In the world of AI, who speaks for the trees?
Training large AI models to different tasks often requires adjusting millions—or even billions—of internal settings called parameters, using enormous amounts of computing power and energy. But Johns Hopkins computer scientists have developed a method that dramatically cuts the environmental costs of fine-tuning AI. They call it EigenLoRAx and, like the Dr. Seuss character, it’s a […]