Part of the problem is that AI has been trained on all text, not just the internet but scientific papers and books of all varieties. AI style is almost certainly the average of that style approach but we use very different styles for different writing and getting it wrong grates, and AI doesn't seem to deal with these style differences well at all.
Thats the training data, but i dont think thats the biggest factor in the tone. I think its the RLHF. This thing has been guided by silicon valley techbros so it tlaks like them. Even claudes latest style of trying to cram as much information into as little space as possible by nouning verbs and just creating adhoc jargon, is how alot engineers (including me) actually talk. I think they just guided it towards that and overfit on it
I’d echo this. You can see it with other, perhaps lesser, models: GLM5.3 and Deepseek 4.1 have such a recognisably “Claude”-sounding patter I’d have (ill-informedly) SWORN I was using an Anthropic model.
If you’re distilling output from a frontier model, as we expect the open-weight leaders to be doing, it’s natural you’d pick up the language styles.
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If you’re distilling output from a frontier model, as we expect the open-weight leaders to be doing, it’s natural you’d pick up the language styles.