What if the future of artificial intelligence wasn’t about building bigger, more complex models, but instead about making them smaller, faster, and more accessible? The buzz around so-called “1-bit ...
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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 ...
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 ...
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 ...
Today LeapMind announced Efficiera, an ultra-low power AI inference accelerator IP for companies that design ASIC and FPGA circuits, and other related products. Efficiera will enable customers to ...
INT8 provides better performance with comparable precision than floating point for AI inference. But when INT8 is unable to meet the desired performance with limited resources, INT4 optimization is ...
Today LeapMind announced Efficiera, an ultra-low power AI inference accelerator IP for companies that design ASIC and FPGA circuits, and other related products. Efficiera will enable customers to ...
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