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AI Glossary

What is Fine-Tuning?

Training an AI model on specific data to specialize it for particular tasks.

By Council Research TeamUpdated: Jan 27, 2026

Definition

Fine-tuning takes a pre-trained AI model and trains it further on domain-specific data. This creates a specialized model that performs better on specific tasks while retaining general capabilities.

Examples

1Training GPT on medical data
2Customizing Claude for legal documents
3Brand voice adaptation

Why It Matters

Fine-tuning creates specialized AI that outperforms generic models on specific tasks.

Related Terms

Large Language Model (LLM)

An AI system trained on vast text data to understand and generate human-like text.

Prompt Engineering

The practice of crafting effective instructions to get better results from AI models.

Common Questions

What does Fine-Tuning mean in simple terms?

Training an AI model on specific data to specialize it for particular tasks.

Why is Fine-Tuning important for AI users?

Fine-tuning creates specialized AI that outperforms generic models on specific tasks.

How does Fine-Tuning relate to AI chatbots like ChatGPT?

Fine-Tuning is a fundamental concept in how AI assistants like ChatGPT, Claude, and Gemini work. For example: Training GPT on medical data Understanding this helps you use AI tools more effectively.

Related Use Cases

Best AI for Coding

Best AI for Business

AI Models Using This Concept

ClaudeClaudeChatGPTChatGPTGeminiGemini

See Fine-Tuning in Action

Council lets you compare responses from multiple AI models side-by-side. Experience different approaches to the same prompt instantly.

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