Technologies of
Global Impact
We don't just write academic papers. We transform fundamental discoveries into applied protocols that reshape the digital economy. From mathematical entropy control to creating a new, machine-readable web.
General Theory of Stupidity
We made the transition from philosophy to physics. For the first time in history, the phenomenon of "Stupidity" has received a rigorous mathematical proof and predictive model. Petrenko's Formula opens perspectives not only for modern psychology but also for cybernetics and artificial intelligence architecture.
Fundamental TheoryFormalizing the Immeasurable
Before us, Stupidity was considered a subjective quality or lack of mind. We introduced the G-metric — a precise state function of the system. This allows us to engineer the failure point of human consciousness and AI models just as one calculates the tensile strength of metal.
Discovery of "Cognitive Singularity"
We experimentally proved the existence of a phase transition at entropy $D \approx 0.7$. At this point, there is not a linear decline in decision quality, but an exponential collapse of agency. This is a fundamental constant of information security previously unknown to science.
Deconstruction of IQ
We mathematically proved the orthogonality of Intelligence ($I$) and Rationality. Our model explains the mechanism of "Motivated Amplification" for the first time: why increasing computational power (IQ in humans or parameters in AI) without entropy control increases rather than decreases the probability of fatal errors.
AI Optimization (AIO)
The fundamental conflict of the digital age: The Internet is built for eyes (HCA), but consumed by algorithms. We created the Machine-Centric Architecture (MCA) standard — a direct knowledge transfer channel for machines. For the first time in Web history, a parallel, deterministic information layer has been created, eliminating interpretation entropy.
Read ResearchHCA vs MCA
The entire modern stack (HTML/CSS) is Human-Centric Architecture (HCA), creating 70% noise for AI ($H_{index} \approx 0.7$). We propose not to "optimize" this noise, but to create a parallel layer of Machine-Centric Architecture (MCA), where information is structured deterministically, without visual artifacts.
Content Envelope
A unified standard for AIO (publishing) and ECR (integration). It is a cryptographically signed container holding synchronized layers: Narrative (pure text), Index (semantic anchors), and Structure (typed data). This is the end of the web scraping era.
Noise Dominance Theorem
Applying G-Theory to machines, we proved: reducing input entropy ($D$) yields a greater quality gain than increasing model parameters ($I$). AIO ensures 83% token reduction and a 21x growth in relevance, making AI not only smarter but also economically efficient (Green AI).
Neural Bytecode (NBS)
Fundamental paradigm shift: from trying to teach machines our language to creating a language for machines. NBS is an AI-native Intermediate Representation (IR) that eliminates the entropy of human syntax. This is the end of the "text" thinking era and the beginning of the era of pure, vector logic.
Read ResearchCognitive Firewall
First time achieving 0% hallucination rate. NBS eliminates semantic noise ($D$), keeping the model in the "Rationality Zone". It's not just code, it's mathematically proven protection against cognitive collapse, turning probabilistic generation into deterministic execution.
The "Cognitive Key" Effect
We discovered that Python's verbosity suppresses true model intelligence. Switching to NBS instantly unlocks hidden reasoning capabilities (Depth 40+) previously inaccessible due to the "syntax tax". This is an instant IQ boost of 200-300% without fine-tuning.
Resident Execution & Green AI
NBS solves the global energy consumption problem. Compressing logic by 46% and executing via NBS-VM (Tensor-VLIW) directly on the GPU turns "heavy" reasoning into efficient matrix operations. This is the only path to sustainable AI scaling amidst energy deficits.