Categories: AI/ML News

Benchmarking framework reveals major safety risks of using AI in lab experiments

While artificial intelligence (AI) models have proved useful in some areas of science, like predicting 3D protein structures, a new study shows that it should not yet be trusted in many lab experiments. The study, published in Nature Machine Intelligence, revealed that all of the large-language models (LLMs) and vision-language models (VLMs) tested fell short on lab safety knowledge. Overtrusting these AI models for help in lab experiments can put researchers at risk.

AI can seem more human than real humans in a classic Turing test

A new University of California San Diego study unveils the first empirical evidence that a modern artificial intelligence system can pass the Turing test—a major scientific benchmark that asks whether a machine can imitate human conversation so convincingly that people can't reliably tell it apart from a real person. In…

May 20, 2026

In "AI/ML News"

Multimodal agent can iteratively design experiments to better understand various components of AI systems

As artificial intelligence models become increasingly prevalent and are integrated into diverse sectors like health care, finance, education, transportation, and entertainment, understanding how they work under the hood is critical. Interpreting the mechanisms underlying AI models enables us to audit them for safety and biases, with the potential to deepen…

July 24, 2024

In "AI/ML News"

Student-powered machine learning

From their early days at MIT, and even before, Emma Liu '22, MNG '22, Yo-whan “John” Kim '22, MNG '22, and Clemente Ocejo '21, MNG '22 knew they wanted to perform computational research and explore artificial intelligence and machine learning. “Since high school, I’ve been into deep learning and was…

August 31, 2022