AI Alignment

AI alignment focuses on ensuring artificial intelligence systems act in accordance with human values and intentions, addressing potential risks from misaligned goals. Current research emphasizes diverse approaches, including reinforcement learning from human feedback (RLHF) and direct preference optimization (DPO), often applied to large language models (LLMs), to achieve alignment through various methods like reward shaping and preference aggregation. This field is crucial for responsible AI development, impacting both the safety and ethical implications of increasingly capable AI systems across numerous applications.