Metadata
- Author: Doug Turnbull
- Full Title:: What AI Engineers Should Know About Search
- Category:: 🗞️Articles
- URL:: https://softwaredoug.com/blog/2024/06/25/what-ai-engineers-need-to-know-search?utm_source=substack&utm_medium=email
- Finished date:: 2024-06-30
Highlights
Search comes with a precision / recall tradeoff. If you cast a wide net, you’ll get more relevant results in the mix, but also likely be showing the users lots of irrelevant ones too! (View Highlight)
New highlights added 2025-05-07
• The fanciest solutions don’t matter as much as getting a good evaluation framework setup to evaluate the quality of search results (View Highlight)
A lot of metrics exist for measuring the quality of a query - if query “zoolander” returns some search results, we can reference the judgments, to see whether or not we gave relevant results. Statistics like (n)DCG, ERR, MAP, Precision, Recall, F-Score are well understood in the search industry (View Highlight)
There are tools to compute the “true” specificity of a term beyond direct IDF, such as blending IDF across fields, or merging all the text into one big field. (View Highlight)