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 ...
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Neuromorphic Spike-Based Large Language Model (NSLLM): The next-generation AI inference architecture for enhanced efficiency and interpretability
Recently, the team led by Guoqi Li and Bo Xu from the Institute of Automation, Chinese Academy of Sciences, published a ...
Quantization is a method of reducing the size of AI models so they can be run on more modest computers. The challenge is how to do this while still retaining as much of the model quality as possible, ...
The shaping of light using spatial light modulators (SLMs) is an established technology for advanced three-dimensional (3D) displays 1 and micro-manipulation 2. In the SLM an incident beam of coherent ...
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