Recent advances in generative artificial intelligence (AI) technologies have been significantly driven by models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and denoising diffusion probabilistic models (DDPMs). Although architects recognize the potential of generative AI in design, personal barriers often restrict their access to the latest technological developments, thereby causing the application of generative AI in architectural design to lag behind. Therefore, it is essential to comprehend the principles and advancements of generative AI models and analyze their relevance in architecture applications. This paper first provides an overview of generative AI technologies, with a focus on probabilistic diffusion models (DDPMs), 3D generative models, and foundation models, highlighting their recent developments and main application scenarios. Then, the paper explains how the abovementioned models could be utilized in architecture. We subdivide the architectural design process into six steps and review related research projects in each step from 2020 to the present. Lastly, this paper discusses potential future directions for applying generative AI in the architectural design steps. This research can help architects quickly understand the development and latest progress of generative AI and contribute to the further development of intelligent architecture.

翻译：近年来，生成对抗网络（GANs）、变分自编码器（VAEs）以及去噪扩散概率模型（DDPMs）等模型极大地推动了生成式人工智能（AI）技术的发展。尽管建筑师们认识到生成式AI在设计领域的潜力，但个人认知壁垒往往限制了他们接触最新技术进展，从而导致生成式AI在建筑设计中的应用相对滞后。因此，理解生成式AI模型的原理与进展，并分析其在建筑应用中的相关性至关重要。本文首先概述了生成式AI技术，重点介绍了概率扩散模型（DDPMs）、3D生成模型以及基础模型，并强调了它们的最新发展和主要应用场景。随后，本文阐述了上述模型如何在建筑领域中得到应用。我们将建筑设计过程细分为六个步骤，并回顾了从2020年至今每个步骤中的相关研究项目。最后，本文探讨了生成式AI在建筑设计步骤中应用的潜在未来方向。本研究有助于建筑师快速了解生成式AI的发展与最新进展，并为智能建筑的进一步发展做出贡献。