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Over 1 billion images and controller actions from players of Bleeding Edge were used as training data for Muse, a new genAI model from Microsoft that could be a game-changer for iterative game design. (Ninja Theory Image)
In a new blog post on Wednesday, Microsoft’s research department debuted a new generative AI model called Muse that it describes as a “breakthrough” for gameplay ideation.
Muse is a World and Human Action Model, or WHAM, built by the Microsoft Research Lab in Cambridge in conjunction with the British game developer and Xbox subsidiary Ninja Theory.
For years, Microsoft Research has used Ninja Theory’s multiplayer shooter Bleeding Edge as a testbed for experiments in how to create more human-like CPU opponents: bots that act and perform more like humans would. With Muse, it’s used the equivalent of roughly seven years of continuous human gameplay as training data, in order to create a new type of model that possessed a detailed understanding of the 3D game world.
“The impressive abilities we first witnessed with ChatGPT and GPT-4 to learn human language are now being matched by AI’s abilities to learn the mechanics of how things work, in effect developing a practical understanding of interactions in the world,” wrote Peter Lee, Microsoft Research president, in a post on the official Microsoft blog.
This allows Muse to generate virtual gameplay sequences of up to two minutes based upon preprogrammed criteria such as controller actions. According to Fatima Kardar, Microsoft’s corporate vice president of gaming AI, Muse is already being used in-house to develop a “real-time playable AI model” using training data from other first-party games from Xbox Game Studios.
In addition, Kardar suggests that Muse could be used as a method of preserving and updating classic games.
“Today, countless classic games tied to aging hardware are no longer playable by most people,” Kardar wrote in a post on Xbox Wire. “Thanks to this breakthrough, we are exploring the potential for Muse to take older back catalog games from our studios and optimize them for any device.”
Kardar continued, “We believe this could radically change how we preserve and experience classic games in the future and make them accessible to more players.”
Lee also notes that Muse’s ability to visualize and navigate 3D spaces could lead to future breakthroughs in fields such as interior design or architectural modeling.
The details behind Muse are further explored in a post on the official Microsoft Research blog by senior principal research manager Katja Hoffman, as well as a new paper in Nature, “World and Human Action Models towards gameplay ideation.”
Hoffman further announced that the weights and sample data are being made open source. Interested researchers can test Microsoft Research’s WHAM model now on Azure AI Foundry.