It affects their ability to hire and retain talent.

If training a good model requires talent then that’s the answer to the question this thread is trying to answer: is training a good model actually that hard?

Talent to do.. what? This could mean a lot of things.

Navigating astronomically huge fundamentally not so hard but still really tangly and hairy projects requiring both excellent short- and long-term vision in an overheated domain with angry people and lots of money is a skill all of its own.

Talent to train high quality LLMs, especially coding LLMs.

Not true, aggressive post training makes models notably dumber.

Why would these be independent?

More specifically, political lobotomy shouldn’t affect coding ability.

You’d be quite surprised, I think. Fine tuning a model on one axis can have drastic impacts on another that as a human we would expect to be completely unrelated.

I have never seen anyone argue that this cannot be overcome with more high quality RLVR data.

The practical reality is that the Chinese and American models might have very different politics. But the most relevant factor in model performance is the quality and volume of training data, not ideology of the base model. Unless you are suggesting something very particular about the way Grok was neutered.

Yet empirically it does

It's all a bunch of weights isn't it? Why wouldn't fiddling with some parts of the weights have cascading effects?

> That shouldn’t affect Grok’ coding ability.

If you are spending all your time having to re-train because the boss doesn;t like the output, it will hamper coding