1-BIT LLMS COULD SOLVE AI'S ENERGY DEMANDS

Summary from the TLDR newsletter

Large language models are demanding more and more energy and computational power as they get better. These models need to shrink to become cheap, fast, and environmentally friendly. Researchers use a process called quantization to compress networks by reducing the precision of their parameters. They are now pushing the envelope to single bit, producing models that are faster and more energy efficient than their full-precision counterparts. The quantized versions of the models perform almost as well as their original versions.