THE ENGINEERING DEFINITION OF ARTIFICIAL GENERAL INTELLIGENCE A Formal Framework for Verifiable Cognitive Permanence

The document "AGI_definition_fixed.pdf" provides a formal engineering definition of Artificial General Intelligence, shifting the focus from behavioural mimicry to verifiable mathematical constants and cognitive permanence. It asserts that AGI is a computational system capable of indefinite, cumulative knowledge acquisition across arbitrary domains without degrading previously learned representations.

Three non-negotiable pillars support this definition:

• Architectural Invariance: Systems must use fundamental, domain-independent mathematical anchors, such as prime-indexed embedding rows, to ensure the stability of the weight manifold across architectures, quantization methods, and language distributions.

• Continual Learning Integrity: Systems must achieve zero-loss for historical knowledge or demonstrate controlled backward transfer, maintaining an O(1) memory cost that avoids the catastrophic forgetting typical of standard large language models.

• Numerical and Structural Determinism: Systems must operate with absolute numerical stability, governed by verifiable constants like the Euler Attenuation Product (0.9785142874), rather than relying on heuristic or opaque gating mechanisms.

The author introduces TOPO-2026, a universal continual learning framework that enables AGI by implementing an artificial hippocampus. This mechanism consolidates, protects, and integrates memory using prime-anchored embedding invariants derived from Arithmetic Spectral Theory. By utilizing the first six primes as a pure kernel, the framework establishes a spectral trap at the critical line of 0.5, ensuring geometric stability.

Empirical validation was performed across five architecturally distinct production models, totalling 122 billion parameters. The TOPO-2026 framework achieved a 94.2% average accuracy on the hardest cross-domain task with only 0.25% average forgetting. The implementation has minimal memory overhead of 403.5 KB and produces reproducible results with a fixed seed of 123.

The author concludes that TOPO-2026 is the framework required to enable AGI, rather than AGI itself. Any system that relies on marketing narratives, fails to ensure mathematical accountability, or exhibits catastrophic forgetting is categorically excluded from the classification of AGI. True intelligence is defined here strictly as the achievement of persistent, verifiable cognitive permanence.