Qubic’s Open Science Team brings neuroscience, artificial intelligence, and engineering together to document, validate, and advance Aigarth — Qubic’s approach to building artificial general intelligence. Their work bridges the biology of human intelligence and the design of decentralized, evolving AI systems.
Qubic’s aim is to create and evolve an artificial general intelligence from the ground up. Rather than depending on large GPU clusters, Aigarth pursues a decentralized, CPU-based, and evolutionary path — using a self-modifying “Intelligent Tissue” and a ternary (TRUE / FALSE / UNKNOWN) computing model to grow problem-solving ability instead of hand-designing it. The goal is a more accessible, sustainable, and democratized route toward safe and beneficial AGI.
Two researchers, one architecture. Co-inventors of Neuraxon, bridging neuroscience and machine intelligence.
Neuroscientist, scientific advisor, and mentor whose work spans the brain, emotions, human behavior, and the convergence of human and artificial intelligence. A professor at UNIR and Scientific Advisor at Qubic, he is co-author of 20 Q1/Q2 publications, two books and co-inventor, with David Vivancos, of the Neuraxon architecture. A first-person explorer of consciousness and a practitioner of meditation for the past 30 years.
Science and technology serial entrepreneur working since 1995 across AI, virtual reality, neurotechnologies, and deep learning, with five startups and 7 books and an AI encyclopedia to his name. A keynote speaker and machine “teacher” with 28,000+ hours in AGI research at Artificiology, he leads brain research at MindBigData — home to the largest open dataset of multimodal brain signals — and is co-inventor, with Dr. José Sánchez, of the Neuraxon architecture.
Authored by José Sánchez García and David Vivancos. Newest first.
Builds on v1 by adding a unified four-step pipeline (adaptive time-warping per synapse, input-conditioned dynamic decay, a complemented-state mechanism to prevent information loss, and astrocyte-gated multi-timescale plasticity) plus richer neuromodulation across nine receptor subtypes, aiming to more closely mirror real cortical neuron behavior.
Introducing Neuraxon, a bio-inspired computational unit that replaces the classic binary perceptron with continuous-time, trinary-state (excitatory / neutral / inhibitory) processing and structural plasticity — synapse formation, collapse, reconnection, and occasional neuron death.
An integrated analysis of human intelligence and its artificial counterpart through Aigarth — covering the biology of intelligence, the self-modifying “Intelligent Tissue,” ternary computing, and an evolutionary, decentralized path toward AGI.
The Neuraxon architecture is open. Read the code, run the Space, or watch it grow live.
The reference implementation and source for the Neuraxon computational unit.
View repositoryAn interactive Space to explore Neuraxon behavior directly in the browser.
Open the SpaceWatch the intelligent tissue grow and reorganize in real time at nxon.online.
Launch live demoNotes and explainers from the Qubic Scientific Team.
What Is AGI? The Limits, Visions, and Definitions of Artificial General Intelligence
What Can a Neuron Compute? Dendritic Computation and Brain-Inspired AI
How Do We Measure the Intelligence of a Machine? The g Factor, ARC-AGI, and the Future of AI Evaluation
The g Factor in Artificial Life: From Spearman's 1904 Classroom to Evolved Artificial Brains
Brain Criticality and the Branching Ratio in Neural and Artificial Networks: A Bioinspired Principle in Neuraxon
Can an AI Have Experience? Lerchner and the Abstraction Fallacy
Digital Ecosystems, Conway’s Game of Life, and Why Emergent Complexity Matters for Decentralized AI
Intelligence Is Not Scale: A Scientific Response to Jensen Huang's AGI Claim
Conscious Machines, Intelligent Organisms: The Science Behind AI Consciousness