AI

What would a behind-the-scenes look at a video generated by an artificial intelligence model be like? You might think the process is similar to stop-motion animation, where many images are created and stitched together, but that’s not quite the case for “diffusion models” like OpenAl’s SORA and Google’s VEO 2. Instead of producing a video […]

The startup behind ChatGPT is going to remain in nonprofit control, but it still needs regulatory approval.

What if data could help predict a patient’s prognosis, streamline hospital operations, or optimize human resources in medicine? A book fresh off the shelves, “The Analytics Edge in Healthcare,” shows that this is already happening, and demonstrates how to scale it.  Authored by Dimitris Bertsimas, MIT’s vice provost for open learning, along with two of Bertsimas’

If there’s one thing that characterizes driving in any major city, it’s the constant stop-and-go as traffic lights change and as cars and trucks merge and separate and turn and park. This constant stopping and starting is extremely inefficient, driving up the amount of pollution, including greenhouse gases, that gets emitted per mile of driving. 

If you missed WIRED’s live, subscriber-only Q&A focused on the software features of ChatGPT, hosted by Reece Rogers, you can watch the replay here.

Forget Mark Zuckerberg’s vision of VR meetings; the industrial metaverse bridges digital and physical worlds in a way that’s actually useful.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial intelligence model inspired by neural oscillations in the brain, with the goal of significantly advancing how machine learning algorithms handle long sequences of data. AI often struggles with analyzing complex information that unfolds over long periods of time, such as

In its push for “efficiency,” DOGE has leaned increasingly on AI—regardless of whether it makes any sense. And it’s using it as an imperfect means to destructive ends.

The Amazon Bedrock multi-agent collaboration feature gives developers the flexibility to create and coordinate multiple AI agents, each specialized for specific tasks, to work together efficiently on complex business processes. This enables seamless handling of sophisticated workflows through agent cooperation. This post aims to demonstrate the application of multiple specialized agents within the Amazon Bedrock

A startup founder told a Palantir alumni Slack group that AI agents could do the work of tens of thousands of government employees. He was met with emojis of clowns and a man licking a boot.