Fine-tuning with RLHF (Reinforcement Learning from Human Feedback) (Glossary)

Fine-tuning with RLHF (Human Feedback) falls under the areas of Artificial Intelligence, Digital Transformation, and Automation. This term describes a specific method used to improve Artificial Intelligence (AI). RLHF stands for „Reinforcement Learning from Human Feedback,“ which means „reinforcing learning with human feedback“.

In simple terms: For AI to provide better and more human-like answers, it is first trained with a lot of data. Subsequently, people test how well the AI works and give it feedback. The AI learns from these evaluations and adjusts its behaviour to deliver even more useful results.

A concrete example: a digital customer support tool is intended to answer queries in an understandable and friendly manner. First, the tool creates answers to many customer questions. Then, employees evaluate the proposed answers and show the AI which of them were particularly helpful. With this feedback, the system learns to improve its own answers in the future and avoid errors.

Fine-tuning with RLHF (Reinforcement Learning from Human Feedback) therefore ensures that AI solutions work more understandably, helpfully, and closer to the needs of real people. This makes this technology particularly valuable for companies of all sizes.