ZOOOO

ZOOOO is a reasoning framework centered on structure, constraints, and internal consistency. It does not treat scale as a goal, and it does not define success as maximum predictive accuracy.

Correlation-driven learning has fundamental limits in complex systems. In such systems, behavior is not a list of isolated effects. It is defined by structure, constraints, interactions, and coherent evolution over time.

ZOOOO was proposed to address these limits: not by adding more correlations, but by building a model that must remain consistent with what a system is allowed to be.

ZOOOO is not designed to win benchmarks or prediction tasks. The central question is: can a system build a structurally grounded, internally consistent understanding under constraints?

Data is a boundary condition imposed by reality, not the answer. The goal is to construct a self-consistent internal structure that can be reasoned over and evolved.

This shifts the emphasis from “predicting what comes next” to “reasoning about how a system holds together.”

The approach is grounded in how complex systems are studied in physics and applied mathematics: continuum systems, geometry, non-equilibrium processes, and complex dynamics.

System behavior is constrained by global structure, not only by local interaction details. ZOOOO brings this structural reasoning into general-purpose models.

ZOOOO is not purely theoretical. Virtual Cell is the first real-world instantiation of ZOOOO in life sciences.

It has been used within real R&D workflows through collaboration with Oda Pharmaceuticals. Virtual Cell does not replace experiments. It serves as an intermediate reasoning layer between experiments and mechanistic understanding.

We present ZOOOO as an evolving foundational framework, not a final solution.