Number Representation

Number representation in computing and artificial intelligence is a crucial area of research focused on improving the efficiency and accuracy of numerical computations, particularly within resource-constrained environments and large language models. Current efforts explore alternative number systems, such as variations on floating-point and fixed-point arithmetic, and novel encoding schemes that incorporate mathematical priors or digit-level information to enhance numerical reasoning capabilities in machine learning models. These advancements are vital for optimizing performance in applications ranging from federated learning and network measurement to improving the numerical reasoning abilities of large language models and ensuring the reliability of AI systems in safety-critical domains.