IBM Technology | Reinforcement Learning from Human Feedback (RLHF) Explained @IBMTechnology | Uploaded August 2024 | Updated October 2024, 13 hours ago.
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Join Martin Keen as he explores Reinforcement Learning from Human Feedback (RLHF), a crucial technique for refining AI systems, particularly large language models (LLMs). Martin breaks down RLHF's components, including reinforcement learning, state space, action space, reward functions, and policy optimization. Learn how RLHF enhances AI by aligning its outputs with human values and preferences, while also addressing its limitations and the potential for future improvements like Reinforcement Learning from AI Feedback (RLAIF).
AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdKSbv
Want to play with the technology yourself? Explore our interactive demo → https://ibm.biz/BdKSby
Learn more about the technology → https://ibm.biz/BdKSbM
Join Martin Keen as he explores Reinforcement Learning from Human Feedback (RLHF), a crucial technique for refining AI systems, particularly large language models (LLMs). Martin breaks down RLHF's components, including reinforcement learning, state space, action space, reward functions, and policy optimization. Learn how RLHF enhances AI by aligning its outputs with human values and preferences, while also addressing its limitations and the potential for future improvements like Reinforcement Learning from AI Feedback (RLAIF).
AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdKSbv
