The Google Research team developed TurboQuant to tackle bottlenecks in AI systems by using "extreme compression".
Morning Overview on MSN
Google says TurboQuant cuts LLM KV-cache memory use 6x, boosts speed
Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in large language models to 3.5 bits per channel, cutting memory consumption ...
The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI chatbots. The cache grows as conversations lengthen, ...
Micron Technology and Sandisk stocks have been dented and TurboQuant could be one of the reasons.
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