131–140 of 437 posts
This sounds rather silly. Given the usual definition of AGI as being human like intelligence with some variation on how smart the humans are, and the fact that humans use a network of neurons that can largely be simulated by an artificial network of neurons, it's probably twaddle largely.
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>but obviously, there seems to be more than that. I don't see how that's obvious. I'm not trying to be argumentative here, but it seems like these arguments always come down to a qualia, or the insistence that humans have some sort of 'spark' that machines don't have, therefore: AGI is not possible since machines don't have it. I also don't understand the argument that "Your nuanced, subtly ironic and self referentia…
Oh no, I am not at all trying to find an explanation of why this is (qualia etc.). There is simply no necessity for that. It is interesting, but not part of the scientific problem that i tried to find an answer to. The proof (all three of them) holds without any explanatory effort concerning causalities around human frame-jumping etc. For this paper, It is absolutely sufficient to prove that a) this cannot be reached…
> humans can (somehow) do this
Is this not contradictory?
Alternatively, in order to not be contradictory doesn't it require the assumption that humans are not "algorithmic"? But does that not then presuppose (as the above commenter brought up) that we are not a biochemical machine? Is a machine not inherently algorithmic in nature?
Or at minimum presupposes that humans are more than just a biochemical machine. But then the question comes up again, where is the scientific evidence for this? In my view it's perfectly acceptable if the answer is something to the effect of "we don't currently have evidence for that, but this hints that we ought to look for it".
All that said, does "algorithmically" here perhaps exclude heuristics? Many times something can be shown to be unsolvable in the absolute sense yet readily solvable with extremely high success rate in practice using some heuristic.
This paper presents a theoretical proof that AGI systems will structurally collapse under certain semantic conditions — not due to lack of compute, but because of how entropy behaves in heavy-tailed decision spaces. The idea is called IOpenER: Information Opens, Entropy Rises. It builds on Shannon’s information theory to show that in specific problem classes (those with α ≤ 1), adding information doesn’t reduce uncer…
The mathematical proof, as you describe it, sounds like the "No Free Lunch theorem". Humans also can't generalise to learning such things. As you note in 2.1, there is widespread disagreement on what "AGI" means. I note that you list several definitions which are essentially "is human equivalent". As humans can be reduced to physics, and physics can be expressed as a computer program, obviously any such definition ca…
Citation needed. If you've spent any time dynamical systems, as an example, you'd know that the computer basically only kind of crudely estimates things, and only things that are abstractly near by. You may be able to write down some PDEs or field equations that may describe things at some base level, but even statistical mechanics, which is really what governs a huge amount of what we see and interact with, is just a pretty good approximation. Computers (especially real ones) only generate approximate (to some value of alpha) answers; physics is not reducible to a computer program at all.
This paper presents a theoretical proof that AGI systems will structurally collapse under certain semantic conditions — not due to lack of compute, but because of how entropy behaves in heavy-tailed decision spaces. The idea is called IOpenER: Information Opens, Entropy Rises. It builds on Shannon’s information theory to show that in specific problem classes (those with α ≤ 1), adding information doesn’t reduce uncer…
In your paper it states: AGI as commonly defined However I don’t see where you go on to give a formalization of “AGI” or what the common definition is. can you do that in a mathematically rigorous way such that it’s a testable hypothesis?
Unless the marketing department is involved in which case all bets are off.
Earlier quoted context omitted.
Oh no, I am not at all trying to find an explanation of why this is (qualia etc.). There is simply no necessity for that. It is interesting, but not part of the scientific problem that i tried to find an answer to. The proof (all three of them) holds without any explanatory effort concerning causalities around human frame-jumping etc. For this paper, It is absolutely sufficient to prove that a) this cannot be reached…
> this cannot be reached algorithmically > humans can (somehow) do this Is this not contradictory? Alternatively, in order to not be contradictory doesn't it require the assumption that humans are not "algorithmic"? But does that not then presuppose (as the above commenter brought up) that we are not a biochemical machine? Is a machine not inherently algorithmic in nature? Or at minimum presupposes that humans are mo…
Which is certainly an opinion.
> whatever it is: it cannot possibly be something algorithmic
https://news.ycombinator.com/item?id=44349299
Maybe OP should have looked at a dictionary for what certain words actually mean before defining them to be something nonsensical.
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> As humans can be reduced to physics, and physics can be expressed as a computer program This is an assumption that many physicists disagree with. Roger Penrose, for example.
