Large Language Models, Llm, AI, Deep Learning, Machine Learning.
Sounds amazing, doesn’t it? but how actually it work? It has two stages: 1) caching This involves compressing the gradient vectors of each training data into a low-dimensional representation known as RapidGrad, significantly reducing their size to MBs or even KBs, making them suitable for storage.