🔬 AI Research

Reinforcement Learning from Human Feedback: How RLHF Shapes AI Behavior

RLHF is the technique that transformed raw language models into useful AI assistants. Here is how it works and why it matters for AI alignment.

theAIcatchup Apr 24, 2026 5 min read

⚡ Key Takeaways

{'point': 'RLHF bridges capability and alignment', 'detail': 'Base language models are capable but unaligned; RLHF trains them to optimize for human preferences rather than mere statistical text prediction.'} 𝕏
{'point': 'Three phases build on each other', 'detail': 'Supervised fine-tuning establishes baseline behavior, a reward model learns human preferences, and reinforcement learning optimizes the model against those preferences.'} 𝕏
{'point': 'Alternatives are emerging', 'detail': "Direct Preference Optimization and Constitutional AI address RLHF's limitations around reward hacking, scalability, and annotator bias with simpler or more principled approaches."} 𝕏

Written by

İbrahim Şamil Ceyişakar

Founder and editor covering the latest developments in this space.

#AI alignment #RLHF #reinforcement learning

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