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.
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 ...
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