Demystifying LLM Context Windows: How AI Memory Works (and Why It Fails)
中文摘要
这篇文章深入解析了大语言模型的上下文窗口，探讨了Token、自注意力机制的二次方缩放以及“迷失在中间”等内存运作原理及其局限性。
English Summary
This guide explains LLM context windows, covering tokens, self-attention quadratic scaling, and the "Lost in the Middle" phenomenon to reveal how AI memory works and fails.
原文节选
A comprehensive guide from tokens and contextual embeddings to self-attention quadratic scaling and the “Lost in the Middle” retrieval… Continue reading on Medium »