Fine-tuning in generative AI

Fine-tuning in Generative AI involves refining a pre-trained generative model such as a large language or image model—using a smaller, domain-specific dataset to optimize performance for targeted applications. This process tailors the modelʼs outputs to align with specific industry language, tone, or content requirements while preserving its original capabilities. Fine-tuning enhances relevance, accuracy, and control in use cases like personalized content generation, industry- specific chatbots, and creative design—enabling more effective and reliable generative AI deployments.