You need to ground LLMs w/ Graphs Not Vectors for Enterprise AI, next part we will build one !
🔹 Businesses are increasingly turning to Generative AI for leveraging their wealth of knowledge and data. However, relying solely on language models may not provide a comprehensive understanding of internal data due to their reliance on public sources.
🔹 Enter RAG - a game-changer in enterprise AI! By combining data retrieval with language generation, RAG ensures more accurate and insightful responses to queries.
We all know this, but.... how you do RAG, using vectors ? if yes, keep reading !
💡 Let's explore how Graph-Based RAG addresses the shortcomings of vector-based retrieval
🔸 Vector-based methods face challenges. Graph-Based RAG offers a seamless solution by maintaining semantic relationships, supporting diverse data types, and facilitating efficient updates.
🔸 Imagine your data as a dynamic map, where each piece of information is a destination connected by meaningful pathways. With Graph-Based RAG, navigating through vast datasets becomes more intuitive and effective.
🔸 Looking ahead, Graph-Based RAG promises a smarter approach to data processing, enabling organizations to unlock valuable insights and drive innovation.
🌈 Ready to go on this exciting journey towards the future of enterprise AI? Let's connect and explore the limitless possibilities together! 🚀🔗
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