NEURAL NETWORKS IN ARCHITECTURE: FROM IDEA TO IMPLEMENTATION

Abstract

Problem Statement. In the modern design process, advanced technologies are increasingly being utilized to create complex and innovative architectural projects. Neural networks play a crucial role in the development of automated image generation methods in the architectural field, considering various styles, forms, and textures. However, despite the rapid advancement of these technologies, there are significant issues hindering their full integration into architectural practice. Generating beautiful concept images using neural networks remains far from realization. These images may be inspirational but do not address technical aspects such as developing 3D models, preparing drawings, and performing calculations necessary for the successful implementation of projects. Striking a balance between aesthetics and functionality is a key factor for the successful realization of construction projects. The aim of the article is to examine the issues related to image concept generation in architecture using MidJourney and similar platforms. The primary focus is on analyzing why generating concept images is only the initial step in architectural design. Additional stages are required, such as developing 3D models, preparing drawings, and performing calculations. This will transform the ideas presented in images into tangible three-dimensional objects, considering technical aspects and engineering systems.