Discover how self-attention powers large language models. Learn the query-key-value mechanism, multi-head attention, and why transformers outperform RNNs in understanding context.
Sinusoidal and learned positional encodings were early solutions for transformers, but modern LLMs now use RoPE and ALiBi for better long-context performance. Learn why and how these techniques evolved.