AI and machine learning in architecture
Artificial intelligence and machine learning in architecture
Over the last few decades, computation has given architecture an edge advantage over the understanding of the structure, solve complexities with ease, and better utilization of resources. The evolution of the application of computer or computational design in architecture is divided into era’s which are: 1st era is of 2D Drafting, 2nd era of 3D Modelling, 3rd era of BIM, 4th era of Algorithm-based design, and finally, the 5th era of Machine Learning (ML) and Artificial Intelligence (AI).
Before understanding the impact of ML and AI, it’s important to understand the evolution of the application of computation in simpler terms. 2D Drafting (software like AutoCAD, Sketchpad, etc) comprises of drawing of lines with help of computation, then in 3D Modelling (software like Blender, Maya, etc) the surface, volumes, NURBS, meshes came into play.
When it came to BIM (it’s a workflow, but the most prominent software that helps in BIM are Revit, Tekla, ArchiCAD, etc), an object can store data which can be used productively, for example, a roof when made, the data like its area, volume, physical properties, materials, texture, etc are stored within it, with can be used in BOQ, structural analysis, etc. Algorithm-based design (software like Grasshopper 3D, Dynamo, etc) came to play after the popularization of works of Zaha Hadid and the parametricism movement.
In algorithm-based design, a design is made with some input parameters and let the computer give design output as per the direction coded by the designer. And finally, the era of ML whose concept exits from the late 90s, but the application of it is happening now. Software like Lunchbox, Finch 3D, Sketch Graphs, etc is being developed based on ML.
Machine Learning (ML), which is also known as Statistical learning, is a type of Artificial Intelligence that utilizes a set of data to predict the result with a certain percentage of accuracy. It requires a training data set (larger the data set, more accurate is the result), based on which ML gives the output. Several mathematical models like Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Bayesian networks, Radial Basis Function networks (RBFs), etc are used under ML to achieve different types of results.
So, here is the list of activities with the mathematical models that will generate output.
- Generating Design Concept from the client’s demand
When the architect is using ML to generate concepts, ML also enables the user to get recommendations in the process of design. ML will help the architect to clarify his design intents and recommend choosing truss types, floor plan layouts, and façade treatment.
- Mass customization and urban planning
- Program synthesis
- Analytical Modelling
- 3D Modelling, Production, and Labelling
- Finding hidden correlations
The application of ML and AI is all around us, and its application in the field of architecture is vast. Objectives like the development of an adaptive façade control system, the creation of desired materials, and the development of more smart systems can be achieved with ML. Introduction to ML in architecture will not let the creativity of the architect down but would allow the architect to explore possibilities and find the best, faster simulations, automatic organization of files, and much more, its just a matter of time after which we just need to ask the correct question, to get the best of ML.
With all technology, there come drawbacks. The major drawback of the application of ML in architecture is the training set of ML systems needs to be continuously updated, else it will generate a similar result. Unfortunately, we don’t have any large training set available in architecture. An unbalanced dataset might make ML biased towards particular decisions and research on minimizing the biased character from unbalanced data set is going on. There are several abnormalities related to ML which are being solved, without which application of it in architecture can be disastrous.
The paper “The role of Artificial Intelligence in architectural design: a conversation with designers and researchers” by Giuseppe Gallo, Giovanni Francesco Tuzzolino, and Fulvio Wirz comprises of interviewing the leaders of the architecture industry and trying to figure out the impact of AI in architecture. It’s quite interesting to see that out of 10 interviewed leaders, 4 industry leaders have put Machine Learning, Other computational methods, and Digital Manufacturing in their first place of choice while ordering the technologies that will prove their usefulness in the field of architecture in the next 10 years. The other options that are put in front of them are Building Information Modelling (BIM), Internet of Things (IoT), Augmented Reality (AR), and Virtual Reality (VR). So, it’s quite clear that the amount of impact of ML and AI that the field of architecture will have in the next 10 years has a very high probability.
There are lots of architecture tools that use ML and AI technology to some extent and have become a part of our daily life. Like Google Maps, E-mail filters of Google, Linked In, Google Search Algorithm, etc. In architecture, some of the software that uses ML and AI is Unity 3D (which uses AI to find the shortest distance of fire exits), Lunchbox (it uses general ML for regression analysis, clustering, and networks), Opossum (uses ML for functional evaluations, near-optimal solutions, and simulations), Project Dreamcatcher by Autodesk, etc.
Being surrounded by technology, and predicting the possibilities of the future. The question of “What’s next?” remains the same all through the ages and that’s where AI and humans have the gap.