I really did like the author's framing there, but I think there is a different, simpler way to put it:

Why would you think that asking someone else (that is, another human) to write something (and then reviewing it) is the same thing as writing it yourself?

You may trust the other writer's opinions and knowledge, but it will not have the same tone, structure, word choice, understanding, or narrative flow as it would if you were to write it yourself.

And when it's an LLM, you should not trust it's "opinions" and "knowledge", because it does not have either of those things. The appearance of those things is just that, an appearance.

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card_zero 3 hours ago | parent [-]

There's knowledge in books, and it's ingested all the books, so it does hold knowledge. But I guess that's not how you mean it.

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sethhochberg 3 hours ago | parent | next [-]

The key difference is that while an encyclopedia holds facts themselves, LLMs trained on that source material encode something more like a highly probable facsimile of those facts - the original fact was lost, LLMs are lossy, but can often be generated again with a decent level of accuracy by churning through stats about words, concepts, and relationships between them.

The whole catch is that they can often be regenerated. But LLMs (on their own, in their parametric memory - which is the result of training) don't have any conception of whether what they've generated is a real reproduction of some training material or whether they've invented something false that seemed probable based on their encoded stats. When the probability produces something contrary to what was in the training material, you get hallucinations.

They're very, very good predictive text models and can be very, very powerful when hooked up to other tools or outside databases. But its fundamentally lossy technology and all the books having been fed in doesn't guarantee all of the knowledge from those books can be spat back out.

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zmgsabst 2 hours ago | parent [-]

Your criticism of LLMs also applies to humans and so implies humans don’t possess knowledge.

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JanNash an hour ago | parent [-]

Humans can learn texts by heart, even lots of text (I have some expertise on that, having studied opera singing). They can reproduce these texts accurately, deterministically and repeatably. An LLM is a statistical machine. It does not know any text by heart and it is by pure chance that it sometimes reproduces existing texts verbatim.

	▲	copperx 35 minutes ago \| parent \| next [-]
		Ant tips for doing so? I've never been able to do that, even as a kid. I remember the meaning but not the exact words.
	▲	kjshsh123 16 minutes ago \| parent \| prev [-]
		Humans sometimes don't remember things 100%. LLMs can produce certain text and be run deterministically. I don't really understand this side of the debate other than as a gotcha tbh. If LLM use atrophies your brain and skills that's bad. If it has a repulsive writing style that's bad. I'm not sure what the debate about whether an AI is a statistical parrot unlike humans accomplishes. Is relying 100% on a bad human speechwriter somehow better?

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jvanderbot 3 hours ago | parent | prev | next [-]

It's funny. I always thought that writing was meant to inform, persuade, or entertain about the subject at hand.

But in professional settings, a lot more of the informativeness is about the author, and a lot more of the persuasiveness is I'm worth your time and money. So, if the author is an LLM, and obviously so, what exactly are you informing your audience of (about yourself), and what are you persuading them to do (with your article).

I think we now know.

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mohamedkoubaa 2 hours ago | parent | prev [-]

It doesn't hold knowledge it has the ability to seive through a lossy latent representation of knowledge.