This article addresses the phenomenon of artificial intelligence as an energetic-material system, using the Princonser Method. The universal laws that govern its development, stability, and transformation are identified. Through the ten foundations, it is argued how AI evolves by maintaining the proportion between informational energy and technological matter, and how its temporality is transcended through cyclical integration. Finally, a scientific law is formulated that synthesizes its essential dynamics.

Introduction

We live in an era where machines not only perform tasks but also learn, reason, and make decisions. This new reality, driven by artificial intelligence (AI), is transforming every aspect of our lives—from how we work and communicate, to how diseases are diagnosed or cities are designed. But what lies behind this phenomenon? How can we understand it from a deep, universal perspective?

This article offers a different view: analyzing the age of artificial intelligence not just as a technological advancement, but as an energetic and material system that follows universal laws. To do this, we use the Princonser Method, a scientific analysis tool that reveals the essential structures supporting any complex phenomenon.

We invite the reader to explore how AI, beyond being a modern invention, reflects fundamental principles that govern everything in the universe: balance, transformation, dependence, integration, and temporality. Through this reading, we will not only better understand AI, but also the world we inhabit and the future we are building.

Materials and methods

Elements of the Princonser Method

The Princonser Method is applied, recognizing in every system the proportional unity between energy and matter, governed by ten universal foundations: an essence, three principles, and six laws.

Princonser analysis matrix

The matrix comprises the following foundations:

  1. Universal Essence

  2. Principle of Inseparability

  3. Principle of Conservation

  4. Principle of Destruction

  5. Law of Dependence

  6. Law of Interaction

  7. Law of Integration

  8. Law of Disintegration

  9. Law of Temporality

  10. Law of Timelessness

Problem identification

Unstable material systems self-destruct, releasing energy. Technological obsolescence in AI causes the decomposition of material systems. This destruction releases knowledge, algorithms, and reusable experience as cognitive energy. Thus, the advancement of AI is also nourished by the destruction and surpassing of previous versions. Current facial recognition systems are possible thanks to analyzing failures in older versions, which released key learnings.

In unstable systems, the system's matter is transformed into energy, causing downward qualitative changes. When an AI system becomes obsolete, its material components lose functionality. This loss becomes residual information, but the global system degrades. Therefore, technological obsolescence implies functional disintegration of the AI system. A virtual assistant that cannot be updated ends up as a non-functional artifact, though it holds historical data.

All systems are temporary due to their disintegration. Their temporality is determined by the conservation of their essential structure. AI systems, like any others, have a limited duration determined by their capacity to conserve functional essence. When this balance is lost, the system tends to extinguish. Hence, the life cycle of an AI system depends on its energetic-material balance.

Solution to the problem

All forms of energy are conserved in a cycle of transformation from energy to matter and vice versa. AI transforms data (energy) into machine actions (matter). This conversion remains constant throughout its operation. Therefore, the sustainability of AI relies on maintaining this active cycle. A self-driving car converts sensor data into mechanical movements and back into new real-time inputs.

In all stable systems, input energy is transformed into matter, generating upward qualitative changes. Each algorithmic innovation in AI transforms its scope of application, leading to more complex and functional systems. Hence, AI evolves by integrating cognitive energy into increasingly sophisticated material structures. The use of AI in smart prosthetics demonstrates this upward transformation in medical biomechanics.

Energy, being timeless, can transcend systems and reintegrate into new ones according to the law of dependence and interaction. Conceptual advances in AI remain relevant even after the original systems disappear. This allows knowledge to be reintegrated into future technological developments. For instance, expert system logic has been reused in modern decision-support platforms.

Identification of the law

All systems in the universe are proportional units of energy and matter, transforming unidirectionally and cyclically. The AI era integrates informational energy (algorithms, machine learning) with tangible matter (robots, hardware). This means AI is a proportional unit between the intangible (simulated intelligence) and the material (physical devices). Its evolution relies on this essential balance. An autonomous medical robot illustrates this, combining algorithmic processing with mechanical structures.

In every system, energy and matter are inseparably proportional. Algorithms cannot operate without the hardware that executes them. Thus, AI's software and hardware must evolve together. Deep neural networks only work due to high-capacity GPUs, proving this inseparability.

Each type of energy corresponds to a specific form of matter in a stable system. In AI, algorithmic functions must align with appropriate architectures. This ensures that processing energy doesn’t exceed physical capacity. A neural chip designed for specific tasks prevents system overload and guarantees stability.

In all stable systems, energy and matter transform into each other while maintaining proportionality. AI systems operate in cycles where software and hardware continuously adapt. Smart devices, for example, update their energy use and algorithms in response to wear, preserving balance.

Statement of the law

Law of smart technological energy reintegration:

Every artificial intelligence system evolves when the energy released by the disintegration of its structures is reintegrated proportionally into new material forms, preserving the essential unity between functional information and physical support.

Mathematical representation:

If:

  • E1 / M1 → imbalance/disintegration;

  • E2 = released energy;

  • E2 → M2 under stable proportion (E2 / M2 ≈ constant);

Then:

  • New AI = reintegration of E2 in M2 ⇒ stable and intelligent system

Universal interpretation:

The sustainability of artificial intelligence depends on its ability to reconvert the knowledge released through obsolescence into new structures that maintain energy-matter proportionality.