Scientists warn that current AI tests reward polite responses rather than real moral reasoning in large language models.

As large language models (LLMs) gain momentum worldwide, there’s a growing need for reliable ways to measure their performance. Benchmarks that evaluate LLM outputs allow developers to track ...

Understanding complex biological pathways, such as gene-gene interactions and gene regulatory networks, is crucial for exploring disease mechanisms and advancing drug development. However, manual ...

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.

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 ...

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 ...

Scale AI founder and CEO Alexandr Wang testifies during a House Armed Services Subcommittee on Cyber, Information Technologies and Innovation hearing about artificial intelligence on July 18, 2023, in ...

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, ...

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