AI is revolutionizing architecture. In fact, according to a survey conducted by Architizer, 46% out of 1,227 designers who were surveyed for a study commissioned by Chaos, a leading developer of rendering and simulation software, have already used AI tools in their projects. And 24% are planning to use them soon. AI in architecture is driven by self-learning, with 60% of respondents reporting that they have no formal AI training.

This article explores current trends, tips and examples of AI used in architecture.

What is AI?

Enscape’s Virtual Reality plugin is powered by NVIDIA Deep Learning Super Sampling, an AI-powered rendering engine whose deep-learning neural network provides ultra-high-resolution ray tracing while improving graphics performance. Photo by Enscape

Artificial intelligence (AI), in a very broad sense, is intelligence displayed by machines. Computer systems are a prime example. According to the MIT Technology Review, “AI is a term that encompasses a collection of technologies that enable computers to perform tasks that would require human intelligence to complete.”

AI is a field of computer science that has been rapidly growing. Its primary focus is the development of software to enable computers and machines to “perceive” and learn their environment so they can perform a certain task or function. Almost all modern AI programs are rooted in machine learning, which enables systems to learn autonomously–without being explicitly programmed to do so–by feeding them large datasets; the more data a system receives, the better it is able to adapt, adjust, and improve itself over time.

AI is in its infancy and constantly changing. As it stands, AI is not without its mistakes, from facial recognition programs that misidentify people to driverless vehicles that cause accidents.

What is AI Architecture?

Chaos’ Enscape, a real-time renderer for architects, uses artificial intelligence to achieve various results. Enscape renders

AEC is one industry that has been experimenting with artificial intelligence software. AI can be applied in many ways to architecture and design.

• Helping engineers, designers, and architects imagine innovative, cost-effective or creative solutions
• Create virtual 3D models and renderings
• New design trends and patterns to explore
• Optimizing materials to reduce cost, improve energy efficiency and so on.
• Calculations (e.g. solar studies, lighting simulations, energy consumption estimates, etc.)
• Analysis of large datasets to gain new insights

AI can be used to help architects and designers communicate more effectively with clients.

Our attention spans are shorter, and being able to showcase projects quickly and give people an overview, you can really share the story so much faster without having to walk people through a potentially dense presentation or show them a series of plans that may be hard for the average person. We have shorter attention spans, and by being able to show projects quickly and giving people an overview, it is possible to share the story much faster without having to go through a dense presentation or show a series of plans that are difficult for the average person, Caoimhe Loftus told gb&d.

Current Trends in AI in Architecture

AI has made a big impact on design and architecture. Here are some trends.

1. The combination of augmented reality (AR), virtual reality (VR) and other technologies will allow digital information to be superimposed on the real world. Designers can see how their designs sync or do not sync with existing environments before construction.

2. Urban planners can also use AI to create entire cityscapes. It can use climate data to predict whether current or future green infrastructures will protect cities against storm surges or what degree of structural integrity is needed to make buildings resilient to climatic challenges.

AI in Architecture Examples

The Beck Group served as the architect and general contractor for RiverSouth. They placed a strong emphasis on human health, comfort, and wellness to improve occupant satisfaction while reducing environmental impact. The office tower is known as the smartest in Austin and uses an AI-powered system from KODE Labs to build automation. Photo by Casey Dunn

Architects, designers and engineers are naturally inclined to experiment. They are, therefore, ideal AI researchers. These are some of the results of their AI discovery in architecture.

AI for Data Analysis & Automation

Nest thermostats use AI to analyze HVAC usage patterns and data to improve energy efficiency. Photo by Nest

Though artificial intelligence is not the most flashy or groundbreaking application of AI today, it has the potential to change the way we analyze data. AI, and machine learning in particular, is capable of processing large amounts of structured, unstructured, and semi-structured data more quickly and accurately than traditional data analyst methods.

The AEC uses AI-driven analytics to monitor and track building performance metrics. These include those collected by BAS or networks that automate certain building functions, such as heating and cooling, lighting, alarms, and so on, through a single control system. The RiverSouth Office Tower in Austin, Texas, for instance, uses smart sensor technology and boasts a BAS powered by AI from KODE Labs.

In a previous article, Natalie Terrill (director of sustainability for The Beck Group, the firm that designed the building) wrote: “The building uses cutting edge sensors connected to its automated system, effectively control air quality, heating ventilation, air-conditioning systems, lighting and security.” The data collected from these systems are analyzed with artificial intelligence in order to maintain and improve the building’s performance and energy efficiency.

KODE Labs Smart Building OS analyzes, standardizes, and normalizes data collected by sensors in real time, allowing managers to schedule and plan operations in real time. The Smart Building OS helps to optimize energy consumption and predict maintenance issues. It also facilitates smart scheduling for building systems.

The same concept applies to Google’s Nest Thermostat. It uses machine learning technology to analyze HVAC usage patterns and make automatic micro-adjustments that help homeowners save money. Gene LaNois is the general manager of Nest’s Professional Channel. He says the Nest Thermostat “always optimizes itself” to meet comfort needs and run the most energy-efficient cycles.

