{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"Self-Attention — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"<div style=\"font-family:sans-serif;border:1px solid #e0e0e0;border-radius:8px;padding:16px;max-width:600px;background:#ffffff;color:#111111;\"><p style=\"margin:0 0 4px;font-size:11px;color:#666;\">AI Glossary — gaks.ai</p><h3 style=\"margin:0 0 8px;font-size:16px;\">Self-Attention</h3><p style=\"margin:0 0 12px;font-size:14px;line-height:1.6;\">A mechanism in which each element of a sequence attends to every other element in the same sequence, allowing the model to capture relationships and dependencies regardless of distance. Self-attention is the defining operation of the transformer architecture. It's what enables a language model to understand how any word in a sentence relates to any other word across the full context window simultaneously, rather than processing text in a fixed local window.  See also: attention mechanism, transformer.</p><a href=\"https://gaks.ai/glossary/self-attention\" style=\"font-size:12px;color:#0077aa;\">Source: gaks.ai/glossary/self-attention →</a></div>"}