LOS ANGELES—Stressing that she had significant reason to fear for her life during yesterday’s confrontation, Homeland Security Secretary Kristi Noem told reporters Friday that she believed Sen. Alex P...

The State Department has intervened on behalf of Musk’s satellite internet company in five developing nations. In Gambia, U.S. diplomats have lobbied and browbeat at least seven government ministers a...

Just 1 in 4 AI investments bring in the ROI they promise—but CEOs just can’t resist the technology.

The Trump administration’s slashing of budgets and staff have Great Lakes scientists concerned that they have lost the ability to protect the public from toxic algal blooms, which can kill animals and...

In recent years AI has taken center stage with the rise of Large Language Models (LLMs) that can be used to perform a wide range of tasks, from question answering to coding. There is now a strong focus on large pretrained foundation models as the core of AI application development. But on their own, these models don’t do much besides taking up significant disk space—it’s only when they’re embedded within larger systems that they start to deliver state-of-the-art results. In this webinar, Professor Christopher Potts will discuss how AI systems built with multiple interacting components can achieve superior results compared to standalone models. He will also examine how this systems approach impacts AI research, product development, safety, and regulation. Learn more about the AI Professional Program: https://online.stanford.edu/programs/artificial-intelligence-professional-program