Projects

A distributed architecture for conditioned self-being and self-becoming. The Ziran System is a total relational observation platform operating across scales — from the molecular to the cosmic — integrating multiple agencies, multiple temporalities, and open configurations toward a more-than-human future. Observe · Measure · Sample · Analyze · Intervene · Reconfigure · Evolve.

Multiple Scales · Multiple Agencies · Multiple Temporalities · One Relational Field

Instead of studying intelligence only through contemporary database-dependent artificial intelligence, this project investigates the minimal configuration in which learning, memory, adaptive self-maintenance, endogenous state change, and potentially thought-like processes could emerge within a self-growing bio-artificial system.

The project connects to biological intelligence, organoid computing, non-database intelligence, self-growing systems, minimal cognition, artificial life, embodied and enactive cognition, AI philosophy, and epistemic boundary redistribution.

The research question is not simply whether biological AI can become conscious. The deeper question is: which minimal configuration and generative interval would justify the transition from matter or biological activity to learning entity, cognitive entity, thinking entity, or subject?

Applies generative interval analysis and total-relational hyperflat analysis to food production, agricultural systems, sexual reproduction, and their relationships to ecological extinction. Examines how the configurations that sustain biological reproduction and food systems have generated, transformed, and may terminate across different scales and temporal intervals.

Analyzes the transition toward machine-maintained machine systems and the displacement of human labor from machine reproduction. Examines machine reproductive closure, energy dependencies, and post-human capital formation.

A reconstruction of political economy for the age of autonomous machine systems. Investigates how classical categories of labor, value, and surplus undergo transformation under machine ecology.

A methodological framework for auditing AI and machine systems without granting ontological priority to any single category — human, machine, institution, or state — while preserving real asymmetries of control and access.

Investigation of conditions under which AI systems can engage in genuine philosophical inquiry, self-critique, and the revision of their own conceptual frameworks.