Pyramid Attention Explained: How Transformers Scale to Long Contexts Faster | Structural efficiency

Pyramid Attention is a hierarchical attention mechanism designed to make Transformers more efficient and scalable. Instead of attending to every token at full resolution, Pyramid Attention processes information at multiple scales — coarse to fine — dramatically reducing memory and compute costs. In this video, you’ll learn: • Why standard attention becomes expensive • What hierarchical / multi-scale attention means • How Pyramid Attention builds coarse-to-fine representations • Why it helps with long context and high-resolution inputs • Where it’s used in vision and language models If you're…