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As AI evolves, the choice isn't just between supermassive context windows and retrieval-augmented generation (RAG)—it's about leveraging RAG for enterprise success. Despite the perks of larger context windows, they bring increased costs and latency. RAG, however, remains… https://t.co/ZVodM14zJk
Christopher Nguyen ⽗ https://t.co/fj5qxTOF1k Real-Reasoning RAG, or Where to Get Performance Gains Out of RAG (from @aitomatic & @IBMResearch, #AIAlliance): • Fine-tuning the retriever model gives you more bang for your buck than the generator model. • Employing reasoning yields significant… https://t.co/rKoAl5107M
Data Science Dojo Prototyping a RAG application is easy, but making it performant, robust, and scalable to a large knowledge corpus is hard. Learn 12 challenges in building production-ready RAG-based LLM applications with solutions ➡️: https://t.co/6PoLhoWb9v #RAGChallenges #RetrievalStage https://t.co/xNeO0WNpnJ
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