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Tag General LLM retrieval-augmented generation

Anthropic’s Contextual RAG and Hybrid Search

Anthropic RAG
Imagine an AI that's not just informative but super-smart, remembering where it learned things! This is Retrieval Augmented Generation (RAG), and Anthropic is leading the charge with a revolutionary approach: contextual retrieval and hybrid search. Forget basic keyword searches - Anthropic's AI understands the deeper meaning of your questions, providing thoughtful and relevant answers. This paves the way for smarter customer service bots, personalized AI assistants, and powerful educational tools. Dive deeper into the future of AI with this blog post! Contextual RAG

Retrieval Augmented Generation: RAGatouille

Retrieval-Augmented Generation: RAGatouille
This engaging excerpt dives into RAGatouille, a groundbreaking open-source project that simplifies building powerful AI systems. It combines information retrieval and generation, allowing you to create applications that answer questions, retrieve documents, and even generate content – all efficiently and accurately.Ready to explore the exciting world of Retrieval-Augmented Generation? Dive into the full guide and unlock the potential of AI for your projects!

Boost LLM’s RAG Performance with Chunking!

Embedding Models: for RAG with OpenAI, Cohere, Google, E5, and BGE
Boost AI Performance with Chunking!This powerful technique breaks down complex information for AI, leading to smarter responses in chatbots, question-answering systems, and more. Discover how chunking unlocks the true potential of RAG architectures.Dive in and unlock the future of AI!