Transcript
0:00 If you're building AI that searches through documents, here's a quick way to test it without writing hundreds of test questions or labeling a bunch of examples by hand. What you want to do is flip the problem. Point an AI at each document and say, "Make up a plausible question that only this document can answer." Now you've got a question paired with a document it came from. You can now feed that question back into your search and measure, "Did it find the right document?" You just turned a hard problem, which is having a bunch of labeled data, into a much easier one.
0:30 Now, this won't catch everything and it isn't a perfect test, but it's a fast and easy test that surfaces big problems and it's a really high return on investment given the amount of effort it takes. If you want to learn more techniques like this, I left some additional resources in the comments.
Summary
- Generate plausible questions from each document to create question-document pairs.
- Use these pairs to test the AI's ability to retrieve the correct document based on the generated question.
- This method reduces the need for extensive manual labeling of data.
- While not exhaustive, it effectively identifies significant issues in the AI's performance.
- The approach is quick and offers a high return on investment in terms of effort versus results.
- Additional resources for similar techniques are available in the comments for further exploration.