AI

The United States and China “are the two largest emitters of carbon in the world,” said Nicholas Burns, former U.S. ambassador to the People’s Republic of China, at a recent MIT seminar. “We need to work with each other for the good of both of our countries.”  During the MITEI Presents: Advancing the Energy Transition […]

In response to Anthropic’s lawsuit, the government said it lawfully penalized the company for trying to limit how its Claude AI models could be used by the military.

The early years of faculty members’ careers are a formative and exciting time in which to establish a firm footing that helps determine the trajectory of researchers’ studies. This includes building a research team, which demands innovative ideas and direction, creative collaborators, and reliable resources.  For a group of MIT faculty working with and on

This post is co-written with Mark Ross from Atos. Organizations pursuing AI transformation can face a familiar challenge: how to upskill their workforce at scale in a way that changes how teams build, deploy, and use AI. Traditional AI training approaches—online courses, certification programs, and classroom-based instruction—are necessary, but often insufficient. While they build foundational

Joe Hogan, Align Technology’s plastics-nerd CEO, says you shouldn’t eat with your aligners and that you don’t need to wear your retainers every night.

Customer conversations with chatbots can include contact information and personal details that make it easier for scammers to launch phishing attacks and commit fraud.

AI is moving fast, and for most of our customers, the real opportunity isn’t in experimenting with it—it’s in running AI in production where it drives meaningful business outcomes. This means building systems that run reliably, perform at scale, and meet your organization’s security and compliance requirements. Today at NVIDIA GTC 2026, AWS and NVIDIA

The technology could help automakers build AI assistants that understand group conversations and what’s happening around the car.

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This is Part II of a two-part series from the AWS Generative AI Innovation Center. If you missed Part I, refer to Operationalizing Agentic AI Part 1: A Stakeholder’s Guide. The biggest barrier to agentic AI isn’t the technology—it’s the operating model. In Part I, we established that organizations generating real value from agents share