The Sweet Spot of Intelligence: World-Binding, Complexity, and the Limits of AGI

The current debate on artificial intelligence, AGI, and superintelligence is often based on the implicit assumption that intelligence can, in principle, be increased without limit. Larger models, more data, greater computational power, and more comprehensive world models are commonly regarded as steps along an open-ended developmental trajectory. The present paper challenges this assumption. Starting from a theory of world-binding (Weltbindung), it is proposed that intelligence should not primarily be understood as information processing, predictive capability, or computational power, but rather as the ability of a system to irreversibly integrate difference into a coherent and actionable world. On this basis, it is argued that world-formation necessarily depends on Raster formation, selective stabilization, and non-closure, as elaborated in the author's previous work. Every form of world-binding simultaneously generates a Gap between the bound world and the remaining openness. This Gap does not disappear through additional knowledge but is reproduced through every new act of form-formation. From this, the paper develops the thesis of a structural sweet spot of intelligence. Intelligence appears neither as a linear function of complexity nor as an infinitely scalable property. Below a certain capacity for differentiation, sufficient world-binding cannot emerge. Above a certain capacity for differentiation, the ability to integrate growing difference begins to disintegrate. Between these two poles lies a region of maximal world-binding capacity. On this basis, the paper demonstrates why additional complexity, additional models, or additional Raster do not fundamentally solve the problem. Every expansion of world generates new integration requirements and new forms of non-closure. The limit of intelligence therefore appears not as a deficit or failure of its development, but as a condition of its effectiveness. Systems become capable of action not despite their limitations, but through them. Finally, the implications of this perspective for current AGI, world model, and superintelligence concepts are discussed. The paper proposes that the central limit of future intelligence systems may not lie in insufficient computational power, inadequate data, or technical restrictions, but in the ontological conditions of world-formation itself. The decisive question is therefore not how intelligent a system can become, but under what conditions a world remains bindable at all.