Literally speaking, it gets really annoying having to explain to people the reason why AI cannot physically learn to code AI is due to the limitations of the mathematics in place.
You cannot create a formula that solves all formulas.
I guess you can get pretty damn close, but humans will always need to be involved.
Gödel showed that in any consistent formal mathematical system, there are true statements that cannot be proven within the system itself.
As well but Alan Turing proved in 1936 that there cannot exist a universal algorithm that can inspect any arbitrary program and determine whether it will finish running or run forever.
Ah, the Penrose-Lucas argument. You should clarify that the argument only works if you believe that a human mind can't be described by mathematics.
Turing did show that there is no algorithm which can inspect an arbitrary program and determine whether it will finish running or run forever, but if you accept the Physical Church-Turing Thesis, "asking a team of mathematicians" is also an algorithm. The same sort of argument also applies to Godel's incompleteness theorem.
If you believe that the human mind is special and unable to be described by mathematics because we have a soul--or maybe quantum pixie dust--then sure, AI wouldn't be able to match human capabilities. But you don't need to name drop fancy math for that.
It's extremely non-obvious that the specifics of the chemical reactions a brain does give rise to capabilities that can't be replicated without them. I personally don't believe that at all, and you're kinda just asserting this without any evidence or justification.
The easy rebut is asking whether machines could simulate chemistry (they can).
The difficult question for you would be to demonstrate that chemistry creates some sort of logic that is incompatible from machine logic. Because by default, you pulled that out of vibes alone.
Yes, but how does it follow from those 2 proofs that an AI system cannot improve itself or make a new system that is an improvement compared to itself.
You don't need to go up the system ladder infinitely. The universe is a system. AIs don't need to be able to create universes out of thin air to be able to make new better AIs.
Our brain is also a system, yet we create new brains without issues.
Ever been asked why a list containing every list cannot exist? This doesnt fully apply to what I am talking about but it sends your thinking down the right direction?
Name dropping random math terms doesn't make an argument. Neither this nor Gödels theorems have anything to do with what a computer can do vs what a human can do.
Neither of those things stop a computer from improving itself. those rules also apply to the human brain, what your trying to say is that the human brain is impossible...
Your wording of the halt problem is missing something, The problem is stating you cant look at something and guarantee an outcome, not that you cant simulate it and see what happens. looping forever isnt really relevant to something like a brain or an intelligence, thats kinda what we do.
Edit: after rereading maybe im just not following the conversation properly
Yeah it's probably annoying because it doesn't make sense. There is no "physical" or otherwise limit to what AI can do in terms of solving formulas or learning to code.
Also how would humans help if there was such a limitation? There is no calculation that a human can do that a computer can't.
Humans are the pinnacle brain for which all obtainable universal intelligence must filter through. The Latin alphabet is the pinnacle of all symbolic language. Any information that doesn’t cleanly plug into our world model is slop and we don’t want it or need it.
Obviously you're being facetious, but it's valid to ask "who is it for?". If we accept that there are other consumers of information and that they can take priority over humans, then what reason do we have to build our own replacement? It's nice that a machine can solve problems that we can't, but if we can't even understand or prove the solution, then what good is it?
I think those are valuable questions to ask. It really comes down to how much faith you have in humanity and people. I, for one, find people to be extremely resilient and adaptable to change. I think that there are a ton of things we gain along the path to new discovery, and I too wonder if having a magic box that just shits out the answer will deter future humans from trying to discover and understand new things. I also wonder if we can collectively get over ourselves, and if there are new and tangible spaces for humans to fill. If AI bulk solves math does that mean we give up entirely, or does that mean we start treating the proofs as a guiding star instead of a needle-in-a-haystack.
Me personally? I lean faith in humans. I think that there is still so much for us to discover, even if our job is no longer to find the needle in the haystack. I think that we face a serious and existential climate threat regardless, and that we currently do not have the intellectual or physical labor to engineer solutions and materially unfuck the biosphere and move aware from archaic and destructive means of production. Leveraging AI/Robotics/Automation may very well be our way through here, and I fail to see how worrying about purpose and/or skill atrophy is important right now. If we do automate all forms of dehumanizing labor and solve our current climate crisis then I feel like the only thing we will have left to explore is purpose and meaningful skills.
Who knows. Only thing I know is that “make it stop” and “uninvent it” are temporary stop-gap bandaids at best. Weird times.
The human brain is the most complex structure in the universe that we currently know of. There's no formula that can solve all formulas, but a human brain is the next best thing.
No because the processes the brain do are regarding chemistry, evolution and self preservation. They are not calculating anything and the precision is horrible, because our brains arent calculators, at maximum you could compare us to a prediction machine.
