I Put a Bunch of AI Agents in Charge of a Fantasy Soccer Team. To experiment with AI's predictive skills, I let Codex loose on a fantasy team. It tried to bench Erling Haaland at first, but it soon learned the error of its ways. I have consulted my AI-powered crystal ball, and it's telling me that frontier models are going to get a lot better at making predictions in the near future. Just ask my Premier League fantasy team .

In 1934, a doctor brought a dog back to life. He tried to do the same with humans. Dr. Robert Cornish was a real-life Victor Frankenstein. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Dr. Robert E. Cornish ties a human subject to his life-restoring teeterboard.

Antimatter is not known for being easy to get ahold of . That's part of why these particles remain so cryptic. But recently, a team of physicists at Northwestern University managed to trap a single antimatter particle for months. Cooling it to temperatures near absolute zero, they could control its quantum states with great precision without even touching it. The experiment, published in Physical Review Letters represents a breakthrough in our understanding of one of the great mysteries of physics.

How far can we push computing? Nowadays big advances are made by scaling up--think more chips packed into ever-bigger data centers. But as we near the ceiling of what we can build, there's still plenty of room below, at the fundamental physical limits of computing. Richard Feynman speaks at CERN in Geneva, Switzerland, in 1965. On the evening of December 29, 1959, at an American Physical Society meeting at Caltech, the physicist Richard Feynman gave a lecture called "There's Plenty of Room at the Bottom," on how we might manipulate and control things on an extremely small scale. There is no physical law stopping us from writing the entire on the head of a pin, he argued, or from storing every book ever written in something the size of a dust speck--or, ultimately, from arranging matter atom by atom. Biology already did versions of this (a living cell keeps its instructions in a wisp of DNA), so all of this was plainly permitted by the laws of physics. We simply had not built the tools yet.

The quest for cognitive immortality continues. Have you ever thought about what makes you? Science assures us it has everything to do with the three-pound organ between our ears, with its billions of neurons and trillions of delicate connections. But it's a lot trickier to explain why we have a sense of self-awareness or to pin down precisely where that first memory of Mommy actually resides. As we age, we forget most of what we've experienced, yet there's still undeniable continuity: At 30, or 50, or 70, you will still be you. To preserve that elusive continuity of self, some far-thinking technologists are working on ways to keep your brain going--even beyond death.

Now It's Chasing the Rest of Science AI may soon be the default way to solve theoretical problems in economics, high-energy physics, and other fields, MIT researchers tell WIRED. Last week, I attended a talk at MIT by Neil Thompson, who studies progress in computing and artificial intelligence . Over the course of just half an hour, Thompson made a convincing case that several scientific fields are about to be upended by AI. As mathematicians reel from the way AI is automating their field, Thompson's latest study suggests that probability, statistics theory, economic theory, high-energy theory, gravitation and cosmology, and quantum physics may be next, thanks to the rapidly evolving capabilities of frontier models. Between mid-2024 and mid-2026, the study shows, the best AI models went from being able to correctly solve about 2 percent of theoretical problems in these fields to about 35 percent of such problems.

Solar geoengineering could buy humanity time against climate change--or trigger a dangerous new arms race. A first-of-its-kind simulation offered a glimpse of what happens when geopolitics takes the wheel. When it comes to deciding the fate of the planet, Colleen Golja always thought science and reason would have a seat at the table. That was until one morning last September in London, when the climate researcher took part in the first in a series of war games. The goal: to prevent an uncontrolled global race to develop a technology aimed at cooling the planet but that comes with vast, unknown risks that could reshape life on Earth. "I thought that would be such an easy thing. Like, we can all agree to do ethical research and make sure it's for the better of all humans," she told WIRED.

At the International Conference on Machine Learning (ICML 2026),, and presented their work Vision Language Models Cannot Reason About Physical Transformation . In this interview, William Yijiang Li tells us more about the research, the method the team used, and the controlled experiments they carried out. What is the topic of the research in your paper and why is it an interesting area for study? Our research asks a fairly fundamental question: do vision-language models actually understand how the physical world changes over time? Modern vision-language models are increasingly being used in areas such as robotics, embodied agents, and video understanding.

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Andreessen Horowitz investor Olivia Moore created an AI-generated TikTok influencer for Bama Rush to test how viewers react to artificial intelligence content.