Google DeepMind shared on Thursday a research preview of SIMA 2, the next generation of its generalist AI agent that integrates the language and reasoning powers of Gemini, Google’s large language model, to move beyond simply following instructions to understanding and interacting with its environment. Like many of DeepMind’s projects, including AlphaFold, the first version of SIMA was trained on hundreds of hours of video game data to learn how to play multiple 3D games like a human, even some games it wasn’t trained on. SIMA 1, unveiled in March 2024, could follow basic instructions across a wide range of virtual environments, but it only had a 31% success rate for completing complex tasks, compared to 71% for humans. “SIMA 2 is a step change and improvement in capabilities over SIMA 1,” Joe Marino, senior research scientist at DeepMind, said in a press briefing. “It’s a more general agent. It can complete complex tasks in previously unseen environments. And it’s a self-improving agent. So it can actually self-improve based on its own experience, which is a step towards more general-purpose robots and AGI systems more generally.” DeepMind says SIMA 2 doubles the performance of SIMA 1Image Credits:Google DeepMind SIMA 2 is powered by the Gemini 2.5 flash-lite model, and AGI refers to artificial general intelligence, which DeepMind defines as a system capable of a wide range of intellectual tasks with the ability to learn new skills and generalize knowledge across different areas. Working with so-called “embodied agents” is crucial to generalized intelligence, DeepMind’s researchers say. Marino explained that an embodied agent interacts with a physical or virtual world via a body — observing inputs and taking actions much like a robot or human would — whereas a non-embodied agent might interact with your calendar, take notes, or execute code. Jane Wang, a research scientist at DeepMind with a background in neuroscience, told TechCrunch that SIMA 2 goes far beyond ga...
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