Modern fabrication tools such as 3D printers can make structural materials in shapes that would have been difficult or impossible using conventional tools. Meanwhile, new generative design systems can take great advantage of this flexibility to create innovative designs for parts of a new building, car, or virtually any other device.

But such “black box” automated systems often fall short of producing designs that are fully optimized for their purpose, such as providing the greatest strength in proportion to weight or minimizing the amount of material needed to support a given load. Fully manual design, on the other hand, is time-consuming and labor-intensive.

Now, researchers at MIT have found a way to achieve some of the best of both of these approaches. They used an automated design system but stopped the process periodically to allow human engineers to evaluate the work in progress and make tweaks or adjustments before letting the computer resume its design process. Introducing a few of these iterations produced results that performed better than those designed by the automated system alone, and the process was completed more quickly compared to the fully manual approach.

Ford’s proposed system would allow your car to lock itself, disable certain features, and even drive itself autonomously to an impound lot.

Waymo, Alphabet Inc.’s multibillion-dollar bet on self-driving cars and trucks, is pulling the human safety drivers out of its robotaxi test fleet in Los Angeles as it works to launch a commercial ride service in the second-biggest U.S. city.

Alphabet Inc.’s multibillion-dollar bet on self-driving cars and trucks isn’t ready to launch any paid rides yet, though the second-biggest U.S. city will be its next commercial market after Phoenix and San Francisco.

Last year, Sony AI and Polyphony Digital, the developers of Gran Turismo, developed a new AI agent that is able to race at a world-class level. At the time, the experiment was described in a paper in Nature, where the researchers showed that this AI was not only capable of driving very fast—something other AI have done in the past—but also learned tactics, strategy, and even racing etiquette.

At the time, GT Sophy—the name of the AI—wasn’t quite ready for prime time. For example, it often passed opponents at the earliest opportunity on a straight, allowing itself to be overtaken in the next braking zone. And unlike human players, GT Sophy would try to overtake players with impending time penalties—humans would just wait for that penalized car to slow to gain the place.