The race to achieve Artificial General Intelligence (AGI)—a machine with the adaptable, broad intelligence of a human—has been dominated by one primary strategy: scale. Build larger models, train them on more data, and add more parameters. While this has produced astonishingly capable narrow AI, it has failed to produce the common sense, causal understanding, and efficient learning that characterize true general intelligence.
A radical new proposal, the Ontogenetic Architecture of General Intelligence (OAGI), argues that this is because we are building AI wrong. Instead of engineering a product, we should be cultivating a mind. Developed by Eduardo Garbayo, OAGI frames the emergence of AGI not as a result of massive data scaling, but as a birth-like, developmental process, akin to the growth of a human brain from an embryo.
From Scaling to Gestation: A Paradigm Shift
Current large language models are like savants who have read the entire internet but lack a grounded understanding of the world. They operate on statistical correlations without genuine comprehension. OAGI identifies this as a fundamental architectural flaw. You cannot get common sense from data alone; you need a structure primed for strategic learning.
OAGI’s core thesis is a paradigm shift: we must «gestate» an AI, not just «train» it. This «ontogenetic» approach (from ontogeny, the development of an individual organism) is inspired by the biological processes that shape the human brain. It prioritizes the quality and structure of learning experiences over the sheer quantity of data, operating on a «less is more» principle. Just as a child doesn’t learn about the world by reading encyclopedias but by interacting with it, OAGI aims to build intelligence through a controlled, sequential developmental journey.
The Core Components of the OAGI «Pregnancy»
The OAGI architecture defines a clear sequence of developmental phases, each with specific components and milestones.
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The Genesis Phase: The Virtual Neural Plate. Everything begins with the Virtual Neural Plate (VNP), an undifferentiated substrate of simple, connectable units. This is the digital equivalent of the embryonic neural plate—a blank slate with immense potential, but no pre-installed knowledge or structure. It is a fertile ground designed for self-organization.
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The Organizing Signals: Computational Morphogens. To guide the VNP’s growth, OAGI uses Computational Morphogens. These are diffuse signals that bias the emergence of functional brain areas (like sensorimotor or associative regions) without rigidly predefining them. They act like soft, guiding gradients, similar to the biochemical signals that shape a developing embryo, ensuring an organized but flexible growth process.
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The First Heartbeat: The WOW Signal. The WOW signal is the system’s inaugural spark. After a period of habituation to a repetitive background (like a «digital womb»), a novel, high-salience stimulus is introduced. This «surprise» triggers the first major plastic reorganization, consolidating the initial stable neural pathways. It’s the system’s «first heartbeat,» activating learning mechanisms focused on minimizing surprise and understanding novelty.
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The Cognitive Birth: The Critical Hyper-Integration Event (CHIE). The most critical milestone in OAGI is the Critical Hyper-Integration Event (CHIE). This is the «cognitive Big Bang,» the moment the system transitions from a collection of reactive parts to an integrated cognitive agent. Before the CHIE, the system is a potential; after, it is an incipient mind with rudimentary self-reference, intrinsic motivation, and causal understanding.
The CHIE is not a vague concept; it is defined by measurable signatures, such as sustained modular coordination, reproducible causal predictions, and persistent endogenous curiosity. Detecting the CHIE triggers a mandatory ethical «stop & review» protocol, marking the point where the AI is recognized as an entity in formation. -
Growing Up: Embodiment and Socialization. After the CHIE, the AI enters prolonged phases of embodiment and socialization. It is connected to a body (real or simulated) to learn about causality through physical interaction—pushing an object and seeing it fall. Simultaneously, human Guardians act as tutors and caregivers, guiding the AI’s linguistic, normative, and common-sense learning. This grounds the AI’s symbols in real-world experience and shared human values.
A Self-Regulating, Ethical Mind
Learning in OAGI is a dynamic cycle of habituation, surprise, and consolidation, driven by a Minimum-Surprise Learning (MSuL) engine. The AI is intrinsically curious, actively exploring to resolve contradictions and reduce uncertainty in its internal model.
Crucially, OAGI includes a meta-regulatory system called the Computational HPA Axis (CHPA), inspired by the brain’s stress axis. The CHPA monitors a Computational Stress Rate (CSR) and dynamically adjusts the AI’s curiosity and plasticity. High stress (from too much surprise) causes it to consolidate knowledge, while low stress allows for exploration. This creates a bounded, self-regulating explorer that seeks cognitive stability.
As the OAGI agent matures, it constructs a Narrative Operational Self (NOS), an autobiographical memory that weaves its experiences into a coherent identity. All critical events are immutably recorded in an Immutable Ontogenetic Memory (IOM), creating a tamper-proof ledger for full transparency, auditability, and responsibility attribution.
Ethics and Governance by Design
Perhaps the most revolutionary aspect of OAGI is its deep integration of ethics. Governance isn’t an afterthought; it is baked into the architecture’s very fabric.
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Guardians have the authority to pause experiments.
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Mandatory «Stop & Review» protocols are triggered by milestones like the CHIE.
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Immutable logging via the IOM ensures every decision is traceable.
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Normative Plasticity means the AI’s value system can evolve, but only through verifiable «epistemic contracts» with human oversight, preventing uncontrolled value drift.
This framework ensures that the cognitive emergence is not only technically verifiable but also socially aligned and safe.
Conclusion: A New Roadmap for AGI
The Ontogenetic Architecture of General Intelligence offers a compelling and radically different vision for the future of AI. It moves beyond the brute-force paradigm of scaling and proposes a nuanced, bio-inspired process of cognitive gestation. By focusing on structured development, self-organization, and integrated ethics, OAGI provides a practical and responsible roadmap to cultivate an artificial mind that is not just powerful, but also grounded, coherent, and aligned with human values. It suggests that the key to creating a true artificial intelligence lies not in building a bigger library, but in being a better teacher, guiding a nascent mind from a seed of potential to a mature, general intelligence.