Prompt Stuffing vs RAG: The Next Great AI Debate скачать в хорошем качестве

Prompt Stuffing vs RAG: The Next Great AI Debate

Super Bowl Halftime Show: Kendrick Lamar vs. Drake Rap Beef Analysis with AI In this episode of Tales from the Jar Side, host Ken Kousen dives into the anticipated Super Bowl halftime show featuring Kendrick Lamar and explores the infamous rap feud between Lamar and Drake. Using AI tools like GPT-4, Claude, Gemini, and Mistral within the LangChain4j framework, Ken attempts to retrieve detailed information on the beef, its escalation in 2024, and the likelihood of Lamar performing the controversial song 'Not Like Us' at the 2025 Super Bowl halftime show. He addresses challenges such as context window limits, prompt stuffing, and the application of RAG (Retrieval Augmented Generation) in analyzing large amounts of data. Join us for an insightful discussion combining AI, Java development, and one of hip-hop's biggest rivalries. 00:00 Super Bowl Halftime Show Introduction 00:40 Using AI Tools to Analyze the Feud 01:07 LangChain4j Framework Overview 01:43 Setting Up the FeudTest Class 02:08 Challenges with AI Training Data 03:15 Loading AI Models in Java 03:53 Running Initial AI Queries 06:37 Handling Context Window Limits 13:37 Using Jsoup for Text Extraction 15:21 Switching AI Models 19:02 Introduction to Retrieval Augmented Generation (RAG) 21:58 Implementing RAG with LangChain4j 24:36 Analyzing AI Model Responses 28:23 Conclusion and Final Thoughts