Enter large language model (LLM) evaluation. The purpose of LLM evaluation is to analyze and refine GenAI outputs to improve their accuracy and reliability while avoiding bias. The evaluation process ...

In a remote, within-participant simulation, 26 oncologists from the United Kingdom, United States, Spain, and Singapore reviewed synthetic breast cancer cases and created comprehensive summaries for ...

Scoping review finds large language models can support glaucoma education and decision support, but accuracy and multimodal limits persist.

Artificial intelligence has traditionally advanced through automatic accuracy tests in tasks meant to approximate human knowledge. Carefully crafted benchmark tests such as The General Language ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine an existing formalized evaluation ...

A new systematic review reveals that only 5% of health care evaluations for large language models use real patient data, with significant gaps in assessing bias, fairness, and a wide range of tasks, ...

MEREDITH identified a broader range of treatment options (median 4) compared with MTB experts (median 2). These options included therapies on the basis of preclinical data and combination treatments, ...

A duplex speech-to-speech model changes the premise: The intelligence layer consumes audio and produces audio directly. The model can attend to what was said and how it was said—content and delivery ...

In many high-stakes situations, large language models are not worth the risk. Knowing which outputs to throw out might fix that. Large language models are famous for their ability to make things up—in ...

Explore how vision-language-action models like Helix, GR00T N1, and RT-1 are enabling robots to understand instructions and act autonomously.