Advanced RAG with Multi-Media RAG

- Advanced RAG Reranker Training & Triplet Fundamentals - Learn contrastive loss vs triplet loss approaches for training retrievers - Understand tri-encoder vs cross-encoder performance trade-offs - Master triplet-loss fundamentals and semi-hard negative mining strategies - Fine-tune rerankers using Cohere Rerank API & SBERT (sbert.net, Hugging Face) - Multimodal & Metadata RAG - Index and query images, tables, and structured JSON using ColQwen-Omni (ColPali-based late interaction for audio, video, and visual documents) - Implement metadata filtering, short vs long-term indices, and query routing logic - Cartridges RAG Technique - Learn how Cartridges compress large corpora into small, trainable KV-cache structures for efficient retrieval (~39x less memory, ~26x faster) - Master the Self-Study training approach using synthetic Q&A and context distillation for generalized question answering - Cartridge-Based Retrieval - Learn modular retrieval systems with topic-specific "cartridges" for precision memory routing - Late Interaction Methods - Study architectures like ColQwen-Omni that combine multimodal (text, audio, image) retrieval using late interaction fusion - Multi-Vector vs Single-Vector Retrieval - Compare ColBERT/Turbopuffer vs FAISS, and understand trade-offs in granularity, accuracy, and inference cost - Query Routing & Hybrid Memory Systems - Explore dynamic routing between lexical, dense, and multimodal indexes - Loss Functions for Retriever Training - Compare contrastive loss vs triplet loss, and learn about semi-hard negative mining - Reranker Tuning with SBERT or APIs - Fine-tune rerankers (SBERT, Cohere API), evaluate with MRR/nDCG, and integrate into retrieval loops - Exercises: Advanced RAG Techniques - Implement triplet loss vs contrastive loss for reranker training with semi-hard negative mining - Build multimodal RAG systems with images, tables, and query routing - Compare single-vector (FAISS) vs multi-vector (ColBERT) retrieval - Create cartridge-based RAG with topic-specific memory routing