RAG continues to rise
Practical AI
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Navigating AI Implementation Challenges
This chapter explores the complexities of using retrieval-augmented generation (RAG) versus fine-tuning in AI systems, particularly for chatbots and assistants. It discusses the operational advantages of RAG, the challenges of fine-tuning for specialized applications, and the growing trend towards a multi-model approach among enterprises. Additionally, the chapter addresses the issues of evaluating machine learning models, the fragmentation of programming communities, and the importance of current data retrieval in AI implementations.
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