Making data transfer in LLM systems faster, leaner, and more scalable

Data transfer in large language model (LLM) systems, particularly for Retrieval-Augmented Generation (RAG), presents a significant bottleneck due to the inefficiency of formats like JSON. To address this, a new binary serialization format has been developed to make data transfer faster, leaner, and more scalable. This format significantly reduces the size of data payloads, which translates to improved performance and lower costs for applications that handle large volumes of documents and embeddings. Cohere has integrated this binary format directly into its Python SDK, allowing developers to easily leverage these efficiency gains when building AI systems.