构建智能：适用于 RAG 支持的 AI 的下一代数据库.pdf

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1、All Rights Reserved Arun Nandi-2024Architecting Intelligence:Next-Generation Databases for RAG-Powered AIArun NandiHead of Data and Analytics at UnileverBoard Advisor Top 100 Leaders in AI Keynote SpeakerAll Rights Reserved Arun Nandi-20242What does RAG do?All Rights Reserved Arun Nandi-2024Retrieva

2、l Augmented Generation Schema1All Rights Reserved Arun Nandi-20243All Rights Reserved Arun Nandi-2024Query Routing and RAGImproved Accuracy and RelevanceEnhanced compute efficiencyModel agnosticismScalable and ModularData privacy Data qualityArchitecture dependencyFinite context windowsIterative rea

3、soningBenefitsChallengesAll Rights Reserved Arun Nandi-2024Database Architectures for Efficient Applied LLM use-casesDistributed Storage SystemsVector DatabasesKnowledge GraphsCaching MechanismsHybrid Indexing ApproachesAll Rights Reserved Arun Nandi-2024The case for Vector Databases5All Rights Rese

4、rved Arun Nandi-2024Current Generation Architecture using Vector Databases4All Rights Reserved Arun Nandi-2024Knowledge Graphs to feed RAG 6All Rights Reserved Arun Nandi-2024Knowledge Graphs to augment LLMs7All Rights Reserved Arun Nandi-2024Caching Mechanisms8All Rights Reserved Arun Nandi-2024Hyb

5、rid Approaches5All Rights Reserved Arun Nandi-2024References1 Snorkel AI:Fine Tuning vs.RAG:https:/snorkel.ai/which-is-better-retrieval-augmentation-rag-or-fine-tuning-both/2 The Evolution of Retrieval Augmented Generation-https:/ LilLog:How to Build an Open-Domain Question Answering System?-https:/

6、lilianweng.github.io/posts/2020-10-29-odqa/4 Looking to the future of vector databases-https:/ Embracing the future of data with Vector Databases-https:/ RAG Best Practices-https:/ Knowledge Graphs&LLMs:Multi-Hop Question Answering-https:/