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Computational design is the merge of design techniques and computational technologies.

Applying computational techniques to the design workflow radically changes how people construct interfaces, services, objects or buildings. Instead of specifying fixed shapes, designers must define the entire processby which an object is created. This generative process is powered by algorithms whilst the output is not performed by humans using a drawing tool but is auto-generated by a set of instructions, variables and parameters.

Computational design is set to dramatically change business, culture, and community throughout the next few years.

John Maeda, author of “How to Speak Machine”, defines three kinds of design:

  • Classical design — activities which pertain to the design of objects we use in the physical world;
  • Design thinking — activities that enable companies to put the user at the center of every design decision and to create innovative products focused on human wants and needs;
  • Computation design — activities involving processors, sensors, memories, actuators, data and networks.

Maeda identifies Computation Design as the most important amongst them, being that destined to have the greatest impact in the future.

Designers who want to work in the computational field have to be confident with machines instructions such as if-then-conditions and loops-cycles. What’s more, they must be focused on the generative process above their ideas. Most of all, they need to collaborate and take advantage of computing power.

Fundamentally, designers are used to working with drawing tools like Sketch, Rhino and 3D Studio to materialise their ideas. Starting from a concept, the software helps them to pass from an abstract conception to a concrete representation. This basic process is adopted in many fields, from interfaces to architecture, with the output coming as the result of a generative process powered by the designer’s mind. Passing to computational design, the generative process becomes powered by machines. Instead of drawing lines and shapes, the designers must define all the computational instructions to achieve the output.


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The Heydar Aliyev Center design by Zaha Hadid © Zaha Hadid

Generative design isn’t a new concept in architecture — there are many tools for 3D modeling and rendering that have been around for some time. When using digital software to create a building, the architect has to define the variables, parameters and constraints so that the computer may generate the output according to the input data. 3D rendering tools help architects visualise the result of the parametric process. Moving further into the generative process, software such as Grasshopper (integrated into Rhino Modelling) helps the architect generate forms using decision nodes and conditions rather than writing lines of code. The results are stunning constructions such as those developed by Zaha Hadid and Norman Foster.

As reported in this Chaos Group article, Zaha Hadid’s Studio workflow consists in a combination of software (such as Maya, Rhino and Grasshopper) that permits a parametric approach in every project. Talking about Grasshopper, Jose Pareja Gomez said:

“Over the past four years, we’ve developed a number of scripts that basically allow us to automate our production a little. For example, I press a button in Grasshopper and Grasshopper creates UVs and clusters meshes together ready for real-time […] We are lazy people and we hate doing the same thing over and over again. So, we invest twice the time to do a script and then don’t worry about it again.”


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Quayola- remains-series © Quayola

Computational design has likewise played a big role in the arts, offering a powerful tool for artists to express themselves.

Universal Everything is a global collective of video artists and experience designers with the aim of developing video artworks and immersive installations. Artists at Universal Everything integrated algorithms into their creative process, resulting in projects that demonstrated the power of merging computer programming and creativity.

In 2019, Barbican opened an exhibition called “AI: More than Human” in which visitors were invited to explore the relationship between themselves and Artificial Intelligence. During the exhibition, Universal Everything created an interactive installation called “Future You”, in which the artwork was able to create a visual response to each visitor, generating more than 40,000 possible variations.

Of the numerous artists pushing the limit of generative technologies to explore creativity, two fascinating examples are Quayola and Gmunk.

Quayola, is a London-based Italian artist who merges software programming, drawing and photography to create audio-visual performances. In exploring old masterpieces, he redefines the shapes, colours and textures by breaking down the boundary between what is real and what is not. In his work Sculpture Factory, Quayola applied advanced robots and artificial intelligence to recreate Renaissance sculptures, with every layer having a complexity that only a computer program could generate.

In a recent interview, Quayola stated:

“What fascinates me are the codes of technology not as a vehicle to reproduce, or represent, a subject but rather as the subject of investigation.”

HOW Art Museum in Shanghai opened a solo exhibition showing several Quayola works, including Strata and iconographies, demonstrating the power of computation and algorithms in defining something that moves an original masterpiece into a new dimension.

Digital products

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Apple Keynote © Apple

Computational design can have the greatest impact in digital products where sensors, actuators, fast processors and cloud computing offer all the ingredients to create stunning advantages also in everyday life.

The iPhone 11 camera integrates Artificial Intelligence into every picture, meaning users can take excellent shots also in low-light environments and with an unstable hand. When the user takes a shot, the camera captures 8 pictures, comparing and combining each one in order to create the best result. The process is called “deep fusion,” which Phil Schiller — Apple’s Senior Vice President of Worldwide Marketing — described as “computational photography mad science”. This process is not a point-and-shoot operation but a combination between processors (A13 Bionic) and machine-learning techniques, a process that can render all other camera manufacturers obsolete.

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