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Researchers propose mathematical limit theory for foundation model intelligence

Researchers have developed a mathematical framework to formalize emergent intelligence in foundation models using limit theory. This approach defines intelligence as a performance function dependent on data size, model size, and training steps, positing that intelligence emerges as a transition to effectively infinite knowledge. The study proves that the existence of a parameter-limit architecture is both necessary and sufficient for emergent intelligence, and derives scaling laws based on this theory. AI

影响 Provides a mathematical foundation for understanding emergent intelligence and scaling laws in large AI models.

排序理由 This is a theoretical computer science paper published on arXiv.

在 arXiv cs.LG 阅读 →

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Researchers propose mathematical limit theory for foundation model intelligence

报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jun Shu, Junxiong Jia, Deyu Meng, Zongben Xu ·

    A Limit Theory of Foundation Models: A Mathematical Approach to Understanding Emergent Intelligence and Scaling Laws

    arXiv:2604.24037v1 Announce Type: new Abstract: Emergent intelligence have played a major role in the modern AI development. While existing studies primarily rely on empirical observations to characterize this phenomenon, a rigorous theoretical framework remains underexplored. Th…