This paper introduces BitNet a4.8, a new way to make large language models (LLMs) work faster and use less memory. Imagine LLMs as really smart computer programs that can understand and write like humans. They use tons of data, which can make them slow and expensive to run. BitNet a4.8 makes them more efficient by using a clever trick: instead of storing all the information in full detail, it selectively uses less information for some parts of the data, kind of like summarizing a long book. It focuses on keeping the most important details, which are represented by numbers, and simplifies or removes less important ones. This makes the model smaller and faster without losing much accuracy. This is like reading a shorter version of a story that still tells you everything you need to know. BitNet a4.8 even allows for further compression of the model's memory, which is like shrinking that shorter story even more without losing any of the important plot points.

https://arxiv.org/pdf/2411.04965