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Will KAG surpassed RAG? KAG [Knowledge Augmented Generation] Architecture and Working Explained
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Learn RAG from Scratch - Will KAG surpassed RAG? KAG [Knowledge Augmented Generation] Architecture and Working Explained

Master RAG & Build 9 Real-World GenAI Projects from Scratch

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19 learners

What you'll learn

Explain the core concepts of RAG and why it mitigates LLM hallucinations.
Implement text chunking and create vector embeddings for a RAG pipeline.
Build a functional RAG system using LangChain, a vector database, and an LLM.
Deploy a RAG application with a user interface for document-based question answering.

This course includes

  • 2.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

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Full Transcript

Welcome to our channel! In this video, we dive into KAG (Knowledge Augmented Generation), a powerful AI framework designed for logical form-guided reasoning and information retrieval. Developed by OpenSPG, KAG leverages cutting-edge techniques to enhance data-driven decision-making and knowledge synthesis. Whether you're a researcher, developer, or enthusiast in AI technology, this video provides an insightful overview of KAG's capabilities and its potential applications. 🔗 GitHub - https://github.com/OpenSPG/KAG 🔗 Explore KAG on GitHub: KAG GitHub(GitHub - OpenSPG/KAG: KAG is a logical form-guided reasoning and retrieval framework based on OpenSP) 📄 Read the full paper on KAG: KAG Paper(https://arxiv.org/pdf/2409.13731) #KAG #OpenSPG Don't forget to like, subscribe, and hit the bell icon for more updates on AI innovations and tools like KAG. Join us as we delve deeper into the future of AI and its transformative impact on various industries. Thank you for watching!" Feel free to adjust the description to better fit your channel's style or any specific details you'd like to highlight about KAG. Join this channel to get access to perks: https://www.youtube.com/channel/UC4RZP6hNT5gMlWCm0NDzUWg/join Don’t forget to: Like this video, subscribe to the channel and Comment your thoughts or questions To get the Source Code, Follow me on GitHub: https://github.com/simranjeet97/ Book your call with me at topmate.io and learn how to harness the latest technologies power and speed up your learning process. Book your call at https://bit.ly/43TLDCD Follow me on Medium for the latest blogs and projects: https://bit.ly/3JGXqwc Playlists that make you skilled up 1. GenAI Full Course with LLM Fine Tuning and Evaluation: https://bit.ly/4bJwZla 2. Learn RAG from scratch with GenAI projects: https://bit.ly/3Zl47KD 3. Latest AI/GenAI Research Papers Explained: https://bit.ly/4huqEMT 4. RAG and LLM Use Cases in Finance Domain Projects: https://bit.ly/3AGSRQm 4. Prompt Engineering: https://bit.ly/42v376M 5. Financial Data Analysis and Financial Modelling: https://bit.ly/3OCWI5O 6. Artificial Intelligence Projects: https://bit.ly/3L8lhEi 7. Predict IPL 2023 Winner (End to End Data Science Project): https://bit.ly/3BfC3N9 8. Explainable AI (XAI) Machine Learning: https://bit.ly/3gsuIxb 9. Face Recognition: https://bit.ly/2YphpHm Youtube Tags: genai projects, Generative ai projects, genai project, generative ai project, KAG, Knowledge Augmented Generation, AI reasoning, logical form-guided reasoning, AI retrieval framework, OpenSPG, machine learning, deep learning, AI research, artificial intelligence, AI frameworks, natural language processing, NLP, AI tools, retrieval-augmented generation, RAG, large language models, LLMs, AI development, knowledge-based AI, AI for research, AI applications, AI innovations, AI technology, AI tutorial, AI walkthrough, KAG tutorial, OpenSPG KAG, KAG framework, AI knowledge retrieval, AI-enhanced reasoning, AI-powered retrieval, generative AI, AI knowledge synthesis, AI decision making, AI models, AI logic, AI and reasoning, AI research tools, machine learning research, KAG demo, AI framework tutorial, open-source AI, AI retrieval methods, AI and NLP, AI advancements, AI paper summary, AI code walkthrough, AI model implementation.

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