Artificial intelligence (AI) is at a very Chinese time in its life. Recent moves from Chinese AI labs are throwing the dominance of American "frontier labs" such as Google and OpenAI into question.

A new study is the first to suggest realistic ways to integrate wisdom into artificial intelligence, to create AI systems that will be more robust, transparent, cooperative, and safe. Researchers from the University of Waterloo led the team, which includes experts in psychology, computer science, and engineering. Their paper proposes ways to train large language models to be wiser, explore new architectures that could support wise reasoning, and suggest benchmarks to measure AI wisdom.

When artificial intelligence systems began acing long-standing academic assessments, researchers realized they had a problem: the tests were too easy. Popular evaluations, such as the Massive Multitask Language Understanding (MMLU) exam, once considered formidable, are no longer challenging enough to meaningfully test advanced AI systems.

German carmaker BMW said Friday it plans to deploy two AI-powered humanoid robots in a factory in a pilot program for the first time this year.

Innovation in artificial intelligence applications, including the rising tide of AI agents, is based on startups accessing AI foundation models offered by Anthropic, OpenAI, and Google. Each of these companies also competes with those startups, creating conflicts of interest. A new report by Vanderbilt Policy Accelerator director of artificial intelligence and technology policy Asad Ramzanali and Akhil Rajan analyzes the foundational model market, highlights a case study of a startup that experienced unfair treatment from a foundation model provider, and recommends a requirement for AI neutrality similar to "net neutrality" rules in broadband.