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Optimizing AI Inference with Hardware Innovations
This chapter explores innovative hardware architectures tailored for AI inference, focusing on large-scale language models. It highlights techniques like quantization and sparsity that enhance computational efficiency while discussing collaborations for transforming pre-trained models into sparse forms. The chapter also addresses advanced optimization methods and their impact on deployment across various hardware platforms, promoting open-source insights for broader industry application.