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So does the human brain transcend math, or are humans not generally intelligent?
by like_any_other 1y ago
So does the human brain transcend math, or are humans not generally intelligent?
- xeonmc 1y agoI think the latter fact is quite self-demonstrably true.
- School-Cotton 1y agoHow so?
- ninetyninenine 1y agoColloquially anything that matches humans in general intelligence and is built by us is by definition an agi and generally intelligent. Humans are the bar for general intelligence.
- mort96 1y agoI would really like to see your definition of general intelligence and argument for why humans don't fit it.
- autobodie 1y agoHumans do a lot of things that computers don't, such as be born, age (verb), die, get hungry, fall in love, reproduce, and more. Computers can only metaphorically do these things, human learning is correlated with all of them, and we don't confidently know how. Have some humility.
- onlyrealcuzzo 1y agoThe point is that if it's mathematically possible for humans, than it naively would be possible for computers. All of that just sounds hard, not mathematically impossible. As I understand it, this is mostly a rehash on the dated Lucas Penrose argument, which most Mind Theory researches refute.
- ninetyninenine 1y agoWe don’t even know how LLMs work. But we do know the underlying mechanisms are governed by math because 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. We just can’t fully model the high level consequence of emergent patterns due to the sheer complexity of trillions of interacting atoms. So it’s not that there’s some mysterious supernatural thing we don’t understand. It’s purely a complexity problem in that we only don’t understand it because it’s too complex. What does humility have to do with anything?
- bigyabai 1y ago> We don’t even know how LLMs work Speak for yourself. LLMs are a feedforward algorithm inferring static weights to create a tokenized response string. We can compare that pretty trivially to the dynamic relationship of neurons and synapses in the human brain. It's not similar, case closed. That's the extent of serious discussion that can be had comparing LLMs to human thought, with apologies to Chomsky et. al. It's like trying to find the anatomical differences between a medieval scribe and a fax machine.
- hnfong 1y agoPretty sure in most other contexts you wouldn't agree a medieval scribe knows how a fax machine works.
- ninetyninenine 1y agoAnalogies aren’t proof. Like if an analogy doesn’t apply in certain context it is not a reflection of the actual situation. It just means the analogy is bad and irrelevant. Often people who don’t know how to be logical end up using analogies as proof. And you can simply say that the analogy doesn’t apply and is inaccurate and the whole argument becomes garbage because analogies aren’t logical basis for anything. Analogies are communication cools to facilitate easier understanding they are not proofs or evidence of anything.
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- andyjohnson0 1y agoTFA presents an information-theoretic argument forAGI being impossible. My reading of your parent commenter is that they are asking why this argument does not also apply to humans. You make broadly valid points, particularly about the advantages of embodyment, but I just dont think theyre good responses to the theoretical article under discussion (or the comment that you were responding to).
- daedrdev 1y agoTaking GLP-1 makes me question how much hunger is really me versus my hormones controlling me.
- add-sub-mul-div 1y agoMy take is that it transcends any science that we'll understand and harness in the lifetime of anyone living today. It for all intents and purposes transcends science from our point of view, but not necessarily in principle.
- ffwd 1y agoI think humans have some kind of algorithm for deciding what's true and consolidating information. What that is I don't know.
- ICBTheory 1y agoI guess so too... but whatever it is: it cannot possibly be something algorithmic. Therefore it doesn't matter in terms of demonstrating that AI has a boundary there, that cannot be transcended by tech, compute, training, data etc.
- ffwd 1y agoWhy can't it be algorithmic? If the brain uses the same process on all information, then that is an algorithmic process. There is some evidence that it does do the same process to do things like consolidating information, processing the "world model" and so on. Some processes are undoubtedly learned from experience but considering people seem to think many of the same things and are similar in many ways it remains to be seen whether the most important parts are learned rather than innate from birth.
- donkeybeer 1y agoExplain what you mean by "algorithm" and "algorithmic". Be very precise. You are using this vague word to hinge on your entire argument and it is necessary you explain first what it means. Since from reading your replies here it is clear you are laboring under a defitnition of "algorithm" quite different from the accepted one.
- vidarh 1y agoWhy can't it be algorithmic? Why do you think it mustn't be algoritmic? Why do you think humans are capable of doing anything that isn't algoritmic? This statement, and your lack of mention of the Church-Turing thesis in your papers suggests you're using a non-standard definition of "algoritmic", and your argument rests on it.
- fellowniusmonk 1y agoThis paper is about the limits in current systems. Ai currently has issues with seeing what's missing. Seeing the negative space. When dealing with complex codebases you are newly exposed to you tackle an issue from multiple angles. You look at things from data structures, code execution paths, basically humans clearly have some pressure to go, fuck, I think I lost the plot, and then approach it from another paradigm or try to narrow scope, or based on the increased information the ability to isolate the core place edits need to be made to achieve something. Basically the ability to say, "this has stopped making sense" and stop or change approach. Also, we clearly do path exploration and semantic compression in our sleep. We also have the ability to transliterate data between semantic to visual structures, time series, light algorithms (but not exponential algorithms, we have a known blindspot there). Humans are better at seeing what's missing, better at not closuring, better at reducing scope using many different approaches and because we operate in linear time and there are a lot of very different agents we collectively nibble away at complex problems over time. I mean on a 1:1 teleomere basis, due to structural differences people can be as low as 93% similar genetically. We also have different brain structures, I assume they don't all function on a single algorithmic substrate, visual reasoning about words, semantic reasoning about colors, synesthesia, the weird handoff between hemispheres, parts of our brain that handle logic better, parts of our brain that handle illogic better. We can introspect on our own semantic saturation, we can introspect that we've lost the plot. We get weird feelings when something seems missing logically, we can dive on that part and then zoom back out. There's a whole bunch of shit the brain does because it has a plurality of structures to handle different types of data processing and even then the message type used seems flexible enough that you can shove word data into a visual processor part and see what falls out, and this happens without us thinking about it explicitly.
