DeepMind has developed a way for AI programs to learn how to team up effectively in a simple video game. Most strikingly, the AI agents can also collaborate with human players—and those players say the programs are better teammates than most people.
Team players: Researchers at DeepMind trained teams of AI agents to play a game of capture the flag in a modified version of the first-person shooter Quake III Arena. Teamwork is extremely difficult to develop effectively in AI programs, because it involves dealing with a complex and ever-changing situation.
Winning formula: The researchers used an algorithm, dubbed “For the Win,” that trains a host of agents in parallel using reinforcement learning, a machine-learning technique modeled on the way animals learn. A few tricks helped optimize and tune the process.
Game changing: It’s a promising advance, because AI programs will need to work nicely with each other. But it’s important to note that the world in which these programs operate is incredibly simple. Demonstrating teamwork in the real world will be a lot more challenging—and achieving that is likely to be a long way off.
This new data poisoning tool lets artists fight back against generative AI
The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models.
Everything you need to know about artificial wombs
Artificial wombs are nearing human trials. But the goal is to save the littlest preemies, not replace the uterus.
Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist
An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.
Data analytics reveal real business value
Sophisticated analytics tools mine insights from data, optimizing operational processes across the enterprise.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.