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How AI Is Changing How We Build Things

October 22, 2018, 10:30 AM UTC

Designing More Efficiently

SURE, COMPUTER ALGORITHMS ARE TAKING over tech and science and medicine … but the creatives are still safe, right? Not exactly. A new program from software developer Autodesk, recently commercialized from an R&D project called Dreamcatcher (rendering above), can use A.I. techniques to assist human designers as they go about their creative tasks. Already in use by companies including Airbus, Under Armour, and Stanley Black & Decker, the software is an example of the burgeoning field of generative design. A designer inputs requirements, limitations, and other qualities into the program—even the total cost of materials. The software then produces hundreds or even thousands of options. As the human designer winnows the choices, the software susses out preferences and helps iterate even better options. Airplane manufacturer Airbus used the software to redesign an interior partition in the A320 and came up with a design that was 66 pounds, or 45%, lighter than the previous setup. —Aaron Pressman

IIlustration by Andrea Manzati

Melding Humans And Robots

ROBOTS HAVE BEEN ON THE ASSEMBLY LINE doing all kinds of manufacturing for decades. Lately, a new feature is being added to the automated work machines: humans. Dubbed “cobots,” short for collaborative robots, the new setups range from robotic helpers that can hand the correct part to a human worker to an almost Ironman like robotic exoskeleton suit that a person wears to gain added strength and A.I. software guidance. BMW has a cobot nicknamed Miss Charlotte that is helping assemble doors at its Spartanburg, S.C., plant. Mercedes-Benz is turning to cobot technology to help personalize each car that the luxury-automaker assembles in some of its most expensive categories. Replacing larger automated systems, humans with more nimble cobot helpers can be quicker at choosing from among the huge variety of parts needed to customize S-Class sedans, for example. MIT professor Julie Shaw is working on software algorithms developed with machine learning that will teach cobots how and when to communicate by reading signals from the humans around them. Some researchers have even looked at connecting cobots to human brainwave readouts. Mind-reading assistive robots? Now that’s collaboration. —Aaron Pressman


Percentage of people who found chatbots pretending to be human “creepy,” according to Mindshare.

Powering Clean Energy

IF WIND ENERGY IS TO BE decisively cheaper than fossil-fuel power, the process of transforming wind into electricity must get more efficient. Machine-learning technology developed at Siemens is helping. Researchers realized that huge wind turbines could use data on weather and component vibration to fine-tune themselves continually, for example, by adjusting the angles of rotor blades. But “you cannot analytically calculate this,” says researcher Volkmar Sterzing.

That’s the right kind of problem for A.I. and machine learning. Sensors were already generating the needed parameters, but “previously, these were used only for remote maintenance and service diagnostics,” says Sterzing. “Now they are also helping wind turbines generate more electricity.” The technology can even adjust turbines to the unpredictable airflows coming through the turbines in front of them.

Deploying this A.I. broadly is now an opportunity for SiemensGamesa Renewable Energy, an independent company formed last year by combining Siemens’s wind operations with the wind power business of Spain’s Gamesa. —Geoff Colvin

Keeping An Eye On The Mortals

HUMANS ARE NOT GREAT at knowing their own limits—they eat too much, sleep too little, and overestimate what can be achieved in a period of time. That may seem a matter of little consequence when it comes to, say, Thanksgiving dinner, but in certain professions—like long-haul trucking and heavy-equipment operation—such fallibility can be dangerous and catastrophically costly.

That’s why companies are increasingly using A.I., guardian angel–like, to safeguard employees in high-risk jobs. Systems, trained on hundreds of hours of employee sensor data, monitor conditions—like an operator’s heart rate, body temperature, and indicators of fatigue level or nervousness—in real time and signal when that individual needs to rest or take a break, explains Mike Flannagan, an SVP at business software firm SAP. (SAP has a Connected Worker Safety product that does this.)

As for the rest of us? We can expect to see this type of technology soon in our own garages, where automakers are dreaming up ways for our cars to keep an eye on us. While the tech is currently limited to a coffee cup icon that flashes on the dash in a few models, Nils Lenke, head of innovation management for automotive at Nuance Communications, an A.I. firm that works with most of the major carmakers, says fatigue-detecting voice and facial recognition technology will soon be standard in new vehicles. —Erika Fry

CORRECTION: An earlier version of this article misidentified the name of an Autodesk A.I.-enabled design program.

A version of this article appears in the November 1, 2018 issue of Fortune as part of the article, ’25 Ways A.I. Is Changing Business.’