Wikipedia has an excellent article about identifying AI-generated text. It calls that particular pattern "Negative parallelisms". https://en.m.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writin...
The really funny thing is, I'll probably miss that tell when it's gone, as every AI company eventually scrubs away obvious blemishes like that from their flagship models.
Interestingly, there are still many other good literary devices that are not yet used by AI - for example, sentences of varying lengths. There is still scope for a good human editor to easily outdo LLMs... but how many will notice? Especially when one of the editorial coloumns in the NYT (or Atlantic, forgot exactly) is merrily using LLMs in the heartfelt advice coloumn. It's really ironic, isn't it? ;)
LLMs are also great at following style, not via criteria but via examples. So this is something that’s easily overcome.
I discovered this when I made an error in a creative writing tool I was working on. I told it to follow the writing style of existing story text, but it ended up making the system messages follow the same style. It was quite amusing to see tool messages and updates written in an increasingly enthusiastic Shakespearean/etc prose (so I left it unfixed!)
It's basically saying: LLMs are not structured like databases, their knowledge is not localized. In a database, a fact lives in a specific place; cut that out, lose the fact. In an LLM, every thing the model learned in training is smeared across the entire network; cut out a small piece, and not much is lost.
As a crude analogy, think of a time vs. frequency domain representation of a signal, like a sound or an image. The latter case is particularly illustrative (!). Take a raster image, pick a pixel. Where is the data (color) of that pixel located in the Fourier transform of the image? A little bit in every single pixel of the transformed image. Conversely, pick a block of pixels in the Fourier transform, blank them out, and transform back to "normal" image - you'll see entire image got blurred or sharpened, depending on which frequencies you just erased.
So in terms of data locality, a database is to an LLM kinda what an image is to its Fourier transform.
(Of course, the other thing the sentence is trying to communicate is, LLMs are not (a different representation of) databases - they don't learn facts, they learn patterns, which encode meanings.)
I think it's kinda ironic (in a more meta Alanis Morissette way) for such an article that has interesting content to default to have an LLM write it. Please, I request authors - you're better than this, and many people actually want to hear you, not an LLM.
For example, what really is the meaning of this sentence?
> These aren't just storage slots for data, they're the learned connections between artificial neurons, each one encoding a tiny fragment of knowledge about language, reasoning, and the patterns hidden in human communication.
I thought parameters were associated with connections, is the author implying that they also store data? Is the connection itself the stored data? Is there non-connective information that stores data? Or non-data-storage things that have connectivity aspects?
I spent a solid amount of time trying to understand what was being told, but thanks to what I would call a false/unnecessary "not just x but y" troupe, I unfortunately lost the plot.
IMO, a human who's a good writer would have a sentence that's clearer to understand, while non advanced writers (including me, almost certainly) would simply degrade gracefully to simpler sentence structure.