Quantizing the AI Colossi

Streamlining Giants Part 2: Neural Network Quantization

In recent years, a powerful alliance has been forged between the transformer neural network architecture and the formulation of various problems as self-supervised sequence prediction tasks. This union has enabled researchers to train large foundation models of unprecedented sizes using massive troves of unlabeled sequential data, and these models have shown uncanny emergent capabilities that closely mimic human-level intelligence in several domains. With newfound heights of …

architecture author computer vision dall dall-e deep learning editors pick foundation llm massive network network architecture neural network part prediction quantization researchers tasks train transformer union