MLCommons Runs First Double-Blind Reliability Evaluation of Proprietary AI Model

MLCommons publishes business guide to measuring and managing AI risk

MLCommons released a guide titled "Assessing & Managing AI Risk for Business and Commercial Deployments," aimed at business owners. It argues teams managing AI risk face tension between protecting the business and adopting AI faster, and that independent measurement can reconcile the two. The guide frames AI risk as a cost that can be measured, priced, and managed.

NIST Study Maps How Toxic Adulterants in Fentanyl Vary Across US

NIST researchers analyzed fentanyl samples nationwide and found that the toxic substances mixed into the drug vary by region and shift over time. The study aims to help first responders and law enforcement identify dangerous adulterants in local supplies, which the agency says can help save lives.

NVIDIA teaches robots to assemble GB300 tester trays

NVIDIA describes how it taught robots to assemble tester trays for its Grace Blackwell GB300 superchip, which powers AI training and inference. The work required skilled physical labor in factories worldwide. NVIDIA says the project offered lessons in robot learning, mechanical intelligence, and traditional engineering.

Ai2's Bolmo byte-level language model technique published in Nature

Ai2 announced that the technique behind Bolmo, its fully open byte-level language models, has been published in Nature. New checkpoints show the approach generalizes beyond the Olmo model family to other model families, according to the Allen Institute for AI.

Microsoft Researcher Jennifer Neville Discusses AI Surprising Failures

Microsoft Research podcast features Jennifer Neville, who discusses her unexpected path into computer science and her work identifying "surprising failures" that make it hard for AI to handle complexity. The episode explores how failure teaches lessons and led to her professional sweet spot in AI research.