Even when I add multiple prompts into the claude.md file not to be so sycophant sounding and just be blunt, it's responses are full of "the reason it lands...", "that's not X, it's Y" "Your understanding of X — it's better than most people's" or "you already own the right question...".
replyI don't like that I like it.
The most helpful instructions I've found that curb this: "Do not use superlatives. Do not use persuasive writing style."
replyI have other more specific ones to avoid talking about things that it's not doing, but those two sentences have covered a lot of ground for me when working w/ Opus models.
I have had success in rooting these out by using the correct linguistic terminology for each. Negative parallelisms, tricolons/polycolons, etc. I haven't come up with the proper terminology for all of them.
replyInteresting. I've found using the keyword "accretion" very useful for LLM code review.
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replyYes! The Claudisms do seem to have this slightly uncanny clickbaity feel to them.
replyYou’re more right than you probably realize!
replyI always thought it could be because volume-wise, most English prose is probably marketing copy and actual clickbait; so when you train on the entire Internet, you get a troll adept at writing ads. Then people ask AdBot2000 to write a novel and are upset it reads like the next iPhone launch site.
replyNah, 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.
replyYes. This completely explains sycophancy at least.
replySo 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?
replyIt would require changing humans first.
replyYou don't blame the puddle for taking the shape of the hole.
replyThere's layers, some of token selection is fingerprinting https://github.com/google-deepmind/synthid-text
replyYeah, 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?
replySo "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.
No, there's no reason chatbot behavior would have anything to do with frequency of text in pretraining.
replyIt's more likely that this is from the training data if they're being trained on reams of Internet stuff.
replyTo me it has a writerly New Yorker vibe to it, as in the magazine which reads as “polished” and probably performs well in RL but is totally exhausting to read in long sessions and completely inappropriate for coding where precision is paramount above all. In writing terms its called purple prose.
replyThe New Yorker may be pretentious but it's generally not unreadable like Opus.
replyIsn’t most of the internet slop by now? Self-reinforcing feedback loop.
replySee: upvotes here
replyIt's not clickbait, it's automated empathy!
reply/s
Given how frequently this kind of punchy-but-vacuous slop gets voted onto the hn front page, the hacking seems to be working.
replyI assumed they just raw dogged the internet and if you do that, you see way more of that garbage than anything else. It's just that most of us have visually/mentally ignored all of that either via spam filters or just, you know, scrolled passed it.
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