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Comment by short_sells_poo | Hacker News Reader

I suppose it's a question whether what we call "reasoning" is an emergent phenomenon from having enough connections in a graph, or whether it's some other special sauce which we simply don't have in our current models yet. E.g. humans follow a deductive process to answer questions which they haven't encountered yet. Do we gain this ability purely from a denser/larger graph of knowledge, or from a completely different architecture?

I think until we know the answer to this, we can't make predictions about how to build true AGI.

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> E.g. humans follow a deductive process to answer questions which they haven't encountered yet.

Rarely, actually.

More generally humans use all kind of inferences where problem at hand is intertwined with all other attention points that is occupying the mental load of the person. Giving a topic full mental attention and finding a path through pure deduction about a circumscribed subject is a rarity, even if you consider only those situations that require any conscious attention at all to perform some action before moving on.

Not within mathematics, where it is the entire sport, and which is the point of contention.

If there is one space where it shines, sure it’s mathematics. But even there, the most notable mathematicians highly rely on some intuitions far before they manage to prove anything, as well as while selecting/creating their conceptual tools to attempt to build the proof, and rarely go to the point of formalizing their points through Coq/Isabelle or even with meticulous paper craft à la Principia Mathematica from Russel and Whitehead.

Except humans correctly believe that a Coq proof is theoretically correct whereas an LLM does not have this meta reasoning ability at all.

All of our deductive reasoning is founded in induction. For example, the basis of all arithmetic is physics analogies regarding things that exist and the understanding that a thing implies another thing is not based in deduction. Similarly, I suspect from my own experience that general reasoning requires a basic understanding of physics if its origin isn't something ineffable. The ability to connect and find implications cannot itself be purely deductive and it would seem to me that an understanding of physical reality would have to be the origin for that ability.

> an emergent phenomenon from having enough connections in a graph, or ... some other special sauce

For humans, it is emergent. But when we reason about reason, we invent special sauce.

If we build our theories of reason into our models, they achieve the strengths and limitations of our models.

If we don't, we're limited by the pace of evolution, because we don't have enough connections in our graph.

So I think we'll have something immediately more useful if we embed ALU special instructions into a neural network.

I must be in the minority here, but I don't think most people exercise any reason. I'd even venture that the vast majority of people haven't reasoned recently at all. In my mind, reasoning is an ability... a willful act to engage in thinking through an abstract problem. Most people don't do this and just use rationalization and learned behavior, which our brains are good at.

Well, 99% of day to day life is mundane for much of living beings on earth. A bee is able to get through it's entire life without showing signs that it deeply ponders about anything.

However, humans have the ability to reason about things (whether most people use this ability is a different question). So then we must ask the question: is this ability just a more advanced form of probabilistic pattern matching, or is it a different architecture altogether? Will current AI models be able to develop this ability, or will we need new models?

I think for the most part that's true, but obviously there are things people want to use LLMs for that do require planning/reasoning, and it makes for unexpected failure modes if LLMs don't have this ability.

People do inference all the time. “Is that driver about to turn?” “Where is the water next to the faucet coming from?” “Does this person like me?”

> humans follow a deductive process to answer questions which they haven't encountered yet

nope. most humans fall in various traps such as pattern recognition, confirmation bias, and many others instead of relying on deductive analysis. Even scientists fail at being rigorous.

Of course there are cases like this, nobody is perfect. But we are talking about mathematics here, not everyday subconscious decision making. I agree that 99% of daily life is trivial pattern recognition. That's not what distinguishes humans though is it? Because animals, down to single celled organisms do just fine without higher order mental capabilities. But we are talking about reasoning here - and specifically about structured one like math.

I disagree that daily life is "trivial pattern recognition".

Just our visual object recognition is immensely powerful and far beyond and current AI. A simple task like walking to the fridge requires a ton of pattern recognition and spatial reasoning. Recognizing people's moods/predicting behaviors is also incredibly involved imo.

Ive said this many times but perhaps we should focus on achieving dog level intelligence first before we start worrying about human level AGI.

Oh I'm very much with you. In fact I get irked by people here breathlessly parroting that human level AGI is upon us any day now. I'd be impressed if an AI had mouse level capabilities any time soon. I think the current models are very impressive, but they are parlor tricks compared to what a true AGI should be capable of.

>if an AI had mouse level capabilities any time soon

That's why nobody has gotten any traction selling access to AIs for $20 a month whereas selling access to mouse labor is such a thriving business.

This is such a strawman. Do you have to really stoop to this level? There are a billion useless things people pay for, is that a measure of the intelligence behind it? People routinely pay $1000 dollars for a dog, does that mean a dog is 50x more intelligent than ChatGPT? All I'm saying is that we should be a bit more humble about intelligence when we understand so little about it.

Just because LLMs are useful, it doesn't mean they exhibit more intelligence than a mouse. A mouse probably also doesn't reason about anything, but it is an agent capable of independent behavior, something that is still very far removed from current AI models.

>All I'm saying is that we should be a bit more humble about intelligence when we understand so little about it.

OK, as long as we're are being humble, how about we refrain from confidently proclaiming that there is a mouse level and a dog level that AI hasn't reached yet and that researchers will have to spend a long time getting past, so there's plenty of time before we have to worry about the possibility of AI's becoming dangerous or transformative to society?

Just our visual object recognition is immensely powerful and far beyond and current AI.

That's a point you'll likely have to revisit pretty soon. Radiology, for instance, probably won't exist as a profession 20-30 years from now. Captchas are already pretty much done for.

Well 1. Radiology is an insanely niche subject not indiciative of general intelligence, and 2. AI being at good radiology isn't about object recognition or spatial reasoning, its data analysis connecting features to outcomes.

Lastly, check out the ARC challenge or any other spatial reasoning tests for AI. Humans get ~80% on these challenges whereas the best AI is still at 25%

Can you point me towards a citation for the 25% figure? I'm seeing numbers like 96% ( https://paperswithcode.com/sota/common-sense-reasoning-on-ar... ) but I'm guessing that's just for a subset of the larger class of questions.

Also, are you familiar with this study? What are your thoughts on it? https://www.esmo.org/newsroom/press-and-media-hub/esmo-media... Seems like a valid case where AI is competitive with skilled humans at object/image recognition.

It seems theres multiple things by the name ARC. There is one by AI2 which is a text based science questions/word problems. The one Im referring to is this https://lab42.global/arc/

https://lab42.global/arcathon/leaderboard/

https://openreview.net/forum?id=E8m8oySvPJ

As to the study, I have the same objection as the radiology one. This isnt about object recognition and certainly not spatial reasoning, its the ability to predict cancer based on presence of visual features.

The "object recognition" part of this is super simple. Its a single, mostly 2D object in more or less the same angle, and the AI is trained on detecting just this.

The "object recognition" part of this is super simple. Its a single, mostly 2D object in more or less the same angle, and the AI is trained on detecting just this.

And yet it outperforms human dermatologists.

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