# Attention and long context

> Why AI models pay more and more to read long text, the ways people cut that cost, how a tree of summaries searches a context, and how to judge the claims.

- [What is attention, and why does long text cost AI models so much?](https://learn.chabulab.com/ai/what-is-attention-and-why-it-costs.md): Click a word to see where attention looks back, then see why doubling the length of a text means four times the work.
- [What are the ways to stop a model rereading everything?](https://learn.chabulab.com/ai/ways-to-cut-attention-cost.md): Compare a sliding window, indexers and a tree on the same context, and see which forgets and which only moves the cost elsewhere.
- [How does a tree of summaries search a context? How ZHA works](https://learn.chabulab.com/ai/searching-context-with-a-tree-zha.md): Watch a question walk down a tree level by level, tune top-p, try random data, then run a small version in about 130 lines.
- [Should you trust a 400× speedup? Reading ZHA's results properly](https://learn.chabulab.com/ai/reading-zha-results-honestly.md): Separate what was measured from what was projected in the ZHA paper, see why deep trees lose attention, and take a checklist to the next paper.