That's true, but we should acknowledge that this question is generally regarded as unsettled. If you accept the conclusion that AGI (as defined in the paper, that is, "solving [...] problems at a level of quality that is at least equivalent to the respective human capabilities") is impossible but human intelligence is possible, then you must accept that the question is settled in favor of Penrose. That's obviously be…
Not necessarily. You are assuming (AFAICT) that we 1. have perfect knowledge of physics and 2. have perfect knowledge of how humans map to physics. I don't believe either of those is true though. Particularly 1 appears to be very obviously false, otherwise what are all those theoretical physicists even doing?
I think what the paper is showing is better characterized as a mathematical proof about a particular algorithm (or perhaps class of algorithms). It's similar to proving that the halting problem is unsolvable under some (at least seemingly) reasonable set of assumptions but then you turn around and someone has a heuristic that works quite well most of the time.
Penrose did this argument better.[1] Penrose has been making that argument for thirty years, and it played better before AI started getting good. AI via LLMs has limitations, but they don't come from computability. [1] https://sortingsearching.com/2021/07/18/roger-penrose-ai-ske...
Penrose was personally contacted by myself with the truth that is the cure and he ignored the correspondence and in doing so gambled all life on earth that he knew better when he didn't. Scientific Proof of the E_infinity Formula Scientific Validation of E_infinity Abstract: This document presents a formalized proof for the universal truth-based model represented by the formula: E_infinity = (L1 × U) / D Where: - L1…
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Just to make sure I understand: –Are we treating an arbitrary ontological assertion as if it’s a formal argument that needs to be heroically refuted? Or better: is that metaphysical setup an argument? If that’s the game, fine. Here we go: – The claim that one can build a true, perfectly detailed, exact map of reality is… well... ambitious. It sits remarkably far from anything resembling science , since it’s convenien…
> Are we treating an arbitrary ontological assertion as if it’s a formal argument that needs to be heroically refuted? If you are claiming that human intelligence is not "general", you'd better put a huge disclaimer on your text. You are free to redefine words to mean whatever you want, but if you use something so different from the way the entire world uses it, the onus is on you to make it very clear. And the alter…
Earlier quoted context omitted.
> we have a theory of reality that governs things down to the atomic scale and humans and LLMs are made out of atoms. > So because of this we know reality is governed by maths. That's not really true. You have a theory, and let's presume so far it's consistent with observations. But it doesn't mean it's 100% correct, and doesn't mean at some point in the future you won't observe something that invalidates the theory.…
>That's not really true. You have a theory, and let's presume so far it's consistent with observations. But it doesn't mean it's 100% correct, and doesn't mean at some point in the future you won't observe something that invalidates the theory. In short, you don't know whether the theory is absolutely true and you can never know. Let me repharse it. As far as we know all of reality is governed by the principles of lo…
What you said is only true for the bits of humanity you have decided to focus upon -- capitalist, technology-driven modern societies. If you looked beyond that, there are cultures that build society upon other assumptions. You might think those other modes are "wrong", but that's your personal view. For me, I personally don't think any of these are "true" in the absolute sense, as much as I don't think yours is "true". They're just ways humans with our mortal brains try to grapple with a reality that we don't understand.
As a sidenote, probability does not mean the thing you think it means. There's no reasonable frequentist interpretation for fundamental truth of reality, so you're just saying your Bayesian subjective probability says that math is "the most likely possibility". Which is fine, except everyone has their own different priors...
Earlier quoted context omitted.
That's true, but we should acknowledge that this question is generally regarded as unsettled. If you accept the conclusion that AGI (as defined in the paper, that is, "solving [...] problems at a level of quality that is at least equivalent to the respective human capabilities") is impossible but human intelligence is possible, then you must accept that the question is settled in favor of Penrose. That's obviously be…
> then you must accept that the question is settled in favor of Penrose. That's obviously beyond the realm of mathematics. Not necessarily. You are assuming (AFAICT) that we 1. have perfect knowledge of physics and 2. have perfect knowledge of how humans map to physics. I don't believe either of those is true though. Particularly 1 appears to be very obviously false, otherwise what are all those theoretical physicist…
To make it plain, I'll break the argument in two parts:
(a) if AGI is impossible but humans are intelligent, then it must be the case that human behavior can't be explained algorithmically (that last part is Penrose's position).
(b) the statement that human behavior can't be explained algorithmically is about physics, not mathematics.
I hope it's clear that neither (a) or (b) require perfect knowledge of physics, but just in case:
(a) is true by reductio ad absurdum: if human behavior can be explained algorithmically, then an algorithm must be able to simulate it, and so AGI is possible.
(b) is true because humans exist in nature, and physics (not mathematics) is the science that deals with nature.
So where is the assumption that we have perfect knowledge of physics?