The renormalization group provides insights into complex systems in physics, and its influence extends into artificial intelligence.
Qualitative explanations in this paper highlight the applicability of the renormalization group beyond traditional physics.
It points to the unifying principles underlying renormalization group applications in various scientific disciplines.
Such findings may enable innovative approaches in artificial intelligence, leveraging concepts from physics.
Abstract
We explain qualitatively in this short paper the essence of the renormalization group, showing that these ideas apply not only in physics but also beyond, forming the foundation of artificial intelligence.