In a provocative intersection of artificial intelligence and fundamental physics, developer Julian Zoria has released an open-source project claiming to simulate core aspects of our universe—including gravity and wave-particle duality—through AI-generated code. Dubbed the "Universe Engine," the project originated from an unconventional approach to circumventing tautological dead-ends in physics definitions.

Breaking the Tautology Trap

Zoria identified a fundamental limitation in how physics concepts are traditionally defined—circular references like "mass is energy, and energy is mass" that create logical loops. To overcome this, he instructed an AI model to discard all pre-learned physics knowledge and instead role-play as a game designer creating an imaginary universe governed by our physical constants. This framing forced the AI to rebuild concepts like time, space, and energy from first principles without tautology.

"This vicious cycle was so deeply rooted in the AI's training data that I could only break it by instructing the AI to forget all physics definitions," Zoria explained in the project's documentation.

The AI then autonomously produced a technical design document outlining the universe's logic and parameters, followed by functional code implementing the specifications. The resulting program simulates a discrete 128x128x128-bit volume—a "hyper-nano-universe"—where Newtonian gravity emerged during initial tests.

From Philosophy to Testable Science

While full-scale validation remains impractical without massive computing resources, the emergence of recognizable physics in a minimalist simulation is significant. As Zoria notes:

"The existence of finished documentation and code confirming that gravity emerges from base parameters shifts the Simulation Theory discussion from philosophy to science."

The project demonstrates AI's potential to reconceptualize complex systems when guided by creative constraints. Even if the model doesn't perfectly replicate our universe, its ability to generate testable emergent phenomena opens new avenues for exploring fundamental physics through computational approaches.

Call for Collaboration

Zoria has open-sourced the project on GitHub, inviting researchers to verify and expand on the work. The initiative highlights how AI can transcend pattern recognition to actively participate in structuring scientific models—provided we reframe problems to bypass ingrained biases.

Whether the "Universe Engine" ultimately mirrors reality or not, it exemplifies a groundbreaking methodology: using AI not just as a tool, but as a collaborative partner in reimagining the foundations of our physical world.

Explore the Universe Engine on GitHub

Source: Project documentation and Hacker News discussion (https://news.ycombinator.com/item?id=46366458)