Researchers from MIT, the Improbable AI Lab, and ETH Zurich have developed a new fine-tuning technique to tackle a common problem in AI called “catastrophic forgetting.” This issue happens when models lose previously learned skills after being updated with new information. Their new method, called self-distillation fine-tuning (SDFT), aims to help models learn new tasks










