DeepMind’s AI agents are better than humans at being your teammate
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.
Keep Reading
Most Popular
The inside story of how ChatGPT was built from the people who made it
Exclusive conversations that take us behind the scenes of a cultural phenomenon.
How Rust went from a side project to the world’s most-loved programming language
For decades, coders wrote critical systems in C and C++. Now they turn to Rust.
Design thinking was supposed to fix the world. Where did it go wrong?
An approach that promised to democratize design may have done the opposite.
Sam Altman invested $180 million into a company trying to delay death
Can anti-aging breakthroughs add 10 healthy years to the human life span? The CEO of OpenAI is paying to find out.
Stay connected
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.