A brief history of computation

We can summarise the history of computation in terms of five eras: the 2D drafting era, the 3D modelling era, the building information modelling (BIM) era; the design computation (algorithmic) era; and more recently, the machine learning era.

 

All tools modify the gestures of their users, and in the design professions this feedback often leaves a visible trace: when these traces become consistent and pervasive across objects, technologies, cultures, people, and places, they coalesce into the style of an age and express the spirit of a time.1

 

Era 1: 2D drafting
The first era of computation mimicked drafting, documenting pen drawings, sketches, and bluebrints. The original Computer Aided Design (CAD) system was Sketchpad, developed by Ivan Sutherland in 1963.2

Ivan Sutherland’s Sketchpad, 1963

It would take a further 20 years to make this technology affordable and accessible to a wider audience with AutoCAD released in 1982 – continuing the practice of representing buildings as multiple 2D drawings.3

 

Era 2: 3D modelling
The second era of computation, also known as the first digital turn, emerged in the 1990s and duplicated model-making. The era was characterised by ‘blob’ architecture, most notably by architects such as Greg Lynn, NOX (Lars Spuybroek), and Frank Gehry.

H2Oexpo, NOX (Lars Spuybroek), 1994

However, by the early 2000s, design professionals started to lambaste the digital blob as the most conspicuous symbol of an age of excess, waste, and technical delusion.4

 

Era 3: Building Information Modelling (BIM)
The third era of computation added physical properties to 3D models. It may be surprising to note that the BIM era started in the 1980s, prior to the 2D drafting era.5 The term ‘building model’ was first used in the mid-1980s: In a 1985 paper by Simon Ruffle,6 and later in a 1986 paper by Robert Aish 7– then at GMW Computers Ltd, developer of RUCAPS (Really Universal Computer Aided Production System) software – referring to the software’s use at London’s Heathrow Airport.8

London’s Heathrow Airport, Terminal 3

The term ‘Building Information Model’ first appeared in a 1992 paper by G.A. van Nederveen and F. P. Tolman.9 However, the terms, including its acronym ‘BIM’, did not become popularly used until some 10 years later when Autodesk released a white paper entitled ‘Building Information Modeling’10 in 2002. Prior to that, different software vendors used differing terminology for what is now accepted as BIM. Graphisoft for example used ‘Virtual Building’, Bentley Systems used ‘Integrated Project Models’, while Autodesk and Vectorworks used ‘Building Information Modeling’.

It is important to note that even with the emergence of 2D CAD, 3D modelling and BIM, the computer didn’t actually aid design, they aided documentation.’11 Dr Robert Aish elaborates on BIM’s limitations 12 13, claiming:

 

  • BIM assumes that buildings are assemblies of components, but that does not necessarily imply that a designer conceives of a building in terms of such assemblies. This ‘component’ assumption forces the designer to think about micro-ideas (the components) before macro-ideas (the building form).
  • BIM models require precise coordinates and dimensions. As a representation, BIM forces the user to be too precise too early in the design process…Effectively BIM confuses precision with certainty.
  • The hard code functionality of the built-in system components is orientated towards conventional construction. This gives a productivity advantage if this approach is accepted, but to circumvent this approach requires additional effort, potentially inhibiting more experimental or unorthodox design exploration.
  • BIM as a representation of the building concept may be too detailed for some forms of analysis, which require simple volumetric description and because of the level of detail the BIM model may be difficult to edit, and therefore inhibit design exploration.
  • BIM is a technology, it is a methodology, but it is not a philosophy of design.

 

Era 4: Design computation (algorithmic)
The design computation era, which began in the late 1980s and early 1990s, saw architects designing not the specific shape of the building, but a set of principles encoded digitally as a sequence of parametric equations. The designer no longer directly modelling the building: instead they develop a graph or script whose executation generates the model.

