Google Research unveiled TurboQuant, a novel quantization algorithm that compresses large language models’ Key-Value caches by up to 6x. With 3.5-bit compression, near-zero accuracy loss, and no ...

Prompt caching has become a vital strategy for managing the rising costs of large language model (LLM) operations. By reusing previously computed data, this approach minimizes redundant computations, ...

Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in large language models to 3.5 bits per channel, cutting memory consumption ...

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working ...

A new technical paper titled “Accelerating LLM Inference via Dynamic KV Cache Placement in Heterogeneous Memory System” was published by researchers at Rensselaer Polytechnic Institute and IBM. “Large ...

DDN added new capabilities to the Lustre platform it manages with Google Cloud, including means to share key-value (KV) cache to boost AI inference workloads. Unveiled at Google’s annual Next event, ...