In the eighties, computer processors became faster and faster, while memory access times stagnated and hindered additional performance increases. Something had to be done to speed up memory access and ...

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 ...

TurboQuant compresses AI’s KV cache by 6x – but cheaper inference historically expands total demand, not shrinks it, a dynamic known as the Jevons Paradox. The selloff in SanDisk and Seagate is ...

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 ...

Google AI has introduced a major breakthrough with TurboQuant, a system that reduces KV cache memory usage by up to 6x while improving chatbot efficiency during real-time conversations. This allows AI ...

Gain insight into the CXL specification. Learn how CXL supports dynamic multiplexing between a rich set of protocols that includes I/O (CLX.io, based on PCIe), caching (CXL.cache), and memory (CXL.mem ...