[Market Trends] Building Multimodal AI RAG with LlamaIndex, NVIDIA NIM, and Milvus | NVIDIA Developer

π Constructing a Cutting-Edge Multimodal AI Chatbot with NVIDIA Tools
This video tutorial demonstrates how to construct a multimodal AI chatbot using NVIDIA's GPU-accelerated models and open-source tools. It covers setting up a vector database, generating embeddings, and employing NVIDIA NeMo for data curation and safety. The system utilizes Retrieval Augmented Generation (RAG) to access external data, enhancing response accuracy. Vision Language Models handle visual data, integrating images into text-based processing. The implementation leverages NVIDIA's NIM API and LLaMA Index for efficient querying and response generation, with Streamlit creating a user-friendly interface for document uploads and real-time question answering.