A new compression technique from Google Research threatens to shrink the memory footprint of large AI models so dramatically ...

Forward-looking: It's no secret that generative AI demands staggering computational power and memory bandwidth, making it a costly endeavor that only the wealthiest players can afford to compete in.

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 ...

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 ...

Intel is developing a new technology that can significantly reduce the size of game textures, helping save storage space and ...

SK Hynix, Samsung and Micron shares fell as investors fear fewer memory chips may be required in the future.

Video compression has become an essential technology to meet the burgeoning demand for high‐resolution content while maintaining manageable file sizes and transmission speeds. Recent advances in ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

Neural Texture Compression (NTC) optimized memory usage for either neural rendering or high-resolution texture and game data.