If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Automation has slowly been creeping into the industry for many years now. The shift to machine work first began with the industrial revolution, where 70% of all American workers made their livings on farms. When the industrial revolution swept through the food and manufacturing industries, robots replaced all but 1% of those workers. The trend continues, but never have we seen a technological revolution such as the one that faces the world right now.
A driverless car running on roads may sound like a screen taken from a sci-fi movie. However, fiction is turning into reality, and we thank Artificial Intelligence (AI) for the same. AI technology complements the very concept of self-driving cars. Elon Musk had predicted in 2017 that all the cars will be autonomous in 10 years without any steering wheel. We are quite close to bringing this prediction into reality in just a short time frame of 4 years.
No matter whether you have adopted machine learning technologies and in the grander picture, artificial intelligence, most engineers recognize that a change is coming. It would seem a natural fit to incorporate artificial intelligence into CAD, into our workflows, into our engineering. This not only facilitates our forward growth as engineers, but it gives us the ability to design with complexities never before possible. Remaining at the top of our engineering game is no easy task when the game is constantly innovating with new technologies. To remain relevant as engineers, we must understand – even predict – how machine learning and AI will change the game and adapt before we are left in the dust. AI is the next platform.
Most product-development tasks are complex optimization problems. Design teams approach them iteratively, refining an initial best guess through rounds of engineering analysis, interpretation, and refinement. But each such iteration takes time and money, and teams may achieve only a handful of iterations within the development timeline. Because teams rarely have the opportunity to explore alternative solutions that depart significantly from their base-case assumptions, too often the final design is suboptimal. Today's technology offers an alternative.
Transformative technology can be powerful not just in its own right, but where different technologies converge. Artificial intelligence, in particular, can be a technology supercharger. The second Insight in our series looking at the digital future (and adapted from an article written for the 2019 Bristol Technology Showcase) considers the transformative power of machine learning. Artificial intelligence, in the form of machine learning or deep learning, relies on finding and mapping the patterns in data and then using more and more data to refine and deepen the accuracy of that model, without the need for human-generated linear hand-coding. Part of the reason why this has become such a powerful tool is the speed and availability of almost limitless computing power, thanks to Moore's law and the development of the cloud, respectively.
It's date night and you are at a lovely restaurant sitting across from your date enjoying idle chit-chat. "Ask me anything, anything at all! I have the answer to all questions!" "Okay…well, how long is the longest cave in the world?" "Mammoth Cave National Park is an American national park in central Kentucky, encompassing portions of Mammoth Cave, the longest cave system known in the world. You glaze over as she drones off fact after fact about this cave for quite some time. "…which is nearly twice as long as the second-longest cave system, Mexico's Sac Actun underwater cave."
The way products are designed and engineered is changing thanks to new technologies. These technologies, from digital twins to 3D printing, not only support humans in their design and engineering work, but they can also efficiently uncover new ways of solving problems that humans hadn't thought of before. The human professionals in design and engineering roles in organizations will see changes to their job duties, will be challenged to acquire new skills and flexibility, and learn new ways of collaborating with machines. They also need to learn how to work with new design, engineering, and product development tools enabled by these new technologies. Organizations and professionals in engineering and design roles can't ignore the changes if they want to remain competitive.
Automating the design of urban environments via digital twinning software, moving from sustainable to circular economies and integrating micro-mobility or Mobility 2.0 into the transport mix are among the "strategy shifts" cities need to make, according to ABI Research. The analyst company also warns that a shift from "safe and secure cities" to "resilient cities" and a rethinking of the urban environment through smart spaces will be required. In its new whitepaper, 5 Ways Smart Cities Are Getting Smarter, ABI Research highlights that while smart city tech investments will reach over $61 billion globally in 2026, most of the expenditure will be for incremental improvements. "It is an illusion to believe that adding just a shallow layer of IoT (Internet of Things) technology to legacy urban environments will allow cities to address the urban challenges of the future, ranging from the provision of sustainable energy to the adoption of smart mobility and the construction of resilient cities," says Dominique Bonte, vice president at ABI Research. As they prepare to face new threats such as cyber-attacks and climate change, Bonte said this "new reality" requires new approaches, leveraging a range of new technologies to create true strategy shifts.
New technologies and approaches spur five key smart cities strategy shifts. It's time for smart cities to embrace new technologies and approaches to combat a growing list of challenges, states global tech market advisory firm, ABI Research. Cities have faced challenges like congestion, pollution, and safety for decades, and most have a plan to combat them. While they continue to face these traditional issues, new threats such as cyberattacks, climate change, and other emerging problems are mounting. "This new reality requires new approaches, leveraging a range of new technologies to create true strategy shifts," says Dominique Bonte, Vice President at ABI Research.
The field of construction is well placed to benefit from the advent of machine learning and artificial intelligence (AI). As part of the BIM 360 Project IQ Team at Autodesk, I've had the privilege to participate in Autodesk's foray into machine learning for construction. This article summarizes developments in this space, and covers some ways in which one can prepare to maximize value from this technology, including a broad survey of some of the applications of AI and machine learning in construction, and the potential impact. These processes are making changes across various areas, including risk management, schedule management, subcontractor management, construction site environment monitoring, and safety, to name a few. The public perception of artificial intelligence usually ranges between the two extremes of having it rule the world to it being dismissed as fantasy with no place in a serious conversation.