SIMA 2, which can figure out how to solve problems inside virtual worlds, could lead to more general-purpose agents and better robots. Google DeepMind has built a new video-game-playing agent called SIMA 2 that can navigate and solve problems in a wide range of 3D virtual worlds. The company claims it's a big step toward more general-purpose agents and better real-world robots. Google DeepMind first demoed SIMA (which stands for "scalable instructable multiworld agent") last year. But SIMA 2 has been built on top of Gemini, the firm's flagship large language model, which gives the agent a huge boost in capability. The researchers claim that SIMA 2 can carry out a range of more complex tasks inside virtual worlds, figure out how to solve certain challenges by itself, and chat with its users.

Google DeepMind has unveiled new research highlighting an AI agent that's able to carry out a swath of tasks in 3D games it hasn't seen before. The team has long been experimenting with AI models that can win in the likes of Go and chess, and even learn games without being told their rules. Now, for the first time, according to DeepMind, an AI agent has shown it's able to understand a wide range of gaming worlds and carry out tasks within them based on natural-language instructions. The researchers teamed up with studios and publishers such as Hello Games ( No Man's Sky), Tuxedo Labs ( Teardown) and Coffee Stain ( Valheim and Goat Simulator 3) to train the Scalable Instructable Multiworld Agent (SIMA) on nine games. The team also used four research environments, including one built in Unity in which agents are instructed to form sculptures using building blocks.

Goat Simulator 3 is a surreal video game in which players take domesticated ungulates on a series of implausible adventures, sometimes involving jetpacks. That might seem an unlikely venue for the next big leap in artificial intelligence, but Google DeepMind today revealed an AI program capable of learning how to complete tasks in a number of games, including Goat Simulator 3. Most impressively, when the program encounters a game for the first time, it can reliably perform tasks by adapting what it learned from playing other games. The program is called SIMA, for Scalable Instructable Multiworld Agent, and it builds upon recent AI advances that have seen large language models produce remarkably capable chabots like ChatGPT. "SIMA is greater than the sum of its parts," says Frederic Besse, a research engineer at Google DeepMind who was involved with the project. "It is able to take advantage of the shared concepts in the game, to learn better skills and to learn to be better at carrying out instructions."

One element of what made the first "Goat Simulator's" shtick grow stale so rapidly was its boundaries. In the original, there are only two zones to gallivant in, and they're pretty vanilla aside from a few interesting sights, such as stumbling upon a Deadmau5 concert. But in "Goat Simulator 3," there are several cities and places, each brimming with life and vibrancy, to explore. There's a food factory that manufactures fake bananas. There's a cemetery where phantoms can be tormented and dragged out of their graves with your elastic tongue. By highlighting them as places of interest with a symbol on the map, "Goat Simulator 3" encourages exploration.