How Modern LLMs Actually Get Fast | LLM Efficiency

This series is about LLM efficiency. Not just how Transformers work… But how they scale. In this playlist, we’ll break down: Why attention is quadratic? How KV Cache avoids recomputation? How FlashAttention reduces memory bottlenecks? How Pyramid Attention handles long inputs? How speculative decoding cuts latency? And how sparse models get bigger without getting slower?