Google TurboQuant reduces memory strain while maintaining accuracy across demanding workloads Vector compression reaches new efficiency levels without additional training requirements Key-value cache ...

In the early days of AI, the industry focused on building faster GPUs and scaling training infrastructure. Performance was largely measured by how quickly models could be trained and how much compute ...

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the model ...

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for ...