Скачать с ютуб AI Engineering Insights from Chip Huyen’s Book | Chapter 3: Mastering AI Evaluation Methods в хорошем качестве

AI Engineering Insights from Chip Huyen’s Book | Chapter 3: Mastering AI Evaluation Methods

Evaluating foundation models is crucial for their success in real-world applications! In this video, I share insights from 𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝟯 of Chip Huyen’s book, 𝘈𝘐 𝘌𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘪𝘯𝘨: 𝘉𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘈𝘱𝘱𝘭𝘪𝘤𝘢𝘵𝘪𝘰𝘯𝘴 𝘸𝘪𝘵𝘩 𝘍𝘰𝘶𝘯𝘥𝘢𝘵𝘪𝘰𝘯 𝘔𝘰𝘥𝘦𝘭𝘴, focusing on how to effectively evaluate AI models. 📌 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀: ✅ Challenges in evaluating open-ended, subjective AI outputs ✅ Key language modeling metrics: Entropy, embeddings, and AI as a judge ✅ Automating AI evaluation with functional correctness and similarity scores ✅ How to design a systematic evaluation pipeline for AI systems ✅ Why human evaluation remains essential, even with automated methods ✅ Best practices for domain-specific and continuous evaluation 📢 𝗗𝗶𝘀𝗰𝗹𝗮𝗶𝗺𝗲𝗿: This video is based on my personal interpretation of the book and is not an official summary. 🚀 Understanding AI evaluation is key to ensuring foundation models perform reliably and effectively. Don’t miss out—watch now and learn how to master AI evaluation! 🔔 𝗦𝘁𝗮𝘆 𝘁𝘂𝗻𝗲𝗱 𝗳𝗼𝗿 𝗖𝗵𝗮𝗽𝘁𝗲𝗿 𝟰 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗻𝗲𝘅𝘁 𝘀𝗲𝘀𝘀𝗶𝗼𝗻! Subscribe for more AI & software architecture insights! #AIEngineering #MachineLearning #ArtificialIntelligence #AIevaluation #SoftwareArchitecture #ChipHuyen #AIModelEvaluation