VerTQ is an accelerator chip that implements Google's TurboQuant algorithm which reduces KV cache memory usage of Large ...
Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.
Morning Overview on MSN
Google’s TurboQuant algorithm slashes the memory bottleneck that limits how many AI models can run at once
Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation.
Caching algorithms Resources stored in the cache require memory. If these resources are not used for a long time, holding on to them proves inefficient. Because the cache’s capacity is limited, when ...
Part 2 looks at the tradeoffs between program and data cache optimizations, and shows how to choose the best compromise. As we saw in the first two parts of this series, cache optimization is often ...
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 ...
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