Reinforcement Learning from Human Feedback (RLHF)

A training technique that improves AI system behaviour by incorporating human evaluations and preferences into the learning process, enabling models to better align with human values and business objectives. Human reviewers rate AI outputs, and these ratings guide the system towards producing more helpful, accurate, and appropriate responses. Businesses implementing customer-facing AI benefit from RLHF's ability to fine-tune system behaviour for brand voice, customer service standards, and quality expectations. This approach bridges the gap between AI capabilities and real-world business requirements, ensuring systems perform reliably in operational contexts.