Two projects completed in the early 1990s heralded the new possibilities of the design computation era: The Vila Olimpica Complex in Barcelona (1992) by Frank Gehry which used CATIA, and the International Terminal at Waterloo Station in London (1993) by Grimshaw which used I/EMS mechanical modelling software.14

International Terminal at Waterloo Station, Grimshaw, 1993

However, it was not until 2003 with the release of Generative Components and later in 2007, with the release of Grasshopper, did design computational really take off.

 

Era 5: Machine learning
The fifth age of computation has begun – not coincidentally alongside the dawn of the fourth industrial revolution. It is the era of machine learning which combines a range of algorithms, pattern recognition, neural networks, generative design, artificial intelligence, and distributed computation to change how we make things.15

1st industrial revolutionC18th & C19th Used water and steam power to mechanise production.
2nd industrial revolution1870 - 1914Used electric power to create mass production.
3rd industrial revolution1980s - Used electronics and information technology to automate production.
4th industrial revolution2010s - Characterised by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres.

 

Whereas previous computation eras used new technology to implement the old science we knew, now, to the contrary, we are learning that computers can work better and faster when we let them follow a different, nonhuman, postscientic method.16 Machine learning follows three main steps: training, analysis and application.

 

Final thoughts
Computation is the only resource that has consistently dropped in price and vaulted in quantity and quality. As computation accelerates, algorithms will become more sophisticated and pack more intelligence into every action. Digital tools will harness more complexity and simplify work into higher-order activities. Computation will increase options but reduce complexity. Designers will need to continually educate themselves and they will need to cultivate a new literacy of thinking in systems.

 

References
1 Carpo, M. (2017). The Second Digital Turn: Design Beyond Intelligence. The MIT Press, Cambridge, p. 55.
2 Sutherland, I. (1963). Sketchpad: A Man-Machine Graphical Communication Systems, AFIPS Conference Proceedings, vol 23, pp. 232-238.
3 Aish, R. (2013). First Build Your Tools. In Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, Peters, B. & Peters, T. (eds). Wiley, Chichester, p. 41.
4 Carpo, M. (2017). The Second Digital Turn: Design Beyond Intelligence. The MIT Press, Cambridge, pp. 4-5.
5 Aish, R. (2013). First Build Your Tools. In Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, Peters, B. & Peters, T. (eds), Wiley, Chichester, p. 43.
6 Ruffle S. (1986). Architectural Design Exposed: From Computer-Aided-Drawing to Computer-Aided-Design. In Environments and Planning B: Planning and Design, March 7, pp. 385-389.
7 Aish, R. (1986). Building Modelling: The Key to Integrated Construction CAD. CIB 5th International Symposium on the Use of Computers for Environmental Engineering related to Building, 7–9 July.
8 Eastman, C. et al. (2008). BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers, and Contractors. John Wiley, New Jersey.
9 Van Nederveen, G. & Tolman, F. (1992). Modelling Multiple Views on Buildings. Automation in Construction. 1 (3). pp. 215–224.
10 Autodesk (2002). Building Information Modeling. Autodesk, Inc., San Rafael. Available: http://www.laiserin.com/features/bim/autodesk_bim.pdf
11 Wujec, T. (2017). The Future of Making. Melcher Media, London, p. 88.
12 Aish, R. UK Dynamo User Group. Available: https://vimeo.com/ukdug
13 Aish, R. (2013). First Build Your Tools. In Inside Smartgeometry: Expanding the Architectural Possibilities of Computational Design, Peters, B. & Peters, T. (eds). Wiley, Chichester, p. 43.
14 Kolarevic, B. (2013). Parametric Evolution. In Inside Smartgeometry: Expanding the Architectural Possibilities of Computational design, Peters, B. & Peters, T. (eds). Wiley, Chichester. pp. 50-59.
15 Wujec, T. (2017). The Future of Making. Melcher Media, London, p. 88.
16 Carpo, M. (2017). The Second Digital Turn: Design Beyond Intelligence. The MIT Press, Cambridge, p. 7.

One Comment on “A brief history of computation

  1. Nice article! I genuinely did not realise that we are already in the “Machine Learning” era already.

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