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Making Neural Networks Smaller: Quantization and Pruning | PrismML
Quantization in deep learning | Deep Learning Tutorial 49 (Tensorflow, Keras & Python)
Quantization vs Pruning vs Distillation: Optimizing NNs for Inference
How LLMs survive in low precision | Quantization Fundamentals
Quantization explained with PyTorch - Post-Training Quantization, Quantization-Aware Training
Learning Highly Sparse Deep Neural Networks through Pruning and Quantization
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Last Updated: October 15, 2026
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This Tech Talk explores how to compress Qualcomm AI Research has been developing state-of-the-art [2026 - DAY 1 - INFERENCE SYSTEMS] Large language models are increasingly powerful but remain bottlenecked by memory, ... Are you planning to deploy a deep learning model on any edge device (microcontrollers, cell phone or wearable device)? Try Voice Writer - speak your thoughts and let AI handle the grammar: voicewriter.io Four techniques to optimize the speed ... In this video, we discuss the fundamentals of model In this video I will introduce and explain Presentation for 11-785 final project on: Learning Highly Sparse Deep Ian Colbert, AMD, AI Research Staff About the Speaker: Ian Colbert is an AI Research Staff at Advanced Micro Devices (AMD), ...