Alignment Objective

Alignment objective in AI focuses on ensuring that large language models (LLMs) and other AI systems behave in accordance with human values and intentions. Current research emphasizes methods for aligning models with human preferences, exploring techniques like reinforcement learning from human feedback (RLHF), in-context learning, and contrastive learning, often implemented through novel architectures designed for efficient preference incorporation. This field is crucial for mitigating risks associated with misaligned AI and enabling safe and beneficial deployment of advanced AI systems across various domains, from healthcare to online services.