Google DeepMind is funding research into the potential dangers of situations where millions of different AI agents interact with each other online. According to Rohin Shah, who directs the company's AGI safety and alignment research, the mass-market arrival of agents that can carry out tasks without human oversight and follow instructions given to them by other agents creates a whole new class of risk . In an effort to address this, Google DeepMind--which made agent-based tools a centerpiece of Google I/O last month --has teamed up with several other organizations to announce a $10 million funding pot for researchers to study the behavior of multi-agent systems and come up with ways to prevent unsafe scenarios. Joining Google DeepMind are Schmidt Sciences, a philanthropic foundation set up by Eric and Wendy Schmidt; ARIA, the UK government's moonshot agency; the Cooperative AI foundation, a UK-based nonprofit research outfit; and Google's charitable arm, Google.org. I asked Shah and James Fox, who leads the Science of Trustworthy AI program at Schmidt Sciences, what they hope to achieve with that $10 million.

I am attempting to solve a mathematical conundrum that has stumped many of humanity's greatest thinkers. I have zero mathematical training, apart from a distant undergraduate physics degree, which should put my odds of success at slim to none. But I also have a trick up my sleeve - a kind of mathematical genie that can conjure arcane secrets seemingly out of thin air. I make a short request concerning an esoteric conjecture in number theory, then cross my fingers. Perhaps "genie" is a bit too strong - I'm simply using GPT 5.5 Pro, the latest iteration of OpenAI's flagship model. But for mathematicians, modern AI models appear to have a spark of magic.

Trajectory is betting the rapid iteration cycle that supercharged vibe-coding can help all kinds of companies build AI products that learn continuously. Trajectory founders, Ronak Malde (left), Michael Elabd(center), and Arjun Karanam (right). A group of AI researchers who previously worked at Google DeepMind, Apple, OpenAI, and Meta Superintelligence Labs announced on Wednesday they're launching a new startup called Trajectory, which aims to help companies regularly improve their AI products by training on real-world user interactions. Trajectory wants to build a platform for AI that can learn continuously, a capability that researchers have long held up as a major barrier to further AI progress. OpenAI, Google, and Anthropic have found success training increasingly capable versions of AI models, especially for domains such as coding, math, and science.

Plus: Trump has postponed an AI order due to overregulation fears. Anthropic's Code with Claude showed off coding's future--whether you like it or not At Anthropic's developer event in London this week, Code with Claude, attendees were asked if they'd shipped code written entirely by Claude. Almost half the room raised their hands. Many admitted they hadn't even read the code before pushing it live. As tools like Claude Code get better, more and more developers are happy to hand their work off to AI. Anthropic says it wants to push automation as far as it will go. But not everyone is convinced that's the right approach.

Messages between Shivon Zilis and Tesla executives reveal plans in 2017 to start a rival AI lab, potentially led by Altman or Demis Hassabis. A few months before Elon Musk left OpenAI's board of directors in February 2018, he tried to recruit Sam Altman to join a "world-class AI lab" within Tesla. Musk went as far as offering the OpenAI CEO a Tesla board seat, according to emails and testimony presented in federal court on Wednesday during the trial . The emails were shown to a jury during the cross examination of Shivon Zilis, a former OpenAI adviser and board member who is also the mother of four of Musk's children. Musk's core claim in this lawsuit is that Altman and OpenAI president Greg Brockman effectively stole a nonprofit, using the $38 million Musk invested to create a private company worth more than $800 billion today.

Isomorphic Labs president Max Jaderberg said at WIRED Health in London that the startup has built a "broad and exciting pipeline of new medicines." Google DeepMind's AlphaFold has already revolutionized scientists' understanding of proteins . Now, the ability of the platform to design safe and effective drugs is about to be put to the test. Isomorphic Labs, the UK-based biotech spinoff of Google DeepMind, will soon begin human trials of drugs designed by its Nobel Prize-winning AI technology. "We're gearing up to go into the clinic," Isomorphic Labs president Max Jaderberg said on April 16 at WIRED Health in London.

Ten years ago, AlphaGo trounced human competitors--and its legacy is still present in today's most advanced bots. Thore Graepel may have been the first human to be vanquished by a superintelligence. In 2015, on his first day as a researcher at Google DeepMind, he was challenged to play against the earliest iteration of AlphaGo--a computer program developed by DeepMind that would prove so effective at the ancient-Chinese game of (or Go, as it is commonly known in the West) that it changed how humans play it, and then upended the field of AI itself. When Graepel faced it, AlphaGo was just a "baby" project, as he put it to me, and he was an accomplished amateur player. But it still took him down.

The speed at which artificial intelligence is gaining in mathematical ability has taken many by surprise. Are the days of handwritten mathematics coming to an end? In March 2025, mathematician Daniel Litt made a bet. Despite the march of progress of artificial intelligence in many fields, he believed his subject was safe, wagering with a colleague that there was only a 25 per cent chance an AI could write a mathematical paper at the level of the best human mathematicians by 2030. Only a year later, he thinks he was wrong.

Has the technology lived up to its potential? The first time that AlphaGo revealed its full power, it prompted a visceral reaction . Lee Sedol, the world's greatest player of the ancient Chinese board game Go, had grown visibly agitated at the artificial intelligence's prowess. The hushed crowd in downtown Seoul, South Korea, could barely contain its gasps. It was quickly dawning on Lee, and the tens of millions watching at home, that this AI was different to those that had come before. It wasn't just beating Lee, but it was doing so with an almost human-like aptitude.

For decades, handmade narco subs have been some of the cocaine trade's most elusive and productive workhorses, ferrying multi-ton loads of illicit drugs from Colombian estuaries toward markets in North America and, increasingly, the rest of the world. Now off-the-shelf technology--Starlink terminals, plug-and-play nautical autopilots, high-resolution video cameras--may be advancing that cat-and-mouse game into a new phase. Uncrewed subs could move more cocaine over longer distances, and they wouldn't put human smugglers at risk of capture. And law enforcement around the world is just beginning to grapple with what this means for the future. This story is from the next print issue of magazine, which is all about crime. Google DeepMind is calling for the moral behavior of large language models--such as what they do when called on to act as companions, therapists, medical advisors, and so on--to be scrutinized with the same kind of rigor as their ability to code or do math.