Fine-tuning with RLHF (Human Feedback) belongs to the fields of artificial intelligence, digital transformation and automation. This term describes a special method used to improve artificial intelligence (AI). RLHF stands for "reinforcement learning from human feedback", which means "reinforcement learning with human feedback".
In simple terms: in order for an AI to give better and more human answers, it is first trained with a lot of data. Humans then test how well the AI works and give it feedback. The AI learns from these evaluations and adapts its behaviour to deliver even more useful results.
A concrete example: A digital customer support tool should answer enquiries in a clear and friendly manner. First, the tool creates answers to many customer questions. Employees then evaluate the suggested answers and show the AI which ones were particularly helpful. The system uses this feedback to learn how to improve its own answers in future and avoid errors.
Fine-tuning with RLHF (human feedback) therefore ensures that AI solutions are more comprehensible, more helpful and closer to the needs of real people. This makes this technology particularly valuable for companies of all sizes.
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