Lifeboat Foundation

Researchers from Washington State University and Ohio State University have developed a low-cost, easy way to make custom lenses that could help manufacturers avoid the expensive molds required for optical manufacturing.

Led by Lei Li, assistant professor in the School of Mechanical and Materials Engineering, and graduate student, Mojtaba Falahati, the researchers developed a liquid mold from droplets that they can manipulate with magnets to create lenses in a variety of shapes and sizes. Their work is featured on the cover of the journal, Applied Physics Letters.

High-quality lenses are increasingly used in everything from cameras, to self-driving cars, and virtually all robotics, but the traditional molding and casting processes used in their manufacturing require sophisticated and expensive metal molds. So, manufacturers are mostly limited to mass producing one kind of lens.

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A U.S. venture-capital firm recently led a round of seed investment for Hermeus Corp., a new startup developing a hypersonic aircraft.

In a bid to help those with limited mobility get to the gate, Tokyo Narita International Airport is set to welcome a number of self-driving wheelchairs to its floors. With the ability to navigate the airport all on their own, the new wheelchairs are hoped to streamline foot traffic in one of Japan’s busiest airports and form part of a wider plan to boost mobility options at such facilities.

Where #Uber, Facebook, #Apple, #Microsoft, #Google, And #Amazon Are Investing In longevity and health span.

As Uber and Lyft grow their massive footprints, they are beginning to look towards the healthcare industry. Here’s what they’re doing in healthcare already and what they might do next.

A fleet of driverless cars working together to keep traffic moving smoothly can improve overall traffic flow by at least 35 percent, researchers have shown.

The researchers, from the University of Cambridge, programmed a small fleet of miniature robotic cars to drive on a multi-lane track and observed how the traffic flow changed when one of the cars stopped.

When the cars were not driving cooperatively, any cars behind the stopped car had to stop or slow down and wait for a gap in the traffic, as would typically happen on a real road. A queue quickly formed behind the stopped car and overall traffic flow was slowed.

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A team of scientists from the University of Maryland recently came up with a take on the hyperdimensional computing theory that could give robots memories and reflexes. This could break the stalemate we seem to be at with autonomous vehicles and other real-world robots, and lead to more human-like AI models.

The solution

The Maryland team came up with a theoretical method by which hyperdimensional computing – a hypervector-based alternative to computations based on Booleans and numbers – could replace current deep learning methods for processing sensory information.

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Car Culture

Other automotive name choices include “Ford,” “Bentley,” and “Audi,” as Mashable reports, accounting for thousands of innocent newborns.

Whether the decision will help the car company overcome hurdles like hitting the lowest stock valuation since 2017 or dealing with multiple reports of Teslas randomly catching fire is unknown.

Continue reading “Hundreds of Americans Are Naming Babies ‘Elon’ and ‘Tesla’” »

A.I. is yet to prove the safety of self-driving cars.

“Shortly following the accident, we informed the National Highway Traffic Safety Administration and the National Transportation Safety Board that the vehicle’s logs showed that Autopilot was first engaged by the driver just 10 seconds prior to the accident, and then the driver immediately removed his hands from the wheel,” a Tesla spokesperson told The Register in an emailed statement. “Autopilot had not been used at any other time during that drive. We are deeply saddened by this accident and our thoughts are with everyone affected by this tragedy.”

To navigate dynamic environments, autonomous vehicles (AVs) should be able to process all information available to them and use it to generate effective driving strategies. Researchers at the University of California, Berkeley, have recently proposed a social perception scheme for planning the behavior of autonomous cars, which could help to develop AVs that are better equipped to deal with uncertainty in their surrounding environment.

“My research has focused on how to design human-like driving behaviors for autonomous cars,” Liting Sun, one of the researchers who carried out the study, told TechXplore. “Our goal is to build AVs that do not only understand human behavior, but also perform in a similar way in multiple aspects, including perception, reasoning and action.”

Sun and her colleagues observed that human drivers tend to treat other vehicles as dynamic obstacles, often inferring additional information from their behavior on the road. This information is generally occluded environment information or physically undetectable social information.

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