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Category: transportation – Page 115

Robotaxi company Cruise is “just days away” from getting regulatory approval that would pave the way for mass production of its purpose-built driverless vehicle, CEO Kyle Vogt said on Thursday in comments reported by the Detroit Free Press.

General Motors-backed Cruise unveiled the vehicle — called Origin — in early 2020, presenting the kind of driverless car that we all dreamed of when R&D in the sector kicked off years ago; a vehicle without a steering wheel and without pedals. A vehicle with passenger seats only.

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Removing membranes could shave off as much as 30 percent of battery costs since they are the most expensive components.

Researchers at the University of Cincinnati in the US have developed a new design that could make lithium-ion batteries much cheaper to produce. This can have a profound impact on the large-scale energy storage systems needed to store renewable energy, a press release said.

Lithium-ion batteries, extensively used for power electronic devices, have also found their way into electric vehicles (EVs) thanks to their superior energy density over conventional batteries. These can also be deployed to store renewable energy when production is high, but the demand is low.

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A new facility will be able to produce battery capacity to power 130,000 homes on a daily basis using renewable energy.

Zinc halide batteries touted as a low-cost alternative to battery energy storage system (BESS) have received a significant boost in the US after the Department of Energy (DOE) offered a $400 million loan to help scale production and reduce manufacturing costs, a press release said. The offer will cover setting up of four production lines at battery maker Eos’ facility in Turtle Creek, Pennsylvania.

Lithium-ion batteries are a crucial component of our attempts to switch to a greener economy powered by renewable energy. Although the technology is ubiquitous these days and powers everyday devices like smartphones and even electric vehicles (EVs), it is still very expensive.

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(NewsNation) — A scientific expedition off the coast of Alaska sparked speculation among livestream viewers when cameras on a remote-controlled dive vehicle captured a mysterious object at the bottom of the ocean.

The National Oceanic and Atmospheric Administration conducted the Aug. 30 expedition and described the object as a “golden orb” that “struck an imaginative chord.”

So, what was it?

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Google Deepmind will soon begin researching autonomous language agents such as Auto-GPT, potentially boosting the viable applications of LLMs such as Gemini.

Google DeepMind is looking for researchers and engineers to help build increasingly autonomous language agents, Edward Grefenstette, director of research at Google DeepMind, announced at X.

Such AI agents already exist in early stages, with Auto-GPT being one of the earliest examples. The basic idea is to create a system that autonomously achieves a given goal using a mix of prompt engineering, self-prompting, memory, and other system parts. While such agents are already showing promising results, they are still far from being able to achieve good results on their own and usually require human feedback and decision-making.

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Active particles can form two-dimensional solids that are different from those formed by nonmotile particles, showing long-range crystalline order accompanied by giant spontaneous deformations.

If you compress a liquid slowly enough at low temperatures, it will freeze into an ordered solid: a crystal. Or at least that’s what we’re used to seeing in three dimensions. If you instead consider particles confined to a two-dimensional (2D) plane, the outcome is quite different. For equilibrium systems, a 2D solid stabilizes into a structure that lacks long-range order—it becomes less ordered further away from a central lattice site. The behavior of systems far from equilibrium, such as self-propelled particles, remains, however, an open question. In a numerical study of bacteria-like particles, Xia-qing Shi of Soochow University in China and his colleagues now show that active crystals follow a slightly different set of rules than their nonmotile counterparts [1]. Like 2D equilibrium crystals, 2D active systems stabilize into an ordered solid-like phase but with extremely large particle fluctuations around the configuration of a perfect crystal lattice.

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The German automaker’s next-generation advanced driver assistance system, or ADAS, will feature in its Neue Klasse range of electric cars that the company revealed on Saturday — that will launch in 2025.

It comes as traditional automakers look to boost the technology in their cars, with a particular focus on ADAS, to compete with Tesla.

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Data privacy protections are almost nonexistent when it comes to automobiles.

Mozilla looked at 25 car brands and found that all of them collected too much personal data, and from multiple sources—monitoring not just which buttons you push or what you do in any of the infotainment system’s apps but also data from other sources like satellite… More.

Today, the Mozilla Foundation published its analysis of how well automakers handle the privacy of data collected by their connected cars, and the results will be unlikely to surprise any regular reader of Ars Technica. The researchers were horrified by their findings, stating that “cars are the worst product category we have ever reviewed for privacy.”

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A team of scientists from Ames National Laboratory has developed a new machine learning model for discovering critical-element-free permanent magnet materials. The model predicts the Curie temperature of new material combinations. It is an important first step in using artificial intelligence to predict new permanent magnet materials. This model adds to the team’s recently developed capability for discovering thermodynamically stable rare earth materials. The work is published in Chemistry of Materials.

High performance magnets are essential for technologies such as , , electric vehicles, and magnetic refrigeration. These magnets contain critical materials such as cobalt and rare earth elements like neodymium and dysprosium. These materials are in high demand but have limited availability. This situation is motivating researchers to find ways to design new magnetic materials with reduced critical materials.

Machine learning (ML) is a form of . It is driven by computer algorithms that use data and trial-and-error algorithms to continually improve its predictions. The team used experimental data on Curie temperatures and theoretical modeling to train the ML algorithm. Curie temperature is the maximum temperature at which a material maintains its magnetism.

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