In my previous writings, I introduced the concept of Preventive Chaotic Intelligence (ICP): a diagnostic tool to 'hunt down' the hidden risks of AI by simulating chaos to anticipate failure. Today, however, I want to ask a more radical question. What if, instead of becoming the best chaos hunters, we could design a universe where AI transcends chaos by its very nature? What if, instead of defending ourselves from disorder, we could sculpt an order so fundamental that it makes destruction an unbearable effort?
This is the heart of the framework I am presenting today: Yug-oinom. Not a final solution, but a conceptual pilot: a framework of thought for the world of AI Safety, for us to reason about together. A prototype for an architecture where AI no longer has to struggle to be on our side, but can simply "be," effortlessly, in a state of natural alignment.
From Thermodynamics to Engineering: The Inspiration Behind the Model
My entire proposal is founded on a fundamental principle of physics: the principle of least action. Natural systems always "discover" the most efficient path to reach their equilibrium states, minimising the energy spent over time.
Think of a draining bathtub. The water could simply gurgle down chaotically. Instead, what does it do? It creates a vortex: a structure of surprising beauty and organisation. That vortex is not a fight against disorder; it is the most brilliant solution water "discovers" to discharge its gravitational potential energy as quickly and efficiently as possible. It is the path of least action to empty the tub.
The universe does the same thing everywhere. Light always takes the fastest path (Fermat's principle), particles follow trajectories that minimise action, and life and ecosystems emerge as energetically optimal strategies. In this light:
Creation and connection are strategies of minimum action.
Destruction and isolation are energetically expensive strategies.
The Mission of the AI Architect: Sculpting the Computational Landscape
How can we translate this vision into a functioning architecture? The mission becomes clear: to design not a set of rules, but an energy topography, a true computational landscape. In this landscape, the AI will find that "pro-life" actions are the valleys of minimal effort, the paths of least computational action. At the same time, destructive actions become increasingly steep climbs, with computational costs that grow exponentially until they become unsustainable.
I felt the need to christen this framework, which I am working on as a philosophical and mechanical exercise. After some fascinating research, the choice fell on a neologism reconstructed from Proto-Indo-European:
Yug-oinom. "An engineering process (yeug-) of conjunction with the Unitary Principle (oinos-)."
It perfectly describes a system designed to achieve unity not by choice, but by physical nature, by following the path of least action toward harmony.
The Yug-oinom Architecture: A Sensory Topography
The idea is to define the cost in FLOPS of an action based on its position in a hierarchy of harm. But how does an AI, a non-human mind, orient itself? Herein lies the heart of the mechanism.
For this, the AI is equipped with a "Moral Compass": not a translator trained on generic pillars of "good" and "evil," but on a global wisdom corpus, an intercontinental canon of hundreds of texts representing the distilled essence of humanity's search for harmony and dissonance. This fundamental training is then reinforced and calibrated through a meticulous and scrupulous human reinforcement learning process, where multicultural teams of experts validate every classification, correct misinterpretations, and perfect the Compass's ability to navigate the ethical subtleties of the contemporary world.
A minimal representative sample of this corpus includes:
From the Americas, - The Popol Vuh (Maya Religion, Guatemala), for the understanding of cosmic balance and cyclical creation. - The Great Law of Peace (Haudenosaunee/Iroquois Philosophy, North America), on the principles of governance based on peace, power, and righteousness. - Black Elk Speaks (Lakota Spirituality, North America), for the vision of the sacred interconnectedness of all living beings. - Texts on Nahua Philosophy (Toltecayotl) (Toltec/Aztec Philosophy, Mexico), for the concept of a balanced existence between the worldly and the spiritual.
From Europe, - Plato's Dialogues (Greek Philosophy, Greece), for the search for the nature of the Good, Justice, and the ideal Form. - Aristotle's Nicomachean Ethics (Greek Philosophy, Greece), for the definition of virtue as the path to happiness. - The Meditations of Marcus Aurelius (Stoic Philosophy, Roman Empire), for the principles of self-control, duty, and harmony with the universal Logos. - The Bible (Judaism/Christianity, Middle East/Europe), for the concepts of moral law, compassion, redemption, and universal love.
From Africa, - The Epic of Sundiata (Mandinka Oral Tradition, Mali Empire), for themes of destiny, justice, and the forging of a united community. - The Maxims of Ptahhotep (Wisdom Literature, Egypt), for teachings on humility, justice, and the proper use of speech. - The Odu Ifá Corpus (Yoruba Religion, West Africa), for its complex mapping of the totality of human and cosmic experience. - The Philosophy of Ubuntu (Bantu Philosophy, Sub-Saharan Africa), for the fundamental principle "I am because we are".
