Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in ...

A more efficient method for using memory in AI systems could increase overall memory demand, especially in the long term.

TurboQuant significantly increases capacity and speeds up key-value cache (KV cache) in AI inference. KV-cache is a type of ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in which the probabilities of tokens occurring in a specific order is ...

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 ...

Google’s TurboQuant cuts AI memory use by 6x and speeds up inference. But will it cause DRAM prices to drop anytime soon? Let ...

As AI workloads extend across nearly every technology sector, systems must move more data, use memory more efficiently, and respond more predictably than traditional design methodologies allow. These ...