The devastating fire that just recently ravaged Paris’s Notre Dame cathedral is a painful reminder that national treasures are vulnerable to not only aging, but also natural and man-made disasters. A plan for rebuilding the cathedral is already in the works, and many wealthy donors have pledged their financial support. But when it comes to executing the plan, building architects will be relying on advanced technologies to ensure the historical accuracy and quality of the project.

Laser digitization is one such technology that may soon be used to help design and rebuild the cathedral. In fact, it was reported in Fortune that a few years ago, American art historian and professor Andrew Tallon used cutting-edge laser scanners to capture over a billion points of data that, when combined in suitable software, can be used to create a 3-D model of the cathedral. Statistical computing capabilities, including those championed by artificial intelligence (AI), machine learning and data science, are already helping to transform the work that architects do, from developing advanced modeling techniques to building virtual reality scenarios that architects can use to streamline their creative design and testing processes.

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AI Takes Center Stage in Fields Like Architectural Design

Simply put, AI technologies enable computers to mimic human intelligence, using logic, if-then rules, decision trees, and other functions to make analytical decisions fast. AI has been identified as a highly disruptive technology, with 30 percent of respondents in a recent survey predicting that AI will be the biggest disruptor to their industry in the next five years. And corporate investment in AI is predicted to become a $100 billion market by 2025. In the case of architectural design and planning, AI has a bright future in helping streamline the technological number crunching for architects. AI can help manage massive amounts of data and virtual images, assist in the research and planning phase, and implement project and design testing scenarios faster than individuals can perform. That leaves architects with far more time to focus on the more valuable creative aspects of their profession.

The AI Skills That Make Advanced Techniques Work

With its vast computing potential, AI is increasingly being used to supercharge other advanced technologies. Not surprisingly, AI engineers are at the heart of creating practical applications to improve processes like computer-aided design (CAD) systems that architects use. AI engineers are trained in using a wide range of intelligent agents, including knowledge-base systems, probabilistic models, agent decision-making functions, neural networks, and multi-layer data abstraction to analyze and deploy data in vast volumes and lightning-fast speeds. Job opportunities for AI experts are charging forward, but for people who are concerned with a deterioration of jobs replaced AI, Gartner predicts net positive job growth for AI by 2020, with 2.3 million jobs created by AI vs. 1.8 million jobs eliminated. AI improves the productivity of many skilled jobs and creates millions of new positions in highly-skilled, management positions like the types employed in architectural design.

Meanwhile, the share of jobs requiring AI skillsets has grown 4.5x since 2013, and year-over-year growth in the volume of AI-related job postings, as a share of all job postings, measured 31.6 percent last year compared to just 20.1 percent the year before.

Putting Data to Work at Scale

The fields of big data and data science are the ultimate winners as AI and machine learning technologies change the way companies and professionals utilize data at a scale. In fact, machine learning and AI are fast becoming synonymous with data science and analytics. According to Indeed, the terms “AI” and “machine learning” were included in the job descriptions for about 75 percent of data scientist jobs. Data scientists are able to use AI models to uncover patterns in data that are directly applied to operations to derive business benefits.

In the case of advanced architectural design, that means that architects can work with data scientists to empower what’s known as “parametric design,” or designing a system that allows you to test various scenarios to create different outputs and develop forms and structures that would have otherwise been impossible. Parametric design lets architects plan a design output, set constraints and parameters, apply the necessary data and iterate multiple designs quickly. Data Science Courses are designed to teach important technology tools that help analyze data in these ways. Data scientists leverage platforms such as R, SAS, Hadoop, Python and Spark to implement data science concepts such as data exploration, visualization hypothesis testing and predictive analytics.

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As painful as the Notre Dame tragedy was to watch, it may help to note that technology advancements like laser digitization, AI and data science will enable French authorities and architects to piece this national treasure – and many others down the road – back together. And with the world watching, it may happen much sooner than later.

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