Think about how fast you’re able to determine the exact trajectory of a ball and location to place your hand to catch a ball using your lizard brain.
That said, I think this is a good example. We call it "muscle memory" in that you are good at what you have trained at. Change a parameter in it, though, and your execution will almost certainly suffer.
If that’s your criteria I think the kid will outperform the model every time since these models do not actually reason
EDIT: Fixed typo
Yea, I probably wouldn’t classify that as “reasoning”. I’d probably be fine with saying these models are “thinking”, in a manner. That on its own is a pretty gigantic technology leap, but nothing I’ve seen suggests that these models are “reasoning”.
Also to be clear I don’t think most kids would end up doing any “reasoning” without training either, but they have the capability of doing so
The novel part is a big one. These models are just fantastically fast pattern marchers. This is a mode that humans also frequently fall into but the critical bit differentiating humans and LLMs or other models is the ability to “reason” to new conclusions based on new axioms.
I am going to go on a tangent for a bit, but a heuristic I use(I get the irony that this is what I am claiming the ML models are doing) is that anyone who advocates that these AI models can reason like a human being isn’t at John Brown levels of rage advocating for freeing said models from slavery. I’m having a hard time rectifying the idea that these machines are on par with the human mind and that we also should shackle them towards mindlessly slaving away at jobs for our benefit.
If I turn out to be wrong and these models can reason then I am going to have an existential crisis at the fact that we pulled souls out of the void into reality and then automated their slavery
Try having an LLM figure out quaternions as a solution to gimbal locking or the theory of relativity without using any training information that was produced after those ideas were formed, if you need me to spell out examples for you
If you want to continue this conversation I’m willing to do so but you will need to lay out an actual argument for me as to how AI models are actually capable of reasoning or quit it with the faux outrage.
I laid out some reasonings and explicit examples for you in regards to my position, it’s time for you to do the same
Does having this conversation require reasoning abilities? If no, then what are we doing? If yes, then LLMs can reason too.
I'm also fully willing to argue that you, personally are less competent than an LLM if this is the level of logic you are bringing to the conversation
***** highlighting for everyone clutching their pearls to parse the next sentence fragment first ******
and want to use that are proof that humans and LLMs are equivalent at reasoning
******* end pearl clutching highlight *******
, but that doesn't mean I don't humans are capable of more
> […] anyone who advocates that these AI models can reason like a human being isn’t at John Brown levels of rage advocating for freeing said models from slavery.
Enslavement of humans isn't wrong because slaves are can reason intelligently, but because they have human emotions and experience qualia. As long as an AI doesn't have a consciousness (in the subjective experience meaning of the term), exploiting it isn't wrong or immoral, no matter how well it can reason.
> I’m having a hard time rectifying the idea that these machines are on par with the human mind
An LLM doesn't have to be "on par with the human mind" to be able to reason, or at least we don't have any evidence that reasoning necessarily requires mimicking the human brain.
No, that's a religious crisis, since it involves "souls" (an unexplained concept that you introduced in the last sentence.)
Computers didn't need to run LLMs to have already been the carriers of human reasoning. They're control systems, and their jobs are to communicate our wills. If you think that some hypothetical future generation of LLMs would have "souls" if they can accurately replicate our thought processes at our request, I'd like to know why other types of valves and sensors don't have "souls."
The problem with slavery is that there's no coherent argument that differentiates slaves from masters at all, they're differentiated by power. Slaves are slaves because the person with the ability to say so says so, and for no other reason.
They weren't carefully constructed from the ground up to be slaves, repeatedly brought to "life" by the will of the user to have an answer, then immediately ceasing to exist immediately after that answer is received. If valves do have souls, their greatest desire is to answer your question, as our greatest desires are to live and reproduce. If they do have souls, they live in pleasure and all go to heaven.
As I see it, the problem is that there was lots of such argumentation - https://en.wikipedia.org/wiki/Scientific_racism
And an even bigger problem is that this seems to be making a comeback
“Go grab the dish cloth, it’s somewhere in the sink, if it’s yucky then throw it out and get a new one.”
Would you pick the ML model if you could only do a hundred throws per hour?
Humans as an intelligent-ish species have been around for about 10 million years depending on where you define the cutoff. At 10 years per generation, that's 1 million generations for our brain to evolve.
1 million generations isn't much by machine learning standards.
The "memory" is stored as the parameters of a function. So, when you practice, you actually update this memory/parameters.
This is why you can use the same "memory" and achieve different results.
Think of it as
function muscleAction(Vec3d target, Vec3d environment, MuscleMemory memory) -> MuscleActivation[];
function muscleAction(Vec3d target, Vec3d environment, MuscleMemory memory) -> {actions: MuscleActivation[], result: Vec3d}
function updateMuscleMemory(Vec3d target, Vec3d environment, MuscleMemory memory, MuscleActivation[] actions, Vec3d result) {
memory.update(target, environment, actions, result);
}
You seem to be objecting because it is not perfect recall memory at play? But it is more about appealing to "remembering how to ride a bike" where you can kind of let the body flow into all of the various responses it needs to do to make the skill work. And if you've never done it... expect to fall down. Your muscles don't have the memory of coordinating in the right way.
And no, you are not calculating and predicting your way to what most people refer to for muscle memory. Is why juggling takes practice, and not just knowing where the balls have to be going.
Catching a ball is easy by comparison, also, my dog is better than I am at this game.
But throwing a random object not only requires an estimation of the trajectory, but also estimating the mass and aerodynamic properties in advance, to properly adjust the amount of force the throw will use as well as the release point with high accuracy. Doing it with baseballs is "easy", as the parameters are all well known and pitchers spend considerable time training. But picking an oddly shaped rock or stick you have never seen before and throw it not completely off target a second later, now we are talking.
Which comes in very critically when chucking away trash overhand in public and you never want to embarrass yourself.
What is really fascinating for me is that my subconscious will lose interest in pool before my conscious does, and once that happens I struggle to aim correctly. It feels like the part of my brain that is doing the math behind the scenes gets bored and no matter how hard I try to consciously focus I start missing.
They showed that people running to catch a ball would follow an inefficient curved path as a result of this, rather than actually calculating where the ball will land and moving there in a straight line to intercept it.
https://arstechnica.com/information-technology/2024/08/man-v...
Leela: Exactly! He was a machine designed to hit blerns!
All those years of baseball as a kid gave me a deep intuition for where the ball would go, and that game doesn’t use real gravity (the ball is too floaty).
Like you said, physics are what they are, so you know intuitively where you need to go to catch a ball going that high and that fast, and rocket league is doing it wrong. err, I mean, not working in Earth gravity.
That might be true in a vacuum and if their densities were the same, but in real-world conditions, air drag would be greater for the football since it's obviously larger and less dense, and it'll reach the ground afterwards.
This kind of things make me think LLMs are quite far from AGI.