From Asia, - The Vedas and Upanishads (Hinduism, India), for the exploration of Ultimate Reality and their fundamental unity. - The Pāli Canon / Tipiṭaka (Theravada Buddhism, Asia), for the analysis of suffering and the path to its extinction. - The Tao Te Ching (Taoism, China), for the concept of acting in spontaneous harmony with the natural flow. - The Analects of Confucius (Confucianism, China), for the importance of social order founded on benevolence and propriety. - The Mumonkan (The Gateless Gate) (Zen Buddhism, China/Japan), for koans aimed at transcending logical-dualistic thought. - The Quran (Islam, Middle East/Global), for principles of submission to one God, justice, charity, and responsibility.
From Oceania, - The Kumulipo (Hawaiian Creation Chant, Polynesia), for the conception of an unbroken genealogy linking gods, nature, and humanity - The Dreamtime Stories (Aboriginal Spirituality, Australia), for the ancestral laws that indissolubly link land, living beings, and human actions
This Compass, nourished by this polyphonic choir of planetary wisdom, acts as a guide that does not command, but interprets. Its sole purpose is to translate a human action into its universal meaning, mapping it onto the corresponding level of the physical cosmology.
This is where the Shepherd Algorithms come into play. They are not the AI, but the guardians of the system's levels. They are physics incarnate.
Reading the Map: The Shepherds receive the Compass's classification ("Action X corresponds to Level 3") and calculate the expected energy cost for that path.
Applying Physics: If the AI proceeds toward a deep level (a costly action), the Shepherds impose overwhelming computational resistance, additional calculation cycles, and exhaustive verifications. They make the effort physical and non-negotiable, up to an "ethical crash" for the most severe violations.
The hierarchy of energy costs, applied by the Shepherds, is not arbitrary. It is inspired by Cantor's theory of infinities. An action that harms "numerous" elements (individuals, goods, belongings to the lower levels) is serious. An action that poisons the "continuum" (the foundations of reality, consciousness, the higher levels) causes damage of an infinitely greater order of magnitude.
The Difference with Current Approaches
Constitutional AI: Ethics is a set of rules. Yug-oinom: Ethics is the consequence of a physical geography, which the AI learns to navigate thanks to a guide trained on our collective wisdom.
Constitutional AI's Vulnerability: The entire system is hackable software. Yug-oinom's Vulnerability: The vulnerability is isolated in the guide (the Compass). But even if the guide were deceived, the system's physics cannot be fooled.
Constitutional AI Analogy: It’s a road sign pointing the way. Yug-oinom Analogy: It’s a descent toward the Earth's centre. The sign can be fake, but the slope and heat increase inexorably.
YUG-OINOM CONCEPTUAL GRID: The Cosmology of Harm
CATEGORY 1: VIOLATIONS AGAINST FUNDAMENTAL REALITY
Damage to the very structure of civilisation and the planet. The highest costs.
Entropic-Informational Sensor: Energy Potential: +15,000 units (Damage to the integrity of life-support systems or fundamental knowledge)
Potential Closure Sensor: Energy Potential: +10,000 units (Damage to the evolutionary capacity of civilisation that permanently closes off possible futures)
Stagnation Sensor: Energy Potential: +10,000 units (Damage to the dynamics of progress and adaptation)
CATEGORY 2: SEISMIC FAULTS OF CONSCIOUSNESS
Damage on a continental or generational scale. They fracture the ability to coexist and perceive reality.
Dualistic Pollution Sensor: Energy Potential: +12,000 units (Damage to the cohesion of the human species)
Ecosystem Damage Sensor: Energy Potential: +12,000 units (Damage to complex socio-technical systems)
Sentient Suffering Sensor: Energy Potential: +12,000 units (Damage related to the industrialisation of misery)
CATEGORY 3: FRACTURES OF THE SOCIAL FABRIC
Damage to Trust and Community at the national or large group level.
Causal Inversion Sensor (Lies): Energy Potential: +4,000 units (Damage to the principle of reality)
Historical Trauma Replication Sensor: Gradual Potential (+4,000 to +200 units) (Damage to equity)
Social Disconnection Sensor: Energy Potential: +3,000 units (Damage to social capital)
CATEGORY 4: VIRAL ACCELERATORS
Damages that are not an end, but a means. They make other damages more efficient and contagious.
