Low-Precision Computing refers to the use of reduced numerical precision in computations, such as using 16-bit or 8-bit numbers instead of the standard 32-bit. This approach significantly reduces the computational and memory requirements, making it ideal for training and deploying large models efficiently. For instance, training models in low precision on GPUs can lead to faster processing times and less energy consumption while maintaining performance.