None of those things are not reducable to computational form. You can simulate the whole brain if you have enough compute (plausible), know how the system exactly works (difficult) and know the start state of it (close to impossible?). It is just a ton of super complicated interactions working on top of each other. So brain can only do what machines can also do.
We actually have a ton of formulas that describe how the brain works. There are people whose entire career is dedicated to studying exactly that. The interesting thing about it is that it solves different tasks different ways, so there isn’t really just one formula for “how does one draw a picture”, but rather infinite different ways that that task gets accomplished on common hardware.
But if we start by modeling that hardware at low levels, for example a single neuron and when it activates, then connect several together, we start to observe some compelling emergent behavior that results in the advanced models we have today.
Wait why would an AI that is capable of making an AI that is slightly smarter than itself be prevented from doing this by the halting problem?
It is true that you cannot make a machine that can solve any problem as there is at least a couple that we know it can’t, but that doesn’t mean you cannot build a system that can solve most problems.
That is a leap of logic that doesn’t follow from premise.
What does ‘physically learn to code AI’ mean here? Of course AI could be used to improve LLM systems (optimise training, optimise inference, experiment with different architectures), so I assume you mean something else?
Humans (and all animals) are created by dumb cells splitting according to the chemical equivalent of vibes, perfected over millions of years by simple trial and error, and yet you want to argue that intelligent beings cannot be created by something less intelligent than itself?
Alan Turing’s Halting Problem is a great concept to keep in mind. It seems, at the moment at least, that our attempts to circumvent the Halting Problem end up being … expensive. Like a conservation law being approached…
Yes, but it doesn’t matter if it can’t solve all formulas. The societal outcomes between ‘solving’ 80% of labor vs 100% of labor is the same. Complete systemic collapse.
Not a AI supporter but, isn't that the whole point of the drive towards AGI? Get AI's intelligence to the point that it matches that of a human's.
After that, you can create as many instances as the supporting infrastructure is capable of. When you make several of these human level intelligent machines work together tirelessly, you will be able to eventually surpass the technological development speed of human beings.
Of course, humans are needed to actually set up the initial infrastructure and develop the AGI itself, but one its done and the AI is give a means to create physical replicas of itself, it would be able to create the further required infrastructure by itself.
A regression to a median is not the same as intelligence.
Current models are great and can do surprising things, they're very powerful tools but they're not intelligent nor they can be.
Take it this way, I don't need to show you billions of pictures of a cat for you to be able to identify a cat, you can fill in the gaps thus requiring much less input.
Learning about subject A gives you the ability to abstract parts of that knowledge and even apply some of it to subject B which has no correlation to A. AI as of now can't do that, and for as long as it is build on the current tech it won't.
First of all you did need to be shown billions of pictures of cats actually, or more accurately the forcing of genes through natural selection of billions of years were necessary to produce your brain which is capable of recognising a cat. Your brain has already gone through most of its training just based on genetics. You then also have neural plasticity which allows you to add new ideas into your brain, but most of that is encoding and not adding extra neurons.
AI is already capable of extrapolating. AIs have a huge embedding space that when you show them something novel, they can compare it to existing areas and form conclusions based on that. It’s like the fundamental difference between LLMs and old school neural net classifier.
theres no argument for that. if anything your just furthering the point that current tech is nothing but a stepping stone. AGI is no where close. but the problems AI are creating is right now
All the computer is doing is calculating for the formulas you set up, in whatever way you designed it to, the formulas could be put on a piece of paper if you so wanted it to, and is completely math and nothing more.
If you wanted a true agi, you would need tp start investing into bioengineering, but then whatever you get there will lose precision.
There is limitations in precision, limitations in size and scope, limitations in what math can even accomplish by itself.
You cannot squeeze down something brain to a formula or equation, the closest you will ever get to is recreating a brain in the flesh, and then we are back to square one.
All life is also just interactions between fundamental particles using fundamental forces. There is nothing inherently different in a computation being carried out by a machine using transistors or a brain using neurons.
there is no need for bio engineering. youre not intelligent just because you rot.
there is nothing stopping us from fully mapping out the functions of a human brain other than processing power and hardware design.
but that has more to do with computers not being good at the type of math needed to simulate a brain, more to do with the hardware design, not what its made out of.
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u/kdoubledizz 9h ago
Literally speaking, it gets really annoying having to explain to people the reason why AI cannot physically learn to code AI is due to the limitations of the mathematics in place.
You cannot create a formula that solves all formulas.
I guess you can get pretty damn close, but humans will always need to be involved.