Small teams can now cheaply improve large AI models by freezing the core

Researchers found a way to update large AI models more cheaply and effectively. This means smaller teams can improve existing models without spending a lot of money or computing power.

Updating large AI models usually means retraining the whole thing, which costs a lot of money and computing power. This paper shows how to do it by only updating specific parts. This makes it much easier for smaller companies or research groups to customize powerful AI models for their specific needs.