Technology
Computational Design: The Future of How We Make Things is Tech-Driven
Future Design is Computational
Design is always changing, and never stagnant.
In the late 20th century, it was the emergence of Design Thinking that upended how architects, engineers, and industrial design organizations made decisions about how to make new things.
Now, the rapid pace of technological advancement has brought forth a new design methodology that will again forever alter the course of design history. Computational design, which takes advantage of mass computing power, machine learning, and large amounts of data, is changing the fundamental role of humans in the design process.
Designing With Billions of Data Points
Today’s infographic comes to us from Schneider Electric, and it looks at how the future of design will be driven by data and processing power.
While computational design is still a term with no real consensus, attempts to define it do have overlap:
Parameter setting
Algorithmic, “rules-based” code can be applied as constraints to test a wide variety of computer-driven designs
3d modelling and visualization tools
Complex 3d models can allow designers to test and create simulations for new ideas
Processing power
Using vast amounts of computational power and automation to make designs not before possible
Designing with data
Applying big data and powerful algorithms to create new designs
Generative design
By creating, testing, and analyzing thousands of design permutations, this approach mimics mother nature’s evolutionary path to design
While designers traditionally rely on intuition and experience to solve design problems, computational design is a new design methodology that can literally produce hundreds or thousands of design permutations to find the absolute best solution to a problem.
The Shifting Roles of Humans and Computers
Throughout history, humans have shaped the world with design.
But now that artificial intelligence is superior in taking on specific roles within the design process, humans will move towards shaping the things that shape the world.
Designers will be relinquishing control to technology, so that humans can do what they do best.
In other words, in the future, designers will work less on designing – and instead will supervise, mentor, and set the parameters for computational designs. Human designers would also interact with a broader group of stakeholders as additional inputs and the frequency of interactions increase.
A New Design Landscape
Disruption to traditional design methods brings more questions than answers:
- How will this change the value chain for design companies and professionals?
- Will AI-enabled computational design tools take the “craft” out of design?
- If automated design “assets” become commercial commodities, will that create new product and revenue channels for businesses?
- Who will own and manage all of this data, and does this create new roles and opportunities for companies?
As we give machines more design autonomy, it will be interesting to see how this literally changes the shape and design of objects that make up the real world.
Technology
Visualizing AI Patents by Country
See which countries have been granted the most AI patents each year, from 2012 to 2022.
Visualizing AI Patents by Country
This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.
This infographic shows the number of AI-related patents granted each year from 2010 to 2022 (latest data available). These figures come from the Center for Security and Emerging Technology (CSET), accessed via Stanford University’s 2024 AI Index Report.
From this data, we can see that China first overtook the U.S. in 2013. Since then, the country has seen enormous growth in the number of AI patents granted each year.
Year | China | EU and UK | U.S. | RoW | Global Total |
---|---|---|---|---|---|
2010 | 307 | 137 | 984 | 571 | 1,999 |
2011 | 516 | 129 | 980 | 581 | 2,206 |
2012 | 926 | 112 | 950 | 660 | 2,648 |
2013 | 1,035 | 91 | 970 | 627 | 2,723 |
2014 | 1,278 | 97 | 1,078 | 667 | 3,120 |
2015 | 1,721 | 110 | 1,135 | 539 | 3,505 |
2016 | 1,621 | 128 | 1,298 | 714 | 3,761 |
2017 | 2,428 | 144 | 1,489 | 1,075 | 5,136 |
2018 | 4,741 | 155 | 1,674 | 1,574 | 8,144 |
2019 | 9,530 | 322 | 3,211 | 2,720 | 15,783 |
2020 | 13,071 | 406 | 5,441 | 4,455 | 23,373 |
2021 | 21,907 | 623 | 8,219 | 7,519 | 38,268 |
2022 | 35,315 | 1,173 | 12,077 | 13,699 | 62,264 |
In 2022, China was granted more patents than every other country combined.
While this suggests that the country is very active in researching the field of artificial intelligence, it doesn’t necessarily mean that China is the farthest in terms of capability.
Key Facts About AI Patents
According to CSET, AI patents relate to mathematical relationships and algorithms, which are considered abstract ideas under patent law. They can also have different meaning, depending on where they are filed.
In the U.S., AI patenting is concentrated amongst large companies including IBM, Microsoft, and Google. On the other hand, AI patenting in China is more distributed across government organizations, universities, and tech firms (e.g. Tencent).
In terms of focus area, China’s patents are typically related to computer vision, a field of AI that enables computers and systems to interpret visual data and inputs. Meanwhile America’s efforts are more evenly distributed across research fields.
Learn More About AI From Visual Capitalist
If you want to see more data visualizations on artificial intelligence, check out this graphic that shows which job departments will be impacted by AI the most.
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