Mathematical Problems of Artificial Intelligence and Fundamental Issues in Constructing Self-Consistent Measures and Their Resolution Through the Universality of the Zeta Function

Artificial Intelligence (AI) faces a range of mathematical challenges, such as optimization, generalization, model interpretability, and phase transitions. These issues significantly limit the application of AI in critical domains such as medicine, autonomous systems, and finance. This article examines the primary mathematical problems of AI and proposes solutions based on the universality of the Riemann zeta function. Furthermore, AI, as a major trend attracting hundreds of billions of dollars, is now tasked with addressing humanity’s most complex challenges, including nuclear fusion, turbulence, the functioning of consciousness, the creation of new materials and medicines, genetic issues, and catastrophes such as earthquakes, volcanoes, tsunamis, as well as climatic and social upheavals, ultimately aiming to elevate civilization to a galactic level. All these problems, both listed and unlisted, are interconnected by the issue of prediction and the problem of “black swans” within existing challenges. This work offers an analysis of AI’s problems and potential pathways to overcome them, which, in our view, will strengthen existing trends established by our great predecessors, which we believe will become foundational in mastering AI.