This does not contradict what I said.
> In what sense is the article dismissive? What, exactly, is it dismissive of?
Consider the following direct quotes:
> It’s like having the world’s most educated parrot: it has heard everything, and now it can mimic a convincing answer.
or
> they generate responses using the same principle: predicting likely answers from huge amounts of training text. They don’t understand the request like a human would; they just know statistically which words tend to follow which. The result can be very useful and surprisingly coherent, but it’s coming from calculation, not comprehension
I believe these examples are self-evidently dismissive, but to further put it into words, the article - ironically - rides on the idea that there's more to understanding then just pattern recognition at a large scale, something mystical and magical, something beyond the frameworks of mathematics and computing, and thus these models are no true scotsmans. I wholeheartedly disagree with this idea; I find the sheer capability of higher level semantic information extraction and manipulation to be already a clear and undeniable evidence of an understanding. This is one thing the article is dismissive of (in my view).
They even put it into words:
> As impressive as the output is, there’s no mystical intelligence at play – just a lot of number crunching and clever programming.
Implying that real intelligence is mystical, not even just in the epistemological but in the ontological sense, too.
> But here at Zero Fluff, we don’t do magic – we do reality.
Please.
It also blatantly contradicts very easily accessible information on how a typical modern LLM works; no, they are not just spouting off a likely series of words (or tokens) in order, as if they were reciting from somewhere. This is also a common lie that this article just propagates further. If that's really how they worked, they'd be even less useful than they presently are. This is another thing the article is dismissive of (in my view).