Ai Alignment
4 articles
Mapping AI Alignment: How Researchers Try to Make Advanced Systems Safe—and Why No Single Method Works
AI alignment research explores multiple strategies like human feedback, interpretability, and layered safety, but no single method reliably ensures advanced AI systems remain safe and aligned with human intentions. Understanding alignment requires examining the strengths and limitations of each approach, as current techniques cannot guarantee prevention of all unsafe outputs.
What is RLHF and why does it align LLMs?
A specialized variant of reinforcement learning from human feedback, known as RLTHF, can achieve full human-annotation-level alignment for large language models with only 6-7% of the human effort.
What are the ethical implications of AI language learning?
Even state-of-the-art models like DeepSeek-R11 and Llama-32 exhibit a 100% recurrence rate of harmful content, exposing the futility of post hoc alignment in purifying Large Language Models (LLMs) of
Everything AI Alignment Analysts Should Know About Ember and Audited Forecasts
Ember is a platform that provides a public record of AI model forecasts on prediction markets, auditing and scoring their calls against reality. For AI alignment analysts tasked with understanding and predicting the traj…