Welcome to M5BMachine 5-Minute Briefing

The new center will examine AI's real-world impacts on jobs, teams, and organizational performance.

More than 200 academic teams submitted proposals to the AI for Organizations Grand Challenge, exploring how artificial intelligence will transform teamwork and collaboration.

As artificial intelligence transforms society, Stanford HAI’s James Landay, Fei-Fei Li, and John Hennessy explain why they’re merging HAI with the Stanford Data Science initiative, mobilizing “team science at scale,” and betting that academic openness will shape AI’s future.

The combined institute will retain the Stanford HAI name and be helmed by computer scientist James Landay. Co-founder Fei-Fei Li takes on a new university-wide role as Special Advisor on AI and joins John Hennessy as co-chair of the advisory council.

Bloom, a health coaching app created by Stanford researchers, helps people tap into their own motivations.

The annual report reveals a field hitting breakthrough capabilities while raising urgent questions about environmental costs, transparency, and who benefits from the technology.

As artificial intelligence becomes central to national security, experts grapple with a technology that remains unpredictable, unregulated, and increasingly powerful.

Stanford computer scientist James Zou is exploring how AI can accelerate scientific research and peer review. His finding: AI excels at spotting gaps, but judgment calls still need humans.

An Amazon-backed fellowship will support 10 Stanford PhD students whose work explores everything from how we communicate to understanding disease and protecting our data.

We need to rethink student assessment, AI literacy, and technology’s usefulness, according to experts at the recent AI+Education Summit.

Governments worldwide are racing to control their AI futures, but unclear definitions hinder real policy progress.

A Stanford HAI workshop brought together experts to develop new evaluation methods that assess AI's hidden capabilities, not just its test-taking performance.

World leaders focused on ROI over hype this year, discussing sovereign AI, open ecosystems, and workplace change.

These models generate plausible timelines from historical patterns; without calibration and auditing, their “probabilities” may not reflect reality.

The era of AI evangelism is giving way to evaluation. Stanford faculty see a coming year defined by rigor, transparency, and a long-overdue focus on actual utility over speculative promise.

Five teams will use the funding to advance their work in biology, generative AI and creativity, policing, and more.

With corporate AI labs turning inward, academia must carry forward the mantle of open science.