Algorithms That Run AI and How to Use It in Testing
summary
Covers four concrete uses: spidering agent that crawls a site and trains a neural policy with perceive‑act‑observe steps (agent repo linked), natural‑language code generation via cursor.sh and Selenium Python that produces runnable scripts, semantic matching with cosine scores shown (1.0 and 0.60), visual diffs using OpenCV and NumPy that highlight missing text/values, and test‑data synthesis using Transformers (distilroberta‑base fill‑mask yields “Paris”) plus GPT‑3.5 for sample lists; demos run but generated tests and code need review and maintenance.
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chapters (6)
- 0:00Intro
- 1:18What is Artificial Intelligence
- 2:31Discovery of New Test
- 5:17Action Logic Creation
- 9:33Visual Testing
- 12:16Test Data Generation
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