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Honda Puts Its Autonomous Vehicle Tech To Work At Construction Site

Honda and the engineering and construction firm Black & Veatch have tested a prototype of Honda’s autonomous work vehicle at a construction site in New Mexico.

During a month of tests, the AWV performed such tasks as towing, moving construction materials and other supplies to specific locations within the work site.

Honda’s AWV was first shown as a concept at the 2018 Consumer Electronics Show. It combines a durable off-road side-by-side platform with advanced autonomous technology. The vehicle uses a collection of sensors to maneuver without a driver, using GPS, radar and lidar for obstacle detection, as well as 3D cameras. Together, these features enable the AWV to be operated by remote control.

The Boring Co Tunnels Are the Future of Transportation

Photo: The Boring Company.

The Boring Company’s tunnels are the future of transportation and while some people don’t think so, those who have had the opportunity to try them are sure of it. Skeptical, West Coast Editor of Autoweek, Mark Vaughn, went downstairs to figure out for himself what The Boring Co tunnels are all about—and whether they are as important as Elon Musk says.

Vaughn admits that he was a little skeptical before using the tunnel. He suggested that there would be long lines and too few cars, so it would be faster and easier to simply walk from the West Hall of the Las Vegas Convention Center (LVCC) to the far South Hall. However, after the “critic” descended the escalator into the underground tunnels he was a little surprised to find that the wait was only about a minute. Vaughn said he just walked up to the Tesla Model X, greeted the human driver, and immediately after the door closed, they drove away.

Reaction Engines assembles partners for its ammonia aviation project

The UK’s Reaction Engines has announced a joint venture to create compact, lightweight ammonia reactors it says can be used to decarbonize difficult sectors like shipping and off-grid energy generation – and surprisingly, also aviation.

We’ve written before about ammonia’s potential in the clean transport sector; check out our ammonia clean fuel primer piece from September. Compared against hydrogen, ammonia’s much easier and cheaper to store and transport, and although it only carries about 20 percent as much energy as hydrogen by weight, it carries about 70 percent more energy than liquid H2 by volume.

The weight issue generally rules ammonia out of aviation discussions; at less than half the specific energy of jet fuel it looks less attractive than hydrogen. But hydrogen’s volume issues must also be taken into account. Today’s airliners are built for jet fuel so retro-fitting large-volume long-range hydrogen tanks can mean you lose seats. And anyone who’s flown economy can attest, airlines really like fitting in as many seats as they can.

Women in tech are fighting A.I. bias —but where are the men?

Battling bias. If I’ve been a little MIA this week, it was because I spent Monday and Tuesday in Boston for Fortune ’s inaugural Brainstorm A.I. gathering. It was a fun and wonky couple of days diving into artificial intelligence and machine learning, technologies that—for good or ill—seem increasingly likely to shape not just the future of business, but the world at large.

There are a lot of good and hopeful things to be said about A.I. and M.L., but there’s also a very real risk that the technologies will perpetuate biases that already exist, and even introduce new ones. That was the subject of one of the most engrossing discussions of the event by a panel that was—as pointed out by moderator, guest co-chair, and deputy CEO of Smart Eye Rana el Kaliouby—comprised entirely of women.

One of the scariest parts of bias in A.I. is how wide and varied the potential effects can be. Sony Group’s head of A.I. ethics office Alice Xiang gave the example of a self-driving car that’s been trained too narrowly in what it recognizes as a human reason to jam on the breaks. “You need to think about being able to detect pedestrians—and ensure that you can detect all sorts of pedestrians and not just people that are represented dominantly in your training or test set,” said Xiang.