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AGI is far from inevitable

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Re: AGI is far from inevitable

#71
post #65
post #15

Earlier quoted context omitted.

Are you talking about the press release that the story on HN currently links to, or the paper that press release is about? The paper (I'm not vouching for it; I just skimmed it) appears to reduce AGI to a theoretical computational model, and then supplies a proof that it's not solvable in polynomial time.

That paper is unserious. It is filled with unjustified assertions, adjectives and emotional appeals, M$-isms like ‘BigTech’, and basic misunderstandings of mathematical theory clearly being sold to a lay audience.

It didn't look especially rigorous to me (but I'm not in this field). I'm really just here because we're doing that thing where we (as a community) have a big 'ol discussion about a press release, when the paper the press release is about is linked right there.

Re: AGI is far from inevitable

#72
From the abstract of the actual paper:

> Yet, as we formally prove herein, creating systems with human(-like or -level) cognition is intrinsically computationally intractable.

Wow. So is this the subject of the paper? Like, this is a massive, fundamental result. Nope, the paper is about "Reclaiming AI as a Theoretical Tool for Cognitive Science".

"Ah and by the way we prove human-like AI is impossible". Haha. Gosh.

Re: AGI is far from inevitable

#73
post #45

Earlier quoted context omitted.

> but LLMs do solve problems that people thought were extremely difficult to solve ten years ago. Well for something to be G or I you need them to solve novel problems. These things have interested most of the Internet and I've yet to see a "reasoning" disentangle memorization from reasoning. Memorization doesn't mean they aren't useful (not sure why this was ever conflated since... Computers are useful...), but it's…

We don't really have the proper vocabulary to talk about this. Well, we do, but C.S. Peirce's writings are still fairly unknown. In short, there are two fundamentally distinct forms of reasoning. One is corollarial reasoning. This is the kind of reasoning that follows deductions that directly follow from the premises. This of course includes subsequent deductions that can be made from those deductions. Obviously comp…

We don't have proper language, but certainly we've improved. Even since Peirce. You're right that many people are not well versed in the philosophical and logician discussions as to what reasoning is (and sadly this lack of literature review isn't always common in the ML community), but I'm not convinced Peirce solved it. I do like that there are many different categories of reasoning and subcategories.

  > All of the above is old hat to the AI winter era guys. But amusingly their reputations have been destroyed much the same as Peirce's was, by dissatisfied government bureaucrats.
Yeah, this has been odd. Since a lot of their work has shown to be fruitful once scaled. I do think you need a combination of theory people + those more engineering oriented, but having too much of one is not a good thing. It seems like now we're overcorrecting and the community is trying to kick out the theorists. By saying things like "It's just linear algebra"[0] or "you don't need math"[1] or "they're black boxes". These are unfortunate because they encourage one to not look inside and try to remove the opaqueness. Or to dismiss those that do work on this and are bettering our understanding (sometimes even post hoc saying it was obvious).

It is quite the confusing time. But I'd like to stop all the bullshit and try to actually make AGI. That does require a competition of ideas and not everyone just boarding the hype train or have no careers....

[0] You can assume anyone that says this doesn't know linear algebra

[1] You don't need math to produce good models, but it sure does help you know why your models are wrong (and understanding the meta should make one understand my reference. If you don't, I'm not sure you're qualified for ML research. But that's not a definitive statement either).

Re: AGI is far from inevitable

#74
post #6

Basically the linked article argues like this: > That’s because cognition, or the ability to observe, learn and gain new insight, is incredibly hard to replicate through AI on the scale that it occurs in the human brain. (no other more substantial arguments were given) I'm also very skeptical on seeing AGI soon, but LLMs do solve problems that people thought were extremely difficult to solve ten years ago.

Pretty sure anyone who tries can build an ai with capabilities indistinguishable from or better than humans.

Re: AGI is far from inevitable

#75

From the abstract of the actual paper: > Yet, as we formally prove herein, creating systems with human(-like or -level) cognition is intrinsically computationally intractable. Wow. So is this the subject of the paper? Like, this is a massive, fundamental result. Nope, the paper is about "Reclaiming AI as a Theoretical Tool for Cognitive Science". "Ah and by the way we prove human-like AI is impossible". Haha. Gosh.

[deleted]

Re: AGI is far from inevitable

#76
Hypothetical situation:

Suppose in five or ten years we achieve AGI and >90% of people agree that we have AGI. What reasons do the authors of this paper give for being wrong?

