[Agentus]

kinda interesting, every single CS person (especially phds) when talking about reasoning are unable to concisely quantify, enumerate, qualify, or define reasoning.

people with (high) intelligence talking and building (artificial) intelligence but never able to convincingly explain aspects of intelligence. just often talk ambiguously and circularly around it.

what are we humans getting ourselves into inventing skynet :wink.

its been an ongoing pet project to tackle reasoning, but i cant answer your question with regards to llms.

[YeGoblynQueenne]

>> Kinda interesting, every single CS person (especially phds) when talking about reasoning are unable to concisely quantify, enumerate, qualify, or define reasoning.

Kinda interesting that mathematicians also can't do the same for mathematics.

And yet.

[logicchains]

Mathematicians absolutely can, it's called foundations, and people actively study what mathematics can be expressed in different foundations. Most mathematicians don't care about it though for the same reason most programmers don't care about Haskell.

[YeGoblynQueenne]

I don't care about Haskell either, but we know what reasoning is [1]. It's been studied extensively in mathematics, computer science, psychology, cognitive science and AI, and in philosophy going back literally thousands of years with grandpapa Aristotle and his syllogisms. Formal reasoning, informal reasoning, non-monotonic reasoning, etc etc. Not only do we know what reasoning is, we know how to do it with computers just fine, too [2]. That's basically the first 50 years of AI, that folks like His Nobelist Eminence Geoffrey Hinton will tell you was all a Bad Idea and a total failure.

Still somehow the question keeps coming up- "what is reasoning". I'll be honest and say that I imagine it's mainly folks who skipped CS 101 because they were busy tweaking their neural nets who go around the web like Diogenes with his lantern, howling "Reasoning! I'm looking for a definition of Reasoning! What is Reasoning!".

I have never heard the people at the top echelons of AI and Deep learning - LeCun, Schmidhuber, Bengio, Hinton, Ng, Hutter, etc etc- say things like that: "what's reasoning". The reason I suppose is that they know exactly what that is, because it was the one thing they could never do with their neural nets, that classical AI could do between sips of coffee at breakfast [3]. Those guys know exactly what their systems are missing and, to their credit, have never made no bones about that.

_________________

[1] e.g. see my profile for a quick summary.

[2] See all of Russeel & Norvig, as a for instance.

[3] Schmidhuber's doctoral thesis was an implementation of genetic algorithms in Prolog, even.

[Agentus]

i have a question for you, in which ive asked many philosophy professors but none could answer satisfactorily. since you seem to have a penchant for reasoning perhaps you might have a good answer. (i hope i remember the full extent of the question properly, i might hit you up with some follow questions)

it pertains to the source of the inference power of deductive inference. do you think all deductive reasoning originated inductively? like when some one discovers a rule or fact that seemingly has contextual predictive power, obviously that can be confirmed inductively by observations, but did that deductive reflex of the mind coagulate by inductive experiences. maybe not all deductive derivative rules but the original deductive rules.

[YeGoblynQueenne]

I'm sorry but I have no idea how to answer your question, which is indeed philosophical. You see, I'm not a philosopher, but a scientist. Science seeks to pose questions, and answer them; philosophy seeks to pose questions, and question them. Me, I like answers more than questions so I don't care about philosophy much.

[Agentus]

well yeah its partially philosphical, i guess my haphazard use of language like “all” makes it more philosophical than intended.

but im getting at a few things. one of those things is neurological. how do deductive inference constructs manifest in neurons and is it really inadvertently an inductive process that that creates deductive neural functions.

other aspect of the question i guess is more philosophical. like why does deductive inference work at all, i think clues to a potential answer to that can be seen in the mechanics of generalization of antecedents predicting(or correlating with) certain generalized consequences consistently. the brain coagulates generalized coinciding concepts by reinforcement and it recognizes or differentiates inclusive instances or excluding instances of a generalization by recognition properties that seem to gatekeep identities accordingly. its hard to explain succinctly what i mean by the latter, but im planning on writing an academic paper on that.

[mistermann]

>Those guys know exactly what their systems are missing

If they did not actually, would they (and you) necessarily be able to know?

Many people claim the ability to prove a negative, but no one will post their method.

[YeGoblynQueenne]

To clarify, what neural nets are missing is a capability present in classical, logic-based and symbolic systems. That's the ability that we commonly call "reasoning". No need to prove any negatives. We just point to what classical systems are doing and ask whether a deep net can do that.

[mistermann]

Do Humans have this ability called "reasoning"?

[Agentus]

well lets just say i think i can explain reasoning better than anyone ive encountered. i have my own hypothesized theory on what it is and how it manifests in neural networks.

i doubt your mathmatician example is equivalent.

examples that are fresh on the mind that further my point. ive heard yann lecun baffled by llms instantiation/emergence of reasoning, along with other ai researchers. eric Schmidt thinks the agentic reasoning is the current frontier and people should be focusing on that. was listening to the start of an ai machine learning interview a week ago with some cs phd asked to explain reasoning and the best he could muster up is you know it when you see it…. not to mention the guy responding to the grandparent that gave a cop out answer ( all the most respect to him).

[YeGoblynQueenne]

>> well lets just say i think i can explain reasoning better than anyone ive encountered. i have my own hypothesized theory on what it is and how it manifests in neural networks.

I'm going to bet you haven't encountered the right people then. Maybe your social circle is limited to folks like the person who presented a slide about A* to a dumb-struck roomfull of Deep Learning researchers, in the last NeurIps?

https://x.com/rao2z/status/1867000627274059949

[Agentus]

possibly, my university doesn’t really do ai research beyond using it as a tool to engineer things. im looking to transfer to a different university.

but no, my take on reasoning is really a somewhat generalized reframing of the definition of reasoning (which you might find on the stanford encylopedia of philosophy) thats reframed partially in axiomatic building blocks of neural network components/terminology. im not claiming to have discovered reasoning, just redefine it in a way thats compatible and sensible to neural networks (ish).

[YeGoblynQueenne]

Well you're free to define and redefine anything and as you like, but be aware that every time you move the target closer to your shot you are setting yourself up for some pretty strong confirmation bias.

[Agentus]

yeah thats why i need help from the machine interpretability crowd to make sure my hypothesized reframing of reasoning has sufficient empirical basis and isn’t adrift in lalaland.

[necovek]

Care to enlighten us with your explanation of what "reasoning" is?

[Agentus]

terribly sorry to be such a tease, but im looking to publish a paper on it, and still need to delve deeper into machine interpretability to make sure its empirically properly couched. if u can help with that perhaps we can continue this convo in private.