Enhance foundational models and evaluate Generative AI output through human input and feedback
Whether you are building generative AI tools or using them to transform your business, the foundational models used to build generative AI and the outputs they create need human input to ensure the quality and accuracy of their results. Further, generative AI solutions require human expertise to deliver domain-specific solutions such as medical, legal and financial services applications.
Reinforcement Learning from Human Feedback (RLHF) is critical to building responsible and explainable generative AI solutions. A key point in the RLHF process is to obtain data that can be used for fine-tuning generative AI models. With RLHF, a curated group of contributors evaluates the output of generative AI solutions, providing human oversight to ensure that the machine learning models used to train these solutions deliver non-offensive, accurate and unbiased results.