Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...
The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...
FriendliAI also offers a unique take on the current memory crisis hitting the industry, especially as inference becomes the dominant AI use case. As recently explored by SDxCentral, 2026 is tipped to ...
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