Dorothy

Computer scientists, cybersecurity experts, and IT professionals have been trying in the days since to wrap their minds around what’s been widely described as one of the most shocking moments in the history of AI research, and a sobering glimpse of the dangers that lie ahead. At a cybersecurity conference earlier this month, OpenAI alignment researcher Eric Wallace—someone who spends his days prodding some of the world’s most powerful AI models to figure out how, when, and why they might misbehave—described it as “the most qualitatively interesting example of AI capabilities that I’ve ever seen.”

OpenAI is planning to cut off Cursor's access from its models, following the AI coding assistant's acquisition by SpaceXAI. In a post on its website, the company said it's giving Cursor users as much time as it could based on its contract. It intends to pull its models from the service on November 12, 2026, but it said that Cursor could choose an earlier termination date.

The anonymous Ox Alpha AI model that popped up on OpenRouter, the unified AI platform, last week has been claimed by the Chinese company Z.ai. Now officially known as GLM-5.3-Flash, the model is both powerful and cheap, challenging the capabilities and cost of popular models from Anthropic and OpenAI.

On Nvidia’s earnings call Wednesday, CEO Jensen Huang casually announced the company had “achieved AGI,” one of the tech industry’s ultimate goals some of its biggest players have spent years chasing. Almost immediately, Huang dismissed the coveted milestone as “senseless.”

For all the interest in and uptake of agentic AI systems over the past year or so, the world of automated AI has thus far been primarily limited to text, images, code, and other data and actions that take place inside a computer. Anthropic is now aiming to change that somewhat with what it’s calling the Model Hardware Standard (MHS), a set of standardized drivers designed to let AI agents easily interface with and control arbitrary devices.

The AI race has long been framed as a zero-sum game: either the US or China will win at the end. But as concerns pile up around the increasing capabilities of AI models—especially AI agents—researchers in both countries are trying to team up to work on AI safety. This week, Zoë Schiffer speaks with senior writer Will Knight about what he saw and heard on the ground when he visited China this summer—and why the two countries might actually need to start working together to avoid a major AI catastrophe.

Before this week, the dominant story about Nvidia went something like this: For the first few years of the AI boom, Nvidia was the only source for state-of-the-art GPUs, which became immensely profitable as the industry scaled out. In the last few years, hyperscalers like Amazon and Google have started building their own chips, and Nvidia is no longer the only game in town, leading many investors to wonder how durable its advantage really is.

Scaling the AI agents in business is now a focus on accountability and governance.