Sakana AI develops new memory optimization for language models
Tokyo-based startup Sakana AI has created a breakthrough technique that reduces memory usage in large language models by up to 75%. As reported by Ben Dickson, the system called “universal transformer memory” uses neural attention memory modules (NAMMs) to efficiently manage information processing. These modules analyze the model’s attention layers to determine which information to …