ARTIFICIAL INTELLIGENCE AND DEEP LEARNING ALGORITHMS: A POST-SMART PATH FOR CITIES

The Artificial intelligence (AI) and deep learning algorithms have had a significant impact in overcoming the concept of a smart city, as evidenced by the latest scientific research. That trajectory is shifting from smart ontology to deep learning algorithms. The work integrates theoretical and practical knowledge of AI cohabitation with the city and how it changes it, but also a reversible process. AI recomposition is also considered, drawing on a number of urban disciplines and case studies. Through a comparative analysis of a series of case studies in cities where different methods of mutual constitutive relations have been applied, a synthesis of conclusions and a series of criteria and recommendations is reached. The chosen methodology is based on the thesis that every local context is unique, and AI system must be developed in a way that is adapted and corresponds to the specific local context. The research reveals the various impacts of AI on society, education, infrastructure, urban planning and sustainable development. The so-called new postsmart path for cities is confirmed through empirical examples and represents a new era and paradigm of future urban life. The urbanism of artificial intelligence was analyzed and the results may be useful in some future research due to the very interdisciplinary nature of the topic both in the fields of urban studies and architecture, as well as from the point of view of studies of scientific and technological development, education, sociology, culture and politics