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. Every time a model like Gemini or GPT-4 processes a long document or sustains a ...
In the eighties, computer processors became faster and faster, while memory access times stagnated and hindered additional performance increases. Something had to be done to speed up memory access and ...
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