1. Principled-based framework

We compute resilient intelligence principles in composite AI models through systematic evidenced-based selection and selection from bioengineering experimentation.

2. Computing resilient function

Biological function emerges from coordinated cellular collaboration. Through collective behavior, cells maintain stability or adapt under stress for system-wide responses.

• Function from collective behavior
• Each cell acts as a Resilient Computing Unit (RCU)
• RCUs enhance group resilience
• Evolution optimizes collective function.
• individual to collective f(x)

3. Teaching AI models to understand disruption response 

Building composite AI with embedded principles for RCUs. We call this an agent-cell unit, computing resilient functions. These systems are able to understand and identify resilient strategies.

4. Expand to

digital agent-cell modules

Building upon agent-cell units by integrating complementary principles and models for specialized functionality. These modular units identify adaptive strategies and are the foundation for domain-specific applications. 

5. From modules to ecosystems

Integrating specialized modules into interconnected networks with ecosystem-level resilience. These systems exhibit collective behavior and adaptive capabilities.

6. Building blocks to

semi-autonomous organizations

Developing specialized agent-cell modules for finance and digital commerce, with operational modules coordinating their interaction. Science driven innovation for aligned and adaptive ecosystems.