Introduction
DF AI Research explores artificial intelligence and fundamental sciences through a cross-disciplinary approach. Our research fields span symbolic AI, computational physics, emergent biology, and applied AI systems. These domains provide the foundation for our projects and publications.
1. Artificial Intelligence & Symbolic Models
We investigate symbolic AI frameworks and emergent intelligence systems. Our work focuses on logical computation, information compression, and adaptive models. Projects such as CUP Framework, CUP-2.0, and Blob IQ are directly connected to this field.
Key themes:
Symbolic computation and logic-based AI
Emergent neural intelligence
Interdisciplinary approaches combining mathematics and information theory
2. Computational Cosmology & Physics
Our research extends to the fundamental structure of the universe. Using logical models such as the ΨΛ Grid, we explore connections between light, time, gravity, and matter. This field bridges cosmology, physics, and information science.
Key themes:
Logical models of the universe (ΨΛ)
Time, entropy, and information structures
Cross-disciplinary cosmology and physics research
3. Computational Biology & Emergent Life
The LIFE Sandbox AI project and its LSARN digital brain are part of this research axis. We design mathematical genomes (ADNΣ) and test protocols for digital life, adaptation, and self-evolution of neural systems.
Key themes:
Mathematical genome and emergent intelligence (ADNΣ)
Digital life simulations (LIFE Sandbox AI)
Evolutionary neural architectures and adaptive agents
4. Applied AI & Creative Systems
We apply artificial intelligence to practical and creative domains, including visual data, WebGL, and interactive media. The Neural Pixel AI System and our work on AI in fashion and photo editing are examples of applied research fields.
Key themes:
Image processing and pixel-level AI
AI-driven design and fashion editing
Real-time applications in WebGL and interactive platforms