Sub Byte

"Sub-byte" research explores efficient data representation and processing, primarily focusing on minimizing data size and computational cost in various applications. Current efforts concentrate on developing novel architectures like byte-level transformers and employing techniques such as sub-byte quantization and zeroth-order optimization to improve the performance of large language models and other machine learning tasks. This work has significant implications for resource-constrained environments, enhancing the efficiency and scalability of AI systems across diverse fields, from natural language processing and image recognition to memory forensics and cybersecurity.