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Comment by drob518 | Hacker News Reader

This feels like a problem with anthropomorphizing. We’re using words like “reasoning” and “thinking” because they are comfortable, and then we’re getting wrapped around the axle because we’re not sure if those words are totally accurate. I assure you that they aren’t accurate (the model is not alive and it’s all just a lot of matrix math under the hood), but there are no good alternative words. If we wanted to be accurate, we’d use a phrase like “model-generated, auxiliary token context augmentation.” But nobody wants to say that or even its acronym. Nevertheless, we have demonstrable proof that whatever it is it results in better answers from the models. Frankly, I expect better analysis from Quanta.

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LLM's reason and think in the way that boats "swim" and planes "fly". It is an analogy. But nevertheless, planes do take you where you want to go, and so do LLMs.

I think we are in sort of the place where before the invention of planes, the only things that "flew" were animals with wings that flapped. The flapping wings might seem to be a core part of the process of flight, and that if you lacked flapping wings, you were doing something other than flying. But maybe the point is moving through the air under your own power. Balloons fly, planes fly, helicopters fly. They just do it in a different way from birds and insects.

Clearly, words morph over time. A “computer” used to refer to a human who would make numeric calculations with a pencil and paper. Maybe we’re at that point with “thinking” and “reasoning.”

Planes fly. They're up in the air passing through it. It's not an analogy; that's what flying is. Long before planes, balloons and helicopters, objects other than birds, bats and insects were considered to fly if for example they were thrown. At no point in human history has flying been restricted to animals. "Flying" as a concept in that sense predates the English word for it.

The sort of place we're actually in is one where astronomical sums of money have been invested in this technology, creating an unprecedented incentive to hype and overstate its fundamental capabilities. They're large language models and their analyses are based on language statistics, not logic, comprehension and knowledge, all of which they are fundamentally incapable of, and all of which are fundamental to reasoning. They don't reason in the literal sense that planes fly.

I don't doubt that there could be a reasoning machine, but LLMs are not it.

We do not academically consider reasoning or thinking an activity restricted to humans, but as absolute processes.

Sure, other living, non-human things clearly reason and think. My German shepherd dog is quite smart and demonstrates these processes all the time. But is a machine following an algorithm (even a stochastic algorithm) “thinking” or “reasoning?” I think not. The algorithm has gotten so difficult for us to explain that we struggle with it, but in the end it’s all just matrix math and some randomization. From a given numeric seed, it’s all quite mechanical.

> is a machine following an algorithm (even a stochastic algorithm) “thinking” or “reasoning”?

If the process is sound, yes, it can be said to be thinking or reasoning - it produced "sound thought or reasoning".

The "reasoning" is there and elsewhere the absolute (from the producing entity) output which is valid as a representation of proper reasoning.

If "A is B and B is C, then A is C" is reasoning, than what produces it in a way "reasons". If not, then a proper definition of "reasoning" must be provided, for it to be discussed.

Yes, a proper definition of reasoning must be provided. How are you defining reasoning, exactly? You imply that formal logic is reasoning. Is reasoning just formal logic or is formal logic just a subset of reasoning? If a subset, what’s the rest of it? Since they implement logic, do Prolog programs “reason” or are they just performing inference according to the SLD resolution algorithm?

> proper definition of reasoning must be provided

It will be related to the context. If a process tells me that "if the light is blue and the sound is sharp then the lever must be lowered", it outputs reasoning; if what the activity did was running on conditional paths like an Expert System, what it did was different from the content and only improper reasoning; if the activity produced semantic evaluations about the light, the blue, the sound, the sharpness, the lever etc., then it was reasoning even if it was a process that reasoned.

But all of this makes sense only when it is there for the proper implementation of reasoning. Otherwise, Dijkstra is valid.

> If a process tells me that "if the light is blue and the sound is sharp then the lever must be lowered", it outputs reasoning

By this definition, all computer programs using simple IF statements are reasoning.

You misread the post. Pls read it again.

> Frankly, I expect better analysis from Quanta.

Seriously? I agree with the rest of your comment but "better analysis" is not even remotely on brand for Quanta.

LOL, okay fair enough. Then maybe let me say that I was left disappointed.

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