Learn how to tackle the out-of-context chunk issue in Retrieval-Augmented Generation (RAG) systems. Discover techniques like contextual chunk headers and dynamic chunk segmentation to improve retrieval accuracy and prevent hallucinations. Watch to explore practical solutions and examples from dsRAG, an open-source retrieval engine. ☎️ Do you need any career or technical help? Book a call with me: https://calendly.com/mg_cafe Code used in this video is in Discord Channel under References: https://discord.gg/2kcjQFMCr5 ******************* LET'S CONNECT! ******************* Join Discord Channel: https://discord.gg/2kcjQFMCr5 ✅ You can contact me at: LinkedIn: https://www.linkedin.com/in/mohammad-ghodratigohar/ Email: mo.ghodrati95@gmail.com Twitter: https://twitter.com/MG_cafe01 🔔 Subscribe for more cloud computing, data, and AI analytics videos by clicking on the subscribe button so you don't miss anything. #RAG #Chunking #LLM

1 Prompt Hacked My Claude Code Agent
265 views

Google Stitch MCP Just Made Claude Code 10x Better
4.5K views

Stop Paying for GPT-5 — This $0 Agent Beats It
485 views

Build Claude Skills That Test & Fix Themselves (Demo)
349 views

Google Proved Longer AI Thinking = Worse Answers
472 views

MIT Made AI That Never Forgets
202 views