Neural Network Comprehension
Tim and Connor discuss the concept of partitioning in neural networks through attention heads, highlighting the potential for faster learning in new tasks. They explore the idea of using consistent phrases to aid in task understanding and the role of embeddings in text comprehension.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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