AI Asset Enhancement

The Chaos AI Enhancer was used to enhance this image. The tool enhances assets using artificial intelligence in Enscape to help architects create more detailed visualizations for their clients. Enscape rendering

Visual aids can be valuable tools for effectively communicating ideas with clients. AI can assist in this department by ensuring that architectural visualizations are as realistic, detailed, and true-to-life as possible.

Chaos, for instance, recently integrated AI-driven asset enhancement into its Enscape real-time rendering software. Ina Iontcheva is a Chaos content creator who wrote previously for gb&dPRO. “The Chaos AI Enhancer uses artificial intelligence to enhance the realism in Enscape assets, especially people and vegetation, while not compromising performance.” The AI feature brings projects to life in just one click.

Instead of using a third-party tool, the Chaos AI Enhancer allows users to manage high-quality assets directly from Enscape via the Chaos Cloud. The tool provides superior results because it has a deep understanding of the scene.

AI in Virtual Reality

Andreea Lipan, Chaos, says that Enscape’s VR can be a game changer in the design process. It allows architects, designers and clients to gain a better understanding of the scale, proportion and spatial relationships found within the built environment. Rendering by Chaos

Enscape is a pioneer in integrating AI and virtual reality technology (VR). This new tool will revolutionize how architects communicate concepts and ideas to their clients.

Andreea Lipan is the product marketing manager for Chaos. She previously spoke to me about it. This eliminates the misunderstandings often caused by static or 2D images. Clients can now visualize their projects and actively participate in the design process.

Enscape has been using NVIDIA RTX since 2019. This real-time ray tracing tool enhances speed, accuracy, and overall realism in 3D models and animations. When NVIDIA released their Deep Learning Super Sampling technology (DLSS) in 2021, Enscape 3.1 quickly adopted it. NVIDIA DLSS is an AI-powered rendering technology that uses a complex deep-learning neural network to increase graphics performance and provide ultra-high-resolution ray tracing. Enscape can render at a low resolution but still produce crisp, high-resolution images.

All in all, this means architects and design firms are able to create detailed, aesthetically appealing visualizations that render quickly while still maintaining a high degree of real-time navigation. Enscape’s integration of VR has democratized space perception, a skill that used to require extensive training in geometrical drawing and geometry. “With a VR headset available instantly, anyone can see architectural designs with the same acuity as an architect,” Lipan explains.

AI Text to Image Generator

Text-to-image generators are an ever-evolving AI technology that uses a combination of deep learning models, computer vision, and natural language processing to create detailed images based on text descriptions. This design is an AI-generated text-to-image rendition of Arktura’s existing Arborist cloud ceiling system. Arktura is the source of this image.

Text-to-image models are among the most well-known AI examples. They use deep learning to create detailed images from text descriptions, using computer vision, natural language processing, and generative adversarial network techniques. Text-to-image creators such as DALL-E2, Stable Diffusion, and Midjourney are currently considered among the most advanced.

AI text-to-image generators hold promise for the AEC industry, as they enable designers to create detailed visuals that can be shown to clients quickly. The AI generator can produce multiple designs based on the input of an architect, including the number of rooms and desired layout of a building. The designs can be refined and combined to produce the best solution for the client. Majeda Alhinai is a Solutions Studio Designer at Arktura. She previously wrote about this in gb&d.

Arktura, a leading manufacturer of innovative and sustainable architectural systems, is always evaluating new technologies. Their Solutions Studio design team never replaces them, but they can help them develop custom solutions for any project. Text-to-image technology has been added to the company’s toolkit to help bring the concepts and ideas of clients to life at an early stage in the creative process. These generated images are not the final product but rather a stepping stone for the team. They can then improve on them and ensure that the finished design still has a human touch.

Generative Design – AI

The Generative AI for architecture is based on algorithms that create a variety of design options based upon the user’s input parameters, as well as a large amount of data, including site conditions and building code, to explore every possible option, like structure, materials and production techniques. It can, for instance, recommend a design that excels at a certain level in terms of cost, weight, or load-bearing characteristics. Architects and designers will be able to select the best design that leads to sustainable buildings or energy-efficient structures with maximum structural integrity.

This AI automates repetitive, time-consuming tasks like building simulations and modelling. By identifying the most cost-effective features, generative AI will save you money. Deloitte, for example, predicts that this technology could save up to 15 on construction costs.

A generative AI can also do what designers and architects might do if given infinite time to explore all the options. Gen AI can create thousands of designs within seconds.

Use AI in Architecture

Arktura, a company which has adopted AI as a text-to-image generator, is an example. It is used by the company’s Solutions Studio, not as a software solution but to help clients visualize their ideas and concepts. Designers can then enhance and improve the generated designs. Arktura render

AI is here to remain, and it’s important to learn how to use it. Here are some tips on how to make AI work for you.

Get to know the latest AI tools that are suitable for designers and architects. Some AI text-to-image generators include DALLE, Stable Diffusion, Midjourney, CLIP, and StyleGAN. These are similar, but they’re also unique. Try them all out to see which works best for you.

Experiment with AI tools for a wide range of projects, from conception through to the final product. Send feedback to the tool makers to make future versions easier to use and more functional.

Create or join a professional network. Use AI in architecture to share experiences and troubleshoot advice.

Ask about or coordinate formal AI training with your company for all team members.