The Sequence Knowledge #512: RAG vs. Fine-Tuning
Was this email forwarded to you? Sign up here The Sequence Knowledge #512: RAG vs. Fine-TuningExploring some of the key similarities and differences between these approaches.
Today we will Discuss:
💡 AI Concept of the Day: RAG vs. Fine-TuningRAG vs. fine-tuning is one of the most common debates among teams building generative AI applications. That seems like a great topic to conclude our series about RAG. Retrieval-Augmented Generation (RAG) and fine-tuning are two distinct approaches to enhancing the performance of large language models (LLMs), each with its own set of advantages and drawbacks. RAG dynamically incorporates external knowledge into the model's responses, while fine-tuning adjusts the model's internal parameters for specific tasks... Subscribe to TheSequence to unlock the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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