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AI Glossary

Fine-Tuning

The process of further training a pre-trained AI model on specific data to customize its behavior for particular tasks.

TL;DR

  • —The process of further training a pre-trained AI model on specific data to customize its behavior for particular tasks.
  • —Understanding Fine-Tuning is critical for effective AI for companies.
  • —Remova helps companies implement this technology safely.

In Depth

Fine-tuning adapts a foundation model's capabilities to specific organizational needs by training it on domain-specific data. This can improve accuracy for specialized tasks, align outputs with organizational tone and style, and reduce hallucinations in domain-specific contexts.

Related Terms

Foundation Model

A large AI model trained on broad data that can be adapted to many downstream tasks.

Training Data

The dataset used to train an AI model, which significantly influences its capabilities and biases.

Large Language Model (LLM)

A deep learning model trained on vast text datasets that can understand and generate human-like text.

System Prompt

Hidden instructions given to an AI model that define its behavior, personality, and constraints for a conversation.

Knowledge Hub

Glossary FAQs

Fine-Tuning is a fundamental concept in the AI for companies landscape because it directly impacts how organizations manage the process of further training a pre-trained ai model on specific data to customize its behavior for particular tasks.. Understanding this is crucial for maintaining AI security and compliance.
Remova's platform is built to natively manage and optimize Fine-Tuning through our integrated governance layer, ensuring that your organization benefits from this technology while mitigating its inherent risks.
You can explore our full AI for companies glossary, which includes detailed definitions for related concepts like Foundation Model and Training Data.

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