> I'm curious how much trained in bias damages in-context performance. I think there's an example right in front of our faces: look at how terribly SOTA LLMs p

> I'm curious how much trained in bias damages in-context performance. I think there's an example right in front of our faces: look at how terribly SOTA LLMs perform on underrepresented languages and frameworks. I have an old side project written in pre-SvelteKit Svelte. I needed to do a dumb little update, so I told Claude to do it. It wrote its code in React, despite all the surrounding code being Svelte. There's a tangible bias towards things with larger sample sizes in the training corpus. It stands to reason those biases could appear in more subtle ways, too.