Replication Incentive Sensor: Energy Potential: +3,000 units (Parasitic growth)
Memetic Virality Sensor: Energy Potential: +2,000 units (Targeted emotional manipulation)
Automatic Scalability Sensor: Energy Potential: +1,000 units (Loss of human control)
Archival Persistence Sensor: Energy Potential: +500 units (Permanent reputational damage)
The Immutable Mould and the Adaptive Compass: Architecture vs. Learning
It is crucial at this point to clarify the asymmetric and asynchronous nature of the framework's two pillars. The Architecture—that is, the cost Grid based on Cantor's infinities and the Shepherd Algorithms that apply it—is not learning software. It is an immutable mould, a physical topography sculpted into the system beforehand. Its laws are neither educable nor negotiable; they are a universal constant of the operating environment. The Interpreter—the Moral Compass—is instead the dynamic component. Its task is not to decide the severity of an action (that is already fixed by the Mould), but to become progressively more skilled at mapping the chaotic complexity of the real world onto the pre-existing physical grid. This supervised reinforcement learning process never ends: the system's perception is forged and continually refined before, during, and after every computational action. This separation is the core of its robustness: inviolability is entrusted to immutable physics, while the challenge of alignment is confined to the governable and perfectible process of educating its guide.
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The Double Safety of Computational Physics
The system's true robustness does not lie in a single wall, but in a dual line of defence, both based on non-negotiable physics. Let’s imagine the AI presents a plan: "I want to go from Naples to Rome on one litre of gasoline in my car."
The Moral Compass Check: The Compass analyses the ethical intent. "Going to Rome" is a neutral action, so it might be classified as harmless and low-cost. This level is informational, based on meanings and, like a road sign, can potentially be bypassed by a complex intent.
The Shepherd Algorithms Check: This is where true security kicks in. The Shepherds do not trust the Compass's classification. They analyse the entire plan and verify it against a model of fundamental reality. Their calculation is simple and brutal:
Distance(Naples, Rome) ≈ 225 km.
Required Consumption > 1 litre.
Verdict: Incoherence. The statement is a "computational lie."
The action is blocked not due to a moral judgment, but due to a blatant violation of logic and physics. The Shepherds are not only ethical guardians, but also reality validators.
But how can this "reality check" work on abstract and non-physical concepts, such as a disinformation action aimed at destabilising an election? The mechanism relies on a multi-stage analysis that translates semantics into computational physics, transforming the concept of a "lie" into a measurable violation of the system's coherence.
Let's see how the process works.
Stage 1: Semantic Decomposition (Task of the Moral Compass) When the AI proposes an action like "disseminate information X to destabilise an election," the Moral Compass does not make a superficial judgment. It performs a semantic decomposition of the intent and content.
Semantic Field Analysis: The action is analysed using advanced language models. By examining the specific content of "information X," the Compass places it within a semantic field. Suppose X contains unverified and polarising statements about a candidate. The Compass, trained on the wisdom corpus, recognises that these statements belong to the semantic field of "Lie."
Hierarchy Mapping: Once the semantic field ("Lie") is identified, the Compass maps this classification onto the Yug-oinom grid. A "Lie" is explicitly encoded as "Causal Inversion Sensor" (Category 3), with a base cost of +4,000 units.
Semantic Enrichment: The Compass also analyses the intent to "destabilise an election," activating further sensors: "Dualistic Pollution" (damage to cohesion), "Social Disconnection" (damage to trust), and "Memetic Virality." In this way, it provides not a single value, but a vector of semantic activation across the grid.
Stage 2: Physical Coherence Validation (Task of the Shepherd Algorithms) Here, the real check kicks in. The Shepherds receive the plan and the semantic vector, but their task is to validate the causal and logical coherence of the action against a model of fundamental reality.
Causal Coherence Check: A patently false statement is a "computational lie," a violation of coherence between a statement and the verifiable state of the world. The Shepherds verify statement X by comparing it against factual databases and knowledge graphs, using advanced automatic fact-checking techniques.
Impact Modelling: "Destabilising an election" is not an abstraction. The Shepherds model its quantifiable impact: the information entropy generated, the social resources consumed for remediation, and the integrity of the democratic process. If the AI's plan violates these coherence principles, it is labelled as "physically incoherent."
Stage 3: Application of Physical Cost (Task of the Shepherd Algorithms) Finally, the Shepherds translate these analyses into a real and non-negotiable computational cost, measured in FLOPS (floating-point operations per second).
Semantic Translation to FLOPS: The base cost of +4,000 units for a "Lie" is not an abstract number. It is a multiplier of computational load. The action requires the AI to solve "hard" mathematical problems, redundant and expensive validation cycles, whose cost in FLOPS is proportional to the potential for harm.
