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.
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.
Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...
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