A new report shows that only 7 percent of new-car buyers in the US completed their purchase online, despite a major push by automakers, Amazon, and others to move past the dealership. In the US, cars follow only housing as the most expensive purchase consumers make. So it makes a lot of sense that, according to recent buyer surveys, very few of them want an Amazon-style, one-click approach to getting a new set of wheels. "People want to see, feel, and touch the car," says Erin Lomax, the vice president of consumer marketing at Cox Automotive, a research firm that also makes digital auto sales products that allow dealers to initiate transactions online. Not to mention test-driving the expensive thing they'll probably use every day.

As vehicles grow more software-dependent, repairing them has become harder than ever. A bill in the US House called the Repair Act would ease those restrictions, but it comes with caveats. Every time you get behind the wheel, your car is collecting data about you. Where you go, how fast you're driving, how hard you brake, and even how much you weigh. All of that data is not typically available to the vehicle owner.

It's a rare thing to shoot yourself in the foot and win a marathon. For years, Elon Musk has managed to do something like that with Tesla, achieving monumental success in spite of a series of self-inflicted disasters. There was the time he heavily promoted the company's automated factory, only to later admit that its "crazy, complex network of conveyor belts" had thrown production of the Model 3 off track; and the time a tweet led him to be sued for fraud by the Securities and Exchange Commission; and the time he said that the Tesla team had "dug our own grave" with the massively delayed and overhyped Cybertruck. Tesla is nonetheless the most valuable car company in the world by a wide margin. Yesterday evening, Tesla reported first-quarter earnings for 2025, and they were abysmal: Profits dropped 71 percent from the same time last year.

The House select committee on combatting China held an event highlighting American tech and robotics manufacturers on Capitol Hill. Tesla made an appearance on Capitol Hill Wednesday where the company was held up as one of several key American manufacturers during a bipartisan event on U.S.-made robotics. Two Tesla humanoid robots were at the event, with onlookers crowding the machines as they struck various poses. They waved their arms at times, and held up hands with two fingers aloft on each in a Richard Nixon-like pose. At one point, a robot's arm swung out and hit the rope dividing it from the crowd, briefly sending a security guard scrambling to fix it.

This study presents a novel application of Graph Neural Networks (GNNs) to optimize dealership network planning for a luxury car manufacturer in the U.S. By conducting a comprehensive literature review on dealership location determinants, the study identifies 65 county-level explanatory variables, augmented by two additional measures of regional interconnectedness derived from social and mobility data. An ablation study involving 34 variable combinations and ten state-of-the-art GNN operators reveals key insights into the predictive power of various variables, particularly highlighting the significance of competition, demographic factors, and mobility patterns in influencing dealership location decisions. The analysis pinpoints seven specific counties as promising targets for network expansion. This research not only illustrates the effectiveness of GNNs in solving complex geospatial decision-making problems but also provides actionable recommendations and valuable methodological insights for industry practitioners.

One of the challenges in text generation is to control text generation as intended by the user. Previous studies proposed specifying the keywords that should be included in the generated text. However, this approach is insufficient to generate text that reflect the user's intent. For example, placing an important keyword at the beginning of the text would help attract the reader's attention; however, existing methods do not enable such flexible control. In this paper, we tackle a novel task of controlling not only keywords but also the position of each keyword in the text generation. To this end, we propose a task-independent method that uses special tokens to control the relative position of keywords. Experimental results on summarization and story generation tasks show that the proposed method can control keywords and their positions. The experimental results also demonstrate that controlling the keyword positions can generate summary texts that are closer to the user's intent than baseline.

AutoRevo, a leading automotive industry software provider, announces the launch of its groundbreaking AI Vehicle Description Builder, an innovative solution that addresses the challenges dealerships face in creating engaging, accurate, and consistent vehicle descriptions for their online inventory. With the AI Vehicle Description Builder, AutoRevo is set to revolutionize the way dealerships present their vehicles on digital platforms. The automotive industry has long struggled with the time-consuming and resource-intensive task of generating effective vehicle descriptions. Realizing that many dealerships either lack the resources for crafting detailed descriptions or struggle to maintain consistency, AutoRevo developed a cutting-edge AI tool designed to streamline the process and enhance online vehicle listings. The AI Vehicle Description Builder works in conjunction with inventory companies to produce high-quality, accurate, and engaging descriptions.

General Motors is bringing artificial intelligence into the vehicle inspection process. The automaker is making an undisclosed "strategic investment" in Israeli startup UVeye, which makes vehicle diagnostic systems that use sensors and AI to quickly identify damaged parts or maintenance issues. The investment in UVeye was made by GM Ventures, the automaker's venture fund, which also has investments in a variety of other AI-themed startups. As part of the collaboration, GM will sell UVeye's technology to its dealer network to upgrade their vehicle inspection systems. GM will also work with UVeye on a variety of vehicle inspection technology projects involving used car auctions, fleet operations, and automotive dealership sales.

SALT and Cion Digital announced a strategic partnership to bring SALT's crypto lending solutions to 5,000 auto dealerships in the US. The announcement marks the launch of SALT's Embedded Crypto Lending Service, which will enable financial service providers and fintech platforms to rapidly deploy crypto financing solutions. Having launched in 2016, SALT was the first platform to offer crypto-backed loans and has since been focused on optimizing its lending technology and servicing operations. Over the past few years, the Company has built a full stack loan management and risk platform that manages complex crypto loans at scale. With the launch of Embedded Crypto Lending, SALT is bringing this technology to other platforms, helping them further their mission to offer new and novel products to their customers.

CALGARY, Alberta, July 06, 2021 (GLOBE NEWSWIRE) -- Quorum Information Technologies Inc. (TSX Venture: QIS) (Quorum) announced today that it is receiving advisory services and funding of up to $724,746 from the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP) to support a research and development project to consolidate Quorum's dealership data and add machine learning capabilities to its Cloud-based applications. The NRC IRAP support is the next step in a process started in 2020 when Quorum launched QAnalytics – an enterprise reporting tool for the Quorum suite of products powered by Microsoft Power BI. QAnalytics is now utilized by 30% of Quorum's XSellerator Dealership Management System (DMS) customers. "QAnalytics has changed how we manage our 11 franchised dealerships in our auto group," stated Tim Davis, CEO of Davis Auto Group. "The real time metrics that QAnalytics provides for all aspects of our dealership's operations allow our management team to make confident, data-driven decisions." Quorum's next step is to strategically consolidate dealership data from its 1,025 customers on Microsoft Azure Synapse, enabling QAnalytics to deliver enhanced critical Business Intelligence insights into dealership operations and provide a consolidated dataset for Machine Learning projects.