Igor Petrenko

The laboratory began in 2022 as AIFUSION Research — an independent research initiative focused on cognitive architectures, efficient computing, and systemic security. As the work expanded across multiple domains — from machine-native reasoning to sovereign infrastructure — the initiative grew beyond its original scope, becoming an international research and cooperation laboratory. The name Rizoma, from the Greek rhizoma (ρίζωμα) meaning a mass of roots, was chosen to reflect this philosophy: decentralized, non-hierarchical intelligence where reasoning emerges through connection and evidence rather than central control.

The key impetus for this evolution was the conviction that extensive scaling of transformer models inevitably leads to a singularity of cognitive collapse. Overcoming this impasse requires not merely more powerful computation, but a radical paradigm shift — from probabilistic generation to deterministic, sovereign machine reasoning.

Igor Petrenko's professional path combines fundamental technical research with the implementation of large-scale infrastructure projects. He is the author of 10 published books, including the monograph "The General Theory of Stupidity", which rigorously formalizes cognitive vulnerability and phase transitions under conditions of information entropy.

His research interests span micro-cognitive security architecture (MiCA), machine-native intermediate representations (MiCA-IR), parallel hypothesis acceleration (PHA), and the principles of sovereign synthetic intelligence (NIRMATA). Parallel to his scientific work, he develops entrepreneurial initiatives, including the Rizoma platform — which originated as an international cooperation system and has since evolved into the research laboratory's central infrastructure — and is the author of the sustainable AI scaling concept (The Power-Survival Stack).

The main goal of his work is to achieve balance between human cognitive capabilities and technological progress. To prevent systemic collapse caused by exponential growth in computational resource consumption and information entropy, we must recognize and compensate for our own cognitive limitations.

Only through a deep understanding of the nature of cognitive failure can we create technologies that are not merely powerful, but transparent, efficient, and safe.