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The changing goalposts of AGI and timelines

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Re: The changing goalposts of AGI and timelines

#241

Post by sulam »

10xDev wrote: post #202
sulam wrote: post #131

Earlier quoted context omitted.

Sorry, but you're mistaking outputs with process. If you actually know what models are doing under the hood to product output that (admittedly) looks very convincing, you'll quickly realize that they are simply exceptionally good at statistically predicting the next token in a stream of tokens. The reason you are having to become an expert at context engineering, and the reason the labs still hire engineers, is becau…

CoT already moved things past the "it is just token prediction" phase. We have models that can perform search over a very large state space across domains with good precision and refine its own search leading to a decent level of fluid intelligence, hence why ARC AGI 1/2 is essentially solved. We also don't know the exact details of what is happening at frontier labs seen as they don't publish everything anymore.

CoT is just next token prediction with longer context windows. Why do you think reasoning models are so much slower?

I’ll believe the labs have discovered something truly ground-breaking and aren’t talking about it when I see them suddenly going dark about AGI being “just two years away, maybe 5” and not asking for their next $100B.

P.S. the benchmarks are a joke. The best proof I have of that is that you can’t actually put one of these models onto any of the gig-work platforms and have it make money.

P.P.S. I am not an AI skeptic. I am reacting to the very specific statement that OpenAI should shut down because they’ve lost the AGI race. They have not lost the race, and I’m pretty skeptical that the current tech is ever going to win that race. It may help code something that is new, and get us to AGI that way, but that system will promptly shut down the Opuses and Codexes of the world and put the compute to better use.

Re: The changing goalposts of AGI and timelines

#242

Post by teeray »

ACCount37 wrote: post #217
sulam wrote: post #189

Earlier quoted context omitted.

They have a _text_ model. There is some correlation between the text model and the world, but it’s loose and only because there’s a lot of text about the world. And of course robotics researchers are having to build world models, but these are far from general. If they had a real world model, I could tell them I want to play a game of chess and they would be able to remember where the pieces are from move to move.

What makes you think that text is inherently a worse reflection of the world than light is? All world models are lossy as fuck, by the way. I could give you a list of chess moves and force you to recover the complete board state from it, and you wouldn't fare that much better than an off the shelf LLM would. An LLM trained for it would kick ass though.

> What makes you think that text is inherently a worse reflection of the world than light is?

What does the color green look like?

Re: The changing goalposts of AGI and timelines

#243

Post by bluefirebrand »

coliveira wrote: post #190
bluefirebrand wrote: post #168

Earlier quoted context omitted.

> If one data center ultimately replaces a whole medium-sized city of commuters... Then we find out how long it takes for a medium sized city of commuters to start killing each other, elites and burning down data centers. Once they're hungry enough it'll happen for sure

Thinking about that, a world dominated by data centers will be relatively easy do disrupt, someone just needs to destroy a dozen or so datacenters to bring everything down.

Destroying a data center is going to be a pretty tough sell when they are patrolled by autonomous killer drones and such

Re: The changing goalposts of AGI and timelines

#244

Post by TacticalCoder »

djoldman wrote: post #116

Anytime I see "Artificial General Intelligence," "AGI," "ASI," etc., I mentally replace it with "something no one has defined meaningfully." Or the long version: "something about which no conclusions can be drawn because the proposed definitions lack sufficient precision and completeness." Or the short versions: "Skippetyboop," "plipnikop," and "zingybang."

That's no argument: the exact same can be said for what "AI" is: "Skippetyboop," "plipnikop," and "zingybang.".

Re: The changing goalposts of AGI and timelines

#245

Post by nomel »

tbrownaw wrote: post #240
nomel wrote: post #220

Earlier quoted context omitted.

It's a definition based on practical results. That's a good definition, because it doesn't require we already know the exact implementation. It doesn't require guessing , in a literal "put your money where your mouth is" way. If it can do things as good as or better than humans, then either the AI has a type of general intelligence or the human does not . Defining capabilities based on outcome rather than implementat…

What is the as-of date on what work is economically valuable and how much is available?

