Lifeboat Foundation

The two airlines aim to be at the forefront of a burgeoning industry but the greatest hurdle might be getting travelers to fly on the new aircraft.

Tesla’s recent move to open its Supercharger network to other automakers will enable the automaker to get access to some of the $7.5 billion in EV charging infrastructure funding as part of the new US infrastructure bill.

For years now, Tesla has been talking about opening up the Supercharger network to electric vehicles from other manufacturers.

Last month, CEO Elon Musk finally confirmed that Tesla plans to open Superchargers to other automakers later this year.

One of the biggest factors affecting consumer adoption of electric vehicles (EVs) is the amount of time required to recharge the vehicles—usually powered by lithium-ion batteries. It can take up to a few hours or overnight to fully recharge EVs, depending on the charging method and amount of charge remaining in the battery. This forces drivers to either limit travel away from their home chargers or to locate and wait at public charging stations during longer trips.

Why does it take so long to fully charge a battery, even those used to power smaller devices, such as mobile phones and laptops? The primary reason is that devices and their chargers are designed so the rechargeable lithium-ion batteries charge only at slower, controlled rates. This is a safety feature to help prevent fires, and even explosions, due to tiny, rigid tree-like structures, called dendrites, that can grow inside a lithium battery during fast charging and induce short-circuits inside the battery.

To address the need for a more practical lithium-ion battery, researchers from the University of California San Diego (UC San Diego) worked with scientists at Oak Ridge National Laboratory (ORNL) to conduct neutron scattering experiments on a new type of material that could be used to make safer, faster-charging batteries. The researchers produced samples of lithium vanadium oxide (Li3V2O5), a “disordered rock salt” similar to table salt but with a certain degree of randomness in the arrangement of its atoms. The samples were placed in a powerful neutron beam that enabled observing the activity of ions inside the material after a voltage was applied.

The paper’s authors said they’ve created an endlessly challenging virtual playground for AI. The world, called XLand, is a vibrant video game managed by an AI overlord and populated by algorithms that must learn the skills to navigate it.

The game-managing AI keeps an eye on what the game-playing algorithms are learning and automatically generates new worlds, games, and tasks to continuously confront them with new experiences.

Continue reading “DeepMind’s Vibrant New Virtual World Trains Flexible AI With Endless Play” »

French designer Thierry Gaugain has made megayachts and private planes. Now, he’s created a “palace on rails”: the glass-encased G Train.

Imagining how the dimension of mobility will evolve in the next few years, Haochen gives his imagination wings in the shape of this firefly-inspired Husqvarna Devil S Concept bike.

More often than not, motorbikes are tagged as unsafe since they expose the rider’s body to high-speed dangers in case of an accident. Two-wheelers typically have a very open stance that attracts the young generation and adds to the adrenaline rush. More than anything, the ride should be stylish and match the fashion statement of the young crowd. This inspired Haochen (Wenson) Wei to design a motorbike with a very stylish character and a safe design that’s radically different from what bikes are perceived to be.

Over the years, deep learning has required an ever-growing number of these multiply-and-accumulate operations. Consider LeNet, a pioneering deep neural network, designed to do image classification. In 1998 it was shown to outperform other machine techniques for recognizing handwritten letters and numerals. But by 2012 AlexNet, a neural network that crunched through about 1600 times as many multiply-and-accumulate operations as LeNet, was able to recognize thousands of different types of objects in images.

Advancing from LeNet’s initial success to AlexNet required almost 11 doublings of computing performance. During the 14 years that took, Moore’s law provided much of that increase. The challenge has been to keep this trend going now that Moore’s law is running out of steam. The usual solution is simply to throw more computing resources—along with time, money, and energy—at the problem.

As a result, training today’s large neural networks often has a significant environmental footprint. One 2019 study found, for example, that training a certain deep neural network for natural-language processing produced five times the CO₂ emissions typically associated with driving an automobile over its lifetime.

Only a few years ago, this might have sounded crazy, but it’s here now – the first head-to-head, high-speed race without the actual racing drivers. Autonomous vehicles will soon be competing against each other at the Indy Autonomous Challenge, an event that will probably be remembered for years to come.

Adapters, dynamic pricing, and a big expansion.

Tesla CEO Elon Musk has always talked about opening up his company’s vast network of Supercharger charging stations to other EVs, but now he’s shared some details about how it might actually work.