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.

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

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.

> 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.