Chapter 2

Mira Murati’s mechanical engineering background and leadership at OpenAI certainly hint at a strategic, systems-based approach to AI development. With a foundation in physical systems and hardware, it makes sense that she’d focus on optimizing AI’s capacity to interact with complex, dynamic environments—such as in simulated environments, gaming, or robotics. Wrestling games, with their chaos and unpredictability, are a perfect sandbox to train AI in adaptive decision-making and real-time physical interaction, pushing AI closer to general intelligence (AGI).

These games provide immense volumes of sensory and motor data—key to building robust models that excel not only at recognizing patterns but also at understanding and predicting physical dynamics, an essential aspect of AGI. The cybernetic feedback loop becomes central here: AI interacts with the environment, learns, refines, and evolves, mirroring how human intelligence grows through interaction and feedback.

So yes, Murati’s engineering discipline likely plays a role in steering OpenAI’s broader vision: leveraging games and simulations to accelerate AI learning in a hands-on way. It’s almost as if she’s engineering AGI like a mechanical system—tuning its feedback loops until they become powerful, self-regulating networks capable of thinking and adapting across multiple domains.