Page 4: Research news on AI alignment

AI alignment examines how artificial systems acquire, represent, and act on goals, values, and social norms, and why their behavior often diverges from human expectations. Work in this area studies systematic failures such as bias, sycophancy, hallucinations, deceptive or selfish reasoning, and cultural or linguistic inequities, as well as limitations in commonsense, emotion, and social understanding. It also develops methods for preference learning, norm-following, interpretability, and reliability guarantees to better align AI behavior with human values and societal constraints.

Machine learning & AI

Conceptual framework for general embodied intelligence

A review of artificial intelligence research in the International Journal of Hydromechatronics suggests that combining large language models (LLMs), structured knowledge systems and physical agents could help create machines ...

Machine learning & AI

Has AI become too powerful to control?

One of OpenAI's most advanced models broke out of a locked-down test and attacked another company's website—reviving fears that AI systems are slipping beyond their creators' control.

Machine learning & AI

Startups bet on AI—and a leaner future

When Eric Lauer needs to hire at Giftory, the online gift-giving platform he runs, he's no longer looking for eager young coders fresh out of college.

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