1. They are in the 10% that deny AGI exists

2. LLMs are doing something they didn't think was happening

3. Something else?

Re: AGI is far from inevitable

#77
post #35

Earlier quoted context omitted.

I have seen far, far too many people say things along the lines of "Sure, LLMs currently don't seem to be good at [thing LLMs are, at least as of now, fundamentally incapable of ], but hey, some people are pretty bad at that sometimes too!" It demonstrates such a complete misunderstanding of the basic nature of the problem that I am left baffled that some of these people claim to actually be in the machine-learning f…

> How can you not understand the difference between "humans are not absolutely perfect or reliable at this task" and "LLMs by their very nature cannot perform this task"? This is a very good distillation of one side of it. What LLMs have taught us is a superficial grasp of language is good enough to reproduce a shocking proportion of what society has come to view as intelligent behaviors. i.e. it seems quite plausibl…

....But this is falling into exactly the same trap: the idea that "some people don't engage the faculties their brains do/could (with education) possess" is equivalent to the LLMs that do not and cannot possess those faculties in the first place.

Re: AGI is far from inevitable

#78

Earlier quoted context omitted.

If that's the case, would you say we're not generally intelligent as future humans tend to be more intelligent? That's just a timescale issue, if its learned experience of gpt4 is being fed into the model on training gpt5, then gptx (i.e. including all of them) can be said to be a general intelligence. Alien life one may say.

> That's just a timescale issue Every problem is a timescale issue. Evolution has shown that. And no you can't just feed GPT4 into GPT5 and expect it to become more intelligent. It may be more accurate since humans are telling it when conversations are wrong or not. But you will still need advancements in the algorithms themselves to take things forward. All of which takes us back to lots and lots of research. And if…

I think you missed my point slightly, sorry my explaining probably.

I mean timescale as in between two points in time. Between the two points it meets the intelligence criteria you mentioned. Feeding human vetted GPT4 data into GPT5 is no different to a human receiving inputs from its interaction with the world and learning. More accurate means smarter, gradually it's intrinsic world model improves as does reasoning etc.

I agree those are the things that will advance it but taking a step back it potentially meets that criteria even if less useful day to day (given its an abstract viewpoint over time and not at the human level).

Re: AGI is far from inevitable

#79
post #35

Earlier quoted context omitted.

I have seen far, far too many people say things along the lines of "Sure, LLMs currently don't seem to be good at [thing LLMs are, at least as of now, fundamentally incapable of ], but hey, some people are pretty bad at that sometimes too!" It demonstrates such a complete misunderstanding of the basic nature of the problem that I am left baffled that some of these people claim to actually be in the machine-learning f…

> How can you not understand the difference between "humans are not absolutely perfect or reliable at this task" and "LLMs by their very nature cannot perform this task"? I understand the difference, and sometimes that second statement really is true. But a rigorous proof that problem X can't be reduced to architecture Y is generally very hard to construct, and most people making these claims don't have one. I've tal…

And I'm much less frustrated by people who are, in fact, claiming that LLMs can do these things, whether or not I agree with them. Frankly, while I have a basic understanding of the underlying technology, I'm not in the ML field myself, and can't claim to be enough of an expert to say with any real authority what an LLM could ever be able to do, just what the particular LLMs I've used or seen the detailed explanations of can do.

No; this is specifically about people who stipulate that the LLMs can't do these things, but still want to claim that they are or will become AGI, so they just basically say "well, humans can't really do it, can they? so LLMs don't need to do it either!"

Re: AGI is far from inevitable

#80
post #19
post #2

AGI is about as far away as it was two decades ago. Language models are merely a dent, and probably will be the precursor to a natural language interface to the thing.

We are clearly closer than 20 years ago - o1 is an order of magnitude closer than anything in the mid-2000s. Also I would think most people would consider AGI science fiction in 2004 - now we consider it a technical possibility which demonstrates a huge change.

"Her" is from 2013. I came out of the cinema thinking "what utter bullshit, computers that talk like human beings, à la 2001" (*). And yes, in 2013 we weren't any closer to it than we were in 1968, when A Space Odyssey came out.

* To be precise, what seemed bs was "computers that talk like humans and it's suddenly a product on the market, and you have it on your phone, and yet everyone around act like it's normal and people still habe jobs!" Ah, I've been proven completely wrong.

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