Civitai--an online marketplace for buying and selling AI-generated content, backed by the venture capital firm Andreessen Horowitz--is letting users buy custom instruction files for generating celebrity deepfakes. Some of these files were specifically designed to make pornographic images banned by the site, a new analysis has found. The study, from researchers at Stanford and Indiana University, looked at people's requests for content on the site, called "bounties." The researchers found that between mid-2023 and the end of 2024, most bounties asked for animated content--but a significant portion were for deepfakes of real people, and 90% of these deepfake requests targeted women. Demand for electric vehicles and the batteries that power them has never been hotter. In 2025, EVs made up over a quarter of new vehicle sales globally, up from less than 5% in 2020.

The Download: China's dying EV batteries, and why AI doomers are doubling down China figured out how to sell EVs. Now it has to bury their batteries. In the past decade, China has seen an EV boom, thanks in part to government support. Buying an electric car has gone from a novel decision to a routine one; by late 2025, nearly 60% of new cars sold were electric or plug-in hybrids. But as the batteries in China's first wave of EVs reach the end of their useful life, early owners are starting to retire their cars, and the country is now under pressure to figure out what to do with those aging components. The issue is putting strain on China's still-developing battery recycling industry and has given rise to a gray market that often cuts corners on safety and environmental standards.

In a circular economy, products in their end-of-life phase should be either remanufactured or recycled. Both of these processes are crucial for sustainability and environmental conservation. However, manufacturers frequently do not support these processes enough in terms of not sharing relevant data about the products nor their (re-)manufacturing processes. This paper proposes to accompany each product with a digital twin technology, specifically the Product Digital Twin (PDT), which can carry information for facilitating and optimizing production and remanufacturing processes. This paper introduces a knowledge representation called Bi-Flow Product-Process-Resource Asset Network (Bi-PAN). Bi-PAN extends a well-proven Product-Process-Resource Asset Network (PAN) paradigm by integrating both assembly and disassembly workflows into a single information model. Such networks enable capturing relevant relationships across products, production resources, manufacturing processes, and specific production operations that have to be done in the manufacturing phase of a product. The proposed approach is demonstrated in a use-case of disassembling electric vehicle (EV) batteries. By utilizing PDTs with Bi-PAN knowledge models, challenges associated with disassembling of EV batteries can be solved flexibly and efficiently for various battery types, enhancing the sustainability of the EV battery life-cycle management.

Abstract--Current products, especially in the automotive sector, pose complex technical systems having a multi-disciplinary mechatronic nature. Industrial standards supporting system engineering and production typically (i) address the production phase only, but do not cover the complete product life cycle, and (ii) focus on production processes and resources rather than the products themselves. The presented approach is motivated by incorporating the impacts of the end-of-life phase of the product life cycle into the engineering phase. This paper proposes a modeling approach coming up from the Product-Process-Resource (PPR) modeling paradigm. It combines requirements on (i) respecting the product structure as a basis for the model, and (ii) incorporates repairing, remanufacturing, or upcycling within cyber-physical production systems. The proposed model called PoPAN should accompany the product during the entire life cycle as a digital shadow encapsulated within the Asset Administration Shell of a product. T o facilitate the adoption of the proposed paradigm, the paper also proposes serialization of the model in the AutomationML data format. The model is demonstrated on a use-case for disassembling electric vehicle batteries to support their remanufacturing for stationary battery applications.

Tech expert Kurt Knutsson talks about the Genesis GV60 MIV, an electric rescue EV with snow tracks for extreme missions. Pulling into a station, swapping your electric car battery and getting back on the road in under two minutes is now a reality. In China, CATL's swappable EV batteries are making this possible. This innovation is transforming the way drivers think about electric vehicle charging by making it fast, easy and as convenient as refueling with gasoline. Sign up for my FREE CyberGuy Report Get my best tech tips, urgent security alerts and exclusive deals delivered straight to your inbox.

Hussain Sajwani, owner of DAMAC Properties, said his company will invest 20 billion to build data centers across the U.S. in a press conference hosted by President-elect Trump at Mar-a-Lago on Jan. 7, 2025. Artificial intelligence is expanding quickly, and so is the energy required to run it. Modern AI data centers use much more electricity than traditional cloud servers. In many cases, the existing power grid cannot keep up. One innovative solution is gaining traction: repurposed EV batteries for AI data centers.

In working with customers, we often hear of a desired Digital Twin use case to drive actionable insights through what-if scenario analysis. These use cases typically include operations efficiency management, fleet management, failure predictions, and maintenance planning, to name a few. To help customers navigate this space, we developed a concise definition and four-level Digital Twin leveling index consistent with our customers' applications. In a prior blog, we described the four-level index (shown in the figure below) to help customers understand their use cases and the technologies required to achieve their desired business value. In this blog, we will illustrate how the L4 Living Digital Twins can be used to model the behavior of a physical system whose inherent behavior evolves over time.

Usually, the life of the battery is the life of an EV because it is the most important and expensive part. Over the course of its life, the battery in electric vehicles undergoes chemical degradation that decreases its capacity until it is unable to power the vehicle. Generally, an electric vehicle is said to have less than 80 per cent of its capacity at the end of its life (EOL). EOL is also assumed to be reached when the battery has more than a 5 per cent self-discharge rate compared to its state when purchased. Lithium-ion (Li-ion) batteries are the most commonly used battery type in electric scooters. In these batteries, Li-ions move in-between the electrodes through the electrolyte to either discharge current (to move the EV) or charge the battery.

General Motors Co. and Honda Motor Co. will jointly develop affordable electric vehicles in major global markets, dramatically expanding a partnership that already spans gas-powered models, batteries and self-driving technology. The automakers plan to create a new architecture based on GM's Ultium EV battery that will be used primarily for small crossover SUVs, with the first models available in North America in 2027, they said in a statement Tuesday. The project is intended to produce EVs that will be priced below GM's planned $30,000 Chevrolet Equinox and similar future offerings from Honda, the companies said on a call with journalists. "GM and Honda will share our best technology, design and manufacturing strategies to deliver affordable and desirable EVs on a global scale, including our key markets in North America, South America and China," GM Chief Executive Officer Mary Barra said in the statement. The collaboration marks a major move toward democratizing electric vehicles, most of which are expensive and beyond the reach of many consumers.

Artificial intelligence could help to create long-lasting electric vehicle (EV) batteries that charge faster. William Chueh at Stanford University in the US and his colleagues have developed an AI that optimises EV battery recharging while also maximising the battery's lifespan. "If you want to charge a battery quickly there is an infinite number of ways you can do so," says Chueh. Standard EV batteries tend to be recharged quickly at first, and then more slowly, for example.