Testing Generative AI: Guide to Evaluation & QA Frameworks

Description

How do you test software that gives a different answer every time? 🤔 In this video, we explore the emerging field of Generative AI Quality Assurance. We break down the differences between deterministic and probabilistic testing, explore key metrics like Hallucinations and Faithfulness, and introduce the RAG Triad for evaluating retrieval systems. We also cover: ✅ Human Evaluation vs. LLM-as-a-Judge ✅ Top Frameworks: RAGAS, DeepEval, Promptfoo ✅ Red Teaming and Security Testing ✅ How to build a Golden Dataset Ensure your LLM applications are production-ready with these testing strategies! 🚀 #GenerativeAI #LLM #QualityAssurance #AIValidation #RAG #MachineLearning #TechEducation Chapters: 00:00 - Introduction to GenAI Testing 00:19 - The Challenge: Deterministic vs Probabilistic 00:45 - Key Testing Metrics 01:09 - Evaluation Methods: Human vs. AI 01:32 - The RAG Triad 01:53 - Popular Frameworks 02:14 - Red Teaming and Security 02:31 - The Golden Dataset 02:51 - Best Practices Checklist 03:11 - Conclusion 03:29 - Outro 🔗 Stay Connected: ▶️ YouTube: https://youtube.com/@thecodelucky 📱 Instagram: https://instagram.com/thecodelucky 📘 Facebook: https://facebook.com/codeluckyfb 🌐 Website: https://codelucky.com ⭐ Support us by Liking, Subscribing, and Sharing! 💬 Drop your questions in the comments below 🔔 Hit the notification bell to never miss an update #CodeLucky