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Anon1096 11 hours ago

Nah, I think this is a common misunderstanding of how LLMs work, where people think that they mimic the pre-training data. Stylistically everything you see is an artifact of post-training, which is from reinforcement learning not from absorbing mass amounts of text. At some point a person or more recently a bot gave a thumbs up to an A/B tested response including em-dashes and claudisms galore.

kridsdale1 11 hours ago | parent | next [-]

Yes. This completely explains sycophancy at least.

ModernMech 11 hours ago | parent | prev | next [-]

So question then, why is it so hard to make an ai that doesn’t do these things? And why do Claude and ChatGPT have the same -isms? They’re both doing the same a/b post training with the same decisions?

cyclopeanutopia 10 hours ago | parent | next [-]

It would require changing humans first.

idiotsecant 6 hours ago | parent | prev [-]

You don't blame the puddle for taking the shape of the hole.

avereveard 10 hours ago | parent | prev [-]

There's layers, some of token selection is fingerprinting https://github.com/google-deepmind/synthid-text

ekidd 9 hours ago | parent [-]

Yeah, but I understand that fingerprinting is essentially a pseudorandom overlay onto a pseudorandom base signal. And unless you have access to both the random number generators and the weights, I don't think you can detect it?

So "fingerprinting" operates on a totally different and basically invisible level, as opposed to the obvious stylistic patterns that the average programmer can identify in about 2 sentences.