TurboQuant is a big deal, but it won’t end the memory crunch
… Instead it aims to reduce the amount of memory required to store the key value KV caches used to maintain context during LLM inference. …
… Instead it aims to reduce the amount of memory required to store the key value KV caches used to maintain context during LLM inference. …
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… Developed by Google's DeepMind team, the fourth generation of Gemma models brings several improvements, including "advanced reasoning" to improve performance in math and instruction-following, support for more than 140 languages, native function calling, and video and audio inputs. …
… "If your accuracy loss is too severe, the speed up becomes irrelevant," Salvator said. However, the FP4 data types supported by AMD and Nvidia's latest accelerators use some clever math to vastly expand the number of values that can represent model weights from 16 to more than 4,000. …