AI & Enterprise
KAIST, Korea University develop knowledge transfer technique between AI models
KAIST said on Jan. 27 that a research team led by Hyunwoo Kim (김현우) jointly with a Korea University team developed a technique to transfer learned knowledge between different AI models. The team proposed TransMiter, a transferable adaptation method that reuses adaptation experience across models regardless of structure or size. It transfers know-how based on prediction results, avoiding repeated, time-consuming training and limiting slowdowns.