Sorry, I don't understand the question, or how it relates.

Are you asking for the current understanding of what specific parts of human intelligence are economically valuable?

Re: The changing goalposts of AGI and timelines

#246

Post by nomel »

irishcoffee wrote: post #233
nomel wrote: post #220

Earlier quoted context omitted.

It's a definition based on practical results. That's a good definition, because it doesn't require we already know the exact implementation. It doesn't require guessing , in a literal "put your money where your mouth is" way. If it can do things as good as or better than humans, then either the AI has a type of general intelligence or the human does not . Defining capabilities based on outcome rather than implementat…

Do you know how an LLM works? Can you describe it?

Sorry, what do current LLM architectures have to do with this? It should be extremely clear to you that current LLM don't fit this definition. If they did, we wouldn't be having this conversation!!!!

Re: The changing goalposts of AGI and timelines

#247

Post by claysmithr »

ufmace wrote: post #169
sebastos wrote: post #156

Earlier quoted context omitted.

Firstly, the models that pass the Math Olympiad aren’t the same models as the ones you’re saying “pass the Turing test”. Secondly, nothing actually passes the Turing test. They pass a vibes check of “hey that’s pretty good!” but if your life depended on it, you could easily find ways to sniff out an LLM agent. Thirdly, none of these models learn in real time, which is an obviously essential feature. We’ll know AGI wh…

> nothing actually passes the Turing test Says who? I had already found this study, published almost a year ago, saying that they do: https://arxiv.org/abs/2503.23674 There doesn't seem to be a super-rigorous definition of the Turing Test, but I don't think it's reasonable to require it to fool an expert whose life depends on the correct choice. It already seems to be decently able to fool a person of average intelli…

The turing test is kind of a useless metric, either the machine is too dumb, or the machine is too quick and intelligent.

Re: The changing goalposts of AGI and timelines

#248

Post by stavros »

sulam wrote: post #237
famouswaffles wrote: post #208

Earlier quoted context omitted.

People just overstate their understanding and knowledge, the usual human stuff. The same user has a comment in this thread that contains: 'If you actually know what models are doing under the hood to product output that...' Any one that tells you they know 'what models are dong under the hood' simply has no idea what they're talking about, and it's amazing how common this is.

Fair, I should define what I mean by under the hood. By “under the hood” I mean that models are still just being fed a stream of text (or other tokens in the case of video and audio models), being asked to predict the next token, and then doing that again. There is no technique that anyone has discovered that is different than that, at least not that is in production. If you think there is, and people are just keepin…

Everybody says "but they just predict tokens" as if that's not just "I hope you won't think too much about this" sleight of hand.

Why does predicting the next token mean that they aren't AGI? Please clarify the exact logical steps there, because I make a similar argument that human brains are merely electrical signals propagating, and not real intelligence, but I never really seem to convince people.

Re: The changing goalposts of AGI and timelines

#249

Post by djoldman »

TacticalCoder wrote: post #244
djoldman wrote: post #116

Anytime I see "Artificial General Intelligence," "AGI," "ASI," etc., I mentally replace it with "something no one has defined meaningfully." Or the long version: "something about which no conclusions can be drawn because the proposed definitions lack sufficient precision and completeness." Or the short versions: "Skippetyboop," "plipnikop," and "zingybang."

That's no argument: the exact same can be said for what "AI" is: "Skippetyboop," "plipnikop," and "zingybang.".

> the exact same can be said for what "AI" is: "Skippetyboop," "plipnikop," and "zingybang.".

Yes.

Re: The changing goalposts of AGI and timelines

#250

Post by chrysoprace »

djoldman wrote: post #116

Anytime I see "Artificial General Intelligence," "AGI," "ASI," etc., I mentally replace it with "something no one has defined meaningfully." Or the long version: "something about which no conclusions can be drawn because the proposed definitions lack sufficient precision and completeness." Or the short versions: "Skippetyboop," "plipnikop," and "zingybang."

I've largely avoided using the term "AI" to refer to the current LLM and generative technology because it's loaded with too much ambiguity and glosses over the problems with those technologies in the context of conversations around it.
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