Fine-tuning (model training)
Fine-tuning – additional LLM training on highly specialized data. What is it, what is different from RAG and what approach is more important for GEO promotion.
Fine-tuning, further education The process of additional training of a ready-made language model on a highly specialized data set. The basic model is run by new examples so that it better understands a particular topic, tone or format.
Fine-tuning is used for corporate chatbots, corporate-style content generation and support automation.
It is important for an SEO professional to understand the difference: fine-tuning changes the behavior of the model through retraining, whereas RAG substitutes relevant data directly into the query.
For GEO-promotion, RAG plays a key role. It determines whose content the model cites in a specific response right now.
Related terms
llm
LLM (Large Language Model) is a neural network behind ChatGPT, Claude and Gemini. How it works, why it’s wrong and what it means for SEO and content marketing.
Artificial intelligenceRAG (Retrieval-Augmented Generation)
RAG is an AI architecture in which a model searches for data from external sources before responding. Learn how it works and why it’s important for GEO.
Artificial intelligenceLLM hallucination
LLM hallucination is when an AI generates compelling but false text. What is it, why does it arise, and how does it affect SEO and AI search?
Artificial intelligenceContext Window (Context Window)
Context window is the volume of text that a language model sees at a time. How the token limit works and why dense content is more likely to fall into AI search responses.
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