- ImHereToVote 1y agoHumans use soul juice to connect to the understandome. Machines can't connect to the understandome because of Gödels incompleteness, they can only make relationships between tokens. Not map them to reality like we can via magic.
- Workaccount2 1y agoStochastic parrots all the ways down https://ai.vixra.org/pdf/2506.0065v1.pdf https://ai.vixra.org/pdf/2506.0065v1.pdf
- deadbabe 1y agoFirst of all, math isn’t real any more than language isn’t real. It’s an entirely human construct, so it’s possible you cannot reach AGI using mathematical means, as math might not be able to fully express it. It’s similar to how language cannot fully describe what a color is, only vague approximations and measurements. If you wanted to create the color green, you cannot do it by describing various properties, you must create the actual green somehow.
- like_any_other 1y agoFair enough. But then, AGI wouldn't really be based on math, but on physics. Why would an artificially-constructed physical system have (fundamentally) different capabilities than a natural one?
- hnfong 1y agoAs a somewhat colorblind person, I can tell you that the "actual green" is pretty much a lie :) It's a deeply philosophical question what constitutes a subjective experience of "green" or whatever... but intelligence is a bit more tractable IHO.
- Workaccount2 1y agoI don't think it would be unfair to accept the brain state of green as an accurate representation of green for all intents and purposes. Similar to how "computer code" and "video game world" are the same thing. Everything in the video game world is perfectly encoded in the programming. There is nothing transcendent happening, it's two different views of the same core object.
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- lexicality 1y ago> are humans not generally intelligent? Have you not met the average person on the street? (/s)
- ben_w 1y agoNoted /s, but truly this is why I think even current models are already more disruptive than naysayers are willing to accept that any future model ever could be.
- topspin 1y agoI'm noting the high frequency of think pieces from said naysayers. It's every day now: they're all furiously writing about flaws and limitations and extrapolating these to unjustifiable conclusions, predicting massive investment failures (inevitable, and irrelevant,) arguing AGI is impossible with no falsifiable evidence, etc.
- ICBTheory 1y agoHi and thanks for engaging :-) Well, it in fact depends on what intelligence is to your understanding: -If it intelligence = IQ, i.e. the rational ability to infer, to detect/recognize and extrapolate patterns etc, then AI is or will soon be more intelligent than us, while we humans are just muddling through or simply lucky having found relativity theory and other innovations just at the convenient moment in time ... So then, AI will soon also stumble over all kind of innovations. None of both will be able to deliberately think beyond what is thinkable at the respective present. - But If intelligence is not only a level of pure rational cognition, but maybe an ability to somehow overcome these frame-limits, then humans obviously exert some sort of abilities that are beyond rational inference. Abilities that algorithms can impossibly reach, as all they can is compute. - Or: intelligence = IQ, but it turns out to be useless in big, pivotal situations where you’re supposed to choose the “best” option — yet the set of possible options isn’t finite, knowable, or probabilistically definable. There’s no way to defer to probability, to optimize, or even to define what “best” means in a stable way. The whole logic of decision collapses — and IQ has nothing left to grab onto. The main point is: neither algorithms nor rationality can point beyond itself. In other words: You cannot think out of the box - thinking IS the box. (maybe have a quick look at my first proof -last chapter before conclusion- - you will find a historical timeline on that IQ-Thing)
- like_any_other 1y agoLet me steal another users alternate phrasing: Since humans and computers are both bound by the same physical laws, why does your proof not apply to humans?
- ICBTheory 1y agoWhy? 1. Basically because physical laws obviously allow more than algorithmic cognition and problem solving. (And also: I am bound by thermodynamics as my mother in Law is, still i get disarranged by her mere presence while I always have to put laxatives in her wine to counter that) 2. human rationality is equally limited as algorithms. Neither an algorithm nor human logic can find itself a path from Newton to Einsteins SR. Because it doesn't exist. 3. Physical laws - where do they really come from? From nature? From logic? Or from that strange thing we do: experience, generate, pattern, abstract, express — and try to make it communicable? I honestly don’t know. In a nutshell: there obviously is no law that forbids us to innovate - we do this, quite often. There only is a logical boundary, that says that there is no way to derive something out of a something that is not part of itself - no way for thinking to point beyond what is thinkable. Imagine little Albert asking his physics teacher in 1880: "Sir - for how long do I have to stay at high speed in order to look as grown up as my elder brother?" ... i guess "interesting thought" would not have been the probable answer... rather something like "have you been drinking? Stop doing that mental crap - go away, you little moron!"
- geoka9 1y agoHumans are fallible in a way computers are not. One could argue any creative process is an exercise in fallibility. More interestingly, humans are capable of assessing the results of their "neural misfires" ("hmm, there's something to this"), whereas even if we could make a computer do such mistakes, it wouldn't know its Penny Lane from its Daddy's Car[0], even if it managed to come up with one. [0]https://www.youtube.com/watch?v=LSHZ_b05W7o https://www.youtube.com/watch?v=LSHZ_b05W7o
- ben_w 1y agoHang on, hasn't everyone spent the past few years complaining about LLMs and diffusion models being very fallible? And we can get LLMs to do better by just prompting them to "think step by step" or replacing the first ten attempts to output a "stop" symbolic token with the token for "Wait… "?
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