We already have all kinds of fully autonomous technologies that are nowhere close to generally intelligent. Plus, at a certain level of abstraction, human beings also need to be “prompted” to some extent by stimuli. And this is the funny thing about general intelligence as a concept: most of the definitions that come close to internal coherence rely on references to human intelligence, a concept we feel like we understand because we all live it all the time, but whose actual nature and structure is extremely slippery.

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    • I don't get it, human employees frequently need to ask for directions too?

      They often act on their own, too, and get things wrong a lot. The reason it works is because of all the systems of laws and institutions we have built around humans, not so much because human minds are special.

    • It sounds like what you're saying is that AGI should have some sort of free will. I'm not sure why you would add that as a requirement. Could you expand?

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  • >You want a computer program to be able to take a single phrase and execute decade long journies? > Who will be responsible for the outputs and side effects of such a closed loop system?

    Itself. That's the point. We can do it. Until it can met that bar, it ain't AGI. That's always been the bar.

    • "Being a person in all of its aspects" isn't the same as "generally intelligent". The latter is at best subset of the former, and it's also easy to imagine a system that is more generally intelligent than humans, without being a person. See also discussions of the personhood of various animals who are less intelligent than average humans.

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- Amazon is full of AI books, and they're clearly making money. AI has won multiple literary and artist awards.

- Okay, it's not a "new company" idea, but VendingBench is all about ability to run a company

- Plenty of people disagree with you on conversational quality; see "AI Boyfriends" etc.. (and it's not hard to find people who consider it uniquely valuable for discussing mental health)

- "come up with its own ideas or theories that nobody else has presented" C'mon, seriously? Solving a half-dozen hard open math problems wasn't enough there? What the heck counts as "it's own ideas or theories" at this point?

- plenty of evidence that custom models are starting to do well on the stock market, although I'll admit we're a year or so from any solid proof, since you need a track record to really make the claim

- LLMs have been capable of being a GM for a TTRPG for over a year (although like humans, they make mistakes)

- Okay, conceded, but humans tend to take years and large teams to make a game. Even if the capability existed today, it would take a while to actually build, test, market, etc.. - all made much more complicated by gamers being largely opposed to AI art styles, etc..

- "be able to sort through research and come to conclusions on complex geopolitical/sociological topics" - uh... did you mean to say something else, because "come to conclusions" is... like, LLM 101?

- Hahaha, have you met humans? We definitely cannot do that.

- Uh... thinking about it's own thinking is trivial. Most LLMs these days are built using LLMs, so uh, self-optimization seems nailed, too? We just don't let them do it unsupervised.

- LLMs fucking love to wonder about things

- "observe contradictions and ironies in the social-consciousness" really seriously have you actually used an LLM recently? I think you would find it remarkably enlightening.

> come up with a new company idea, Run that company

So far nobody's even shown an LLM succesfully running a high-traffic vending machine for as much as 30 days at a time.

I would bet that llms have talked plenty of people both into and out of suicide at this point. That nitpick aside, I think that's an excellent list. Especially being able to articulate what it does and doesn't know, or how confident it is. That's something that naively sounds pretty simple, but clearly isn't. And it's something humans aren't great at either (see: Dunning-Kruger), but so far LLMs don't even really have the capability to attempt it.

So the goalposts have moved to include continual learning.

In a sense I think no one will agree on a definition of AGI until it becomes impossible to construct any benchmark under which an AI underperforms "average" humans. That or it's defined retrospectively, after it's overwhelmingly obvious it met any such definition.

  • I hardly think it’s fair to label an objection so old that Turing included it (and discussed it at length) in the list of objections to thinking machines in 1950 “moving the goalposts.”

    > These arguments take the form, “I grant you that you can make machines do all the things you have mentioned but you will never be able to make one to do X”. Numerous features X are suggested in this connexion. I offer a selection:

    > Be kind, resourceful, beautiful, friendly (p. 448), have initiative, have a sense of humour, tell right from wrong, make mistakes (p. 448), fall in love, enjoy strawberries and cream (p. 448), make some one fall in love with it, learn from experience (pp. 456 f.), use words properly, be the subject of its own thought (p. 449), have as much diversity of behaviour as a man, do something really new (p. 450). (Some of these disabilities are given special consideration as indicated by the page numbers.)

    (emphasis added).

  • Just because a condition is new to you doesn’t imply moving the goalpost. People have been putting forward continual learning and similar conditions like autonomy since 1950s.

I don't agree with you how measure how intelligence is, because why ??? those list is not easy even for expert human to do it either

or are you miss the part "general intelligence" is ????

This is more like ASI instead of AGI

  • The bar must be underground if things humans do all the time are considered "superintelligence"

    • How many times have you done each of the following?

      - write a well-received book, write a best-seller

      - come up with a new company idea, Run that company

      - actually have a decent conversation, maybe someday talk somebody out of suicide effectively

      - come up with its own ideas or theories that nobody else has presented

      - understand the stock market well enough to trade better than an index fund

      I just picked the first few from the top of the list. The average human has probably not done any of them.

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