Unverified50% confidenceFactExact time
There are typically three technical approaches to achieving specialized intelligence: supervised fine-tuning (SFT), retrieval-augmented generation (RAG), and pre-training from scratch.
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10/10/2026
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VerifiedLarge model training goes through three core stages: pre-training, supervised fine-tuning (SFT), and preference alignment.74% similarUnverifiedCompared to training foundation models, applying RAG, agents, and document intelligence to specific industries has a more manageable barrier to entry and a clearer monetization path.73% similarUnverifiedWhen building intelligent customer service systems, enterprises typically do not train models from scratch, but instead inject internal data into existing models through SFT supervised fine-tuning and LoRA fine-tuning.73% similarUnverifiedTechnical difficulty exists on a gradient: fine-tuning < SFT < pre-training, and the recommended learning order is to start with fine-tuning first.71% similarUnverifiedSkill encapsulation differs from RAG in that it focuses more on standardizing executable operational processes rather than merely retrieving reference knowledge.70% similar
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