Science, Technology, Engineering & Mathematics for Artificial Intelligence
Vektra Technologies | AI Division
This repository contains open research in mathematics, science, and engineering applied to artificial intelligence. The work spans original mathematical frameworks, bio-inspired architectures, cognitive science foundations, and cross-domain AI research.
Everything here is the math and the science — the theoretical foundations behind building intelligent systems. No product code. No implementation details. Just the ideas.
Original mathematical frameworks for agent cognition and control systems.
canon/— The canonical mathematics research packet. Covers agent numeracy, arithmetic of state, algebra of invariants, geometry of state spaces, calculus and sensitivity, probability and estimation, control and dynamical systems, graph and network mathematics. Includes proof status registers and experimental protocols.textbook/— A complete textbook building from first distinctions through the Lineage Equation.lineage-papers/— Research papers on the Lineage Equation and CognitiveNet.
Architectures derived from biological systems — virtual blood cells, virtual nervous systems, neural pulse signaling, immune system models, biological regeneration, homeostasis, and cellular replication applied to AI.
Foundational research in emotional spectrum models, drive neuroscience, neural architecture, emotional development across lifespans, and living research system architecture.
Cross-domain AI research spanning biology, chemistry, engineering, geopolitics, history, physics, politics, science, and space.
Research should be open. The math doesn't care who reads it — it cares whether it's correct. We publish this work because the field moves faster when foundations are shared.
Pablo — Founder, Vektra Technologies
MIT