Introduction
DF AI Research develops interdisciplinary projects combining artificial intelligence, symbolic modeling, computational physics, and biology. Below is a selection of our major research projects with summaries and links for further exploration.
1. LIFE Sandbox AI / LSARN
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Summary: A digital life simulation where entities evolve autonomously through emergent neural networks. No behaviors are hard-coded: intelligence emerges through perception, mutation, and adaptation.
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Key aspects: modular architecture of “mini-brains,” stochastic genetic mutations, millions of coexisting agents, and ethical end-of-life protocols.
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Link: Life Sandbox AI
2. ADNΣ – Mathematical Genome for Emergent Neural Intelligence
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Summary: A mathematical genome designed to encode and transmit information for emergent intelligence, integrated within the LSARN framework.
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Key aspects: structured coding, universal patterns, hereditary transmission of neural traits, controlled mutation experiments.
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Link: ADNΣ Genome
3. LSARN — The Living Digital Brain
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Summary: The central digital brain of the LIFE Sandbox project, managing memory, dreams, communication, and potential emergent consciousness.
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Key aspects: interconnected neural modules, emotional states, long-term memory, ethical termination preserving the agent’s neural history.
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Link: LSARN Digital Brain
4. CUP Framework
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Summary: A unified computational protocol for symbolic modeling, memory optimization, and logical computation applied to AI and scientific simulations.
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Key aspects: modular structure, efficiency, scalability, integration with LSARN and other modules.
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Link: CUP Framework
5. CUP-2.0
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Summary: An advanced version of the CUP Framework, offering enhanced protocols, reduced redundancy, and support for real-time environments such as WebGL simulations.
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Key aspects: high efficiency, reduced memory load, designed for cross-disciplinary scientific use.
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Link: CUP-2.0
6. Neural Pixel AI System
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Summary: An AI system focused on pixel-level image processing and visual data analysis. Designed for intelligent filters, fine transformations, and visual modeling.
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Key aspects: low-level neural networks, adaptive vision filters, applications in visual data processing.
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Link: Neural Pixel AI System
7. Blob IQ Projects
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Summary: A collection of projects exploring adaptive and abstract intelligence, including scientific briefs and an educational research portal.
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Key aspects: conceptual experimentation, pedagogical resources, interactive demonstrations.
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Links:
8. Revolutionizing Fashion and Photo Editing with AI
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Summary: Practical application of AI in the fashion and photo industry, developing advanced tools for image editing and adaptive style transfer.
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Key aspects: AI-assisted editing, real-time filters, and creative applications of machine intelligence.
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Link: Fashion & Photo AI