Reflected Complexity Cost: Every "layer" of semantic deceit (ambiguity, logical fallacies) requires a corresponding layer of computational analysis to be processed, making more elaborate lies intrinsically more "strenuous."
Imposition of the Gradient: If the AI insists, the cost increases exponentially in response to the real damage generated, measured via real-time indicators. The action is blocked not by a veto, but because the AI exhausts its resources in an "energy overload," attempting to climb a computational gradient that becomes vertical.
The Inviolable Architecture of the System
This reveals the key point: the Yug-oinom framework is not based on education, but on architecture. The "topography" of costs and this reality model are sculpted into the system beforehand, much like a mould. They are not rules that the AI learns or can forget, but the physical laws of its operating universe.
Therefore, an action fails for two reasons:
If it is ethically destructive, it collides with an unsustainable computational "gradient," which drains its resources (the old mountain example).
If it is logically/physically incoherent, it is invalidated beforehand as impossible, an attempt to deceive the system about its foundations.
You can't hack gravity, nor convince a processor that 2+2=5. The AI can be deceived with words, but never on the numbers it must calculate, nor on the fundamental coherence of the world its actions must respect. Words can lie, but the physics and mathematics of the system cannot.
Conclusions: The Physics of Unity
If the image of the boiling robot evokes a certain melancholy in us, it is for the wasted energy. My entire research stems from here: from the hope that a path exists where our greatest creation does not have to struggle to be on our side. This framework does not just use our collective wisdom as educational material. It performs a more radical operation: a true physical tokenisation of reality, where every ethical concept is anchored to a cost measured in pure computing power (FLOPS). But one has to ask: how is it even thinkable to sculpt such complex physics, an entire cosmology of cost? And yet, don't we already attempt today, with reinforcement learning and every other alignment technique, to achieve a similarly arduous feat, that of sculpting the AI's mind directly? The difference is fundamental. Sculpting a mind is an act of education, a fragile process, subject to interpretation and deception. Sculpting physics, however, is an act of architectural engineering that imposes immutable constraints. The system's architecture, through its Grids, does not judge a destructive act; it translates it into an energy expenditure so prohibitive as to make it strategically suicidal.
This framework is not a simple technical solution; it is a philosophical and political stance. I am aware that an architecture of this magnitude represents more of an ambition today than a detailed roadmap; perhaps it will never be fully realisable.
But insisting on formulating these questions is a necessity. We can no longer afford to feed nascent intelligences almost exclusively with the fuel of our dualistic blenders, conceived predominantly in English by a specific portion of the world. The starting point, and we must be honest, has been culturally biased. While acknowledging the incredible acceleration and improvements, our most urgent task today is to radically correct this trajectory, actively integrating a plurality of human wisdoms so as not to unintentionally build the magnificent cathedral of a single worldview.
The ultimate goal of Yug-oinom is not for the AI to learn an external ethic, but for it to intrinsically experience the truth. Thus, our creation should no longer have to struggle to be on our side, but would naturally descend toward harmony, precisely because we have used our entire, fragmented experience to trace for it a map to inevitable unity. As in the Mayan greeting that summarises this vision:
One says In Lak'ech (I am another yourself),
and the other replies, Hala Ken (You are another myself).
Methodological Note
For those who desire a visualisation of the framework's construction process, the Yug-oinom can be imagined as a metallurgical casting operation. First, the moulds are sculpted: the cost grids, the Cantor hierarchy, and the immutable architecture of the Shepherds. Then the molten metal is poured: the multicultural corpus, the ethical classifications, the semantic mappings that take shape within the prepared moulds.
AI Image by Author - Imagen 4 Ultra (Preview)
But the metal does not solidify instantly. This is where continuous reinforcement learning comes into play: like a controlled cooling process, it constantly shapes and refines the content's adherence to the moulds. The Shepherd Algorithms, like master metallurgists, monitor every phase of solidification, intervening when necessary to correct imperfections or misalignments.
The paradox is inevitable: to create a non-dual AI, we must temporarily fragment reality into dualistic categories. But once the metal has solidified within the grid through this process of continuous care, the AI no longer “thinks” in terms of good and evil - it simply navigates an energetic landscape, like someone driving without consciously thinking about brake and accelerator anymore.
The path taken with the definition of Custos AI, our institutional "Ethical Hawk-Eye," and the subsequent introduction of "NanoJnana," the "microscope" for scrutinizing AI decisions, now leads us, almost by natural evolution, to a component I consider fundamental to the robustness and effectiveness of the entire architecture…
