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Nvidia and auto suppliers roll out partnerships to revive stalled self-driving ambitions

After years of costly failures and repeated delays, the self-driving car industry is once again pushing forward as chipmakers, technology firms and auto suppliers bet that artificial intelligence and deep partnerships can reignite progress. Companies including Nvidia are positioning themselves at the center of this renewed effort, even as automakers remain cautious about costs, scalability and consumer demand.

Fully autonomous vehicles promise to transform transportation, but delivering systems safe enough for public roads has proved far more complex and expensive than initially expected. While a handful of players such as Waymo and Tesla have chosen to pursue in-house development, legacy automakers including General Motors and Ford Motor have pulled back from their own fully autonomous programs.

At this year’s Consumer Electronics Show in Las Vegas, a wave of new collaborations signaled fresh momentum. Amazon Web Services and German supplier Aumovio announced a partnership to support the commercial rollout of self-driving vehicles. Autonomous trucking firm Kodiak AI teamed up with Bosch to scale production of autonomous hardware and sensors.

Nvidia also unveiled its next-generation autonomous driving platform, which will underpin a robotaxi alliance involving Lucid Group, Nuro and Uber. Separately, Mercedes-Benz said it will launch a new advanced driver-assistance system in the United States later this year, powered by Nvidia chips, allowing limited autonomous operation on city streets under driver supervision.

Artificial intelligence is increasingly seen as the key to overcoming some of the industry’s biggest hurdles. Generative AI tools are speeding up development and validation while reducing the resources required, according to Ozgur Tohumcu of AWS, who described AI as a “big accelerant” for autonomous driving.

Western automakers are also feeling pressure from China, where regulators last month approved two vehicles with Level 3 autonomous capabilities, allowing hands-off driving under certain conditions. Still, industry leaders caution against unrealistic expectations. Jochen Hanebeck, CEO of Infineon, warned against “market fantasy” that fully self-driving cars could soon become commonplace, noting that automakers currently prefer revenue-generating Level 2 driver-assistance systems.

Robotaxi trials are expanding in small pockets across China, the United States, Europe and the Middle East, but scaling them remains costly. According to Jeremy McClain, expanding coverage requires massive data, fleets and logistics investments.

The industry’s long history of hype still looms large. Tesla CEO Elon Musk famously predicted in 2019 that a million self-driving Teslas would be on the road within a year, yet only launched a limited robotaxi service last year. Early setbacks, including the shutdown of GM’s Cruise unit after a high-profile accident, forced many automakers to retreat.

Nvidia executives argue that AI breakthroughs are finally addressing long-standing weaknesses, particularly in handling rare “edge cases.” Ali Kani said foundational advances are making the technology feel closer to readiness. Analysts, however, say Tesla still holds a significant lead, even as Nvidia’s open-source platform gives rivals a shared alternative.

Nissan and Monolith Expand AI Collaboration to Speed Up Car Development

Nissan has expanded its partnership with UK software company Monolith to accelerate car development using artificial intelligence. The collaboration aims to reduce the need for physical testing by applying AI-driven data analysis, significantly shortening the time it takes for new models to reach the market.

The renewed partnership follows the successful use of Monolith’s AI to cut testing time for chassis bolt tightening on the new electric Nissan Leaf — a process that will now be applied to upcoming European models as well.

Emma Deutsch, Director of Customer-Oriented Engineering and Test Operations at Nissan Technical Centre Europe, noted that Chinese automakers can develop a new model in just 18 months, adding, “We’ve got to get vehicles to market quicker.” By applying Monolith’s AI to physical test data collected since the 1992 launch of the Nissan Micra, the company managed to shorten bolt-tightening tests from six months to five, with a goal to cut them further to three months.

Nissan is now working with Monolith on additional projects to reduce testing times for tyres and batteries. These AI applications could help Nissan reduce overall vehicle testing by 20%. Monolith’s recent acquisition by AI data centre operator Coreweave is expected to further enhance R&D efficiency in the automotive sector.

Volkswagen Commits €1 Billion to AI by 2030 to Drive Efficiency and Savings

Volkswagen announced on Tuesday that it will invest up to €1 billion ($1.2 billion) in artificial intelligence by 2030, aiming to integrate the technology across all areas of its operations. The strategy, revealed at the IAA car show in Munich, is part of the automaker’s effort to remain competitive against rising Chinese rivals and to modernize its electric vehicle lineup.

The German carmaker expects AI-driven initiatives to deliver up to €4 billion in savings by 2035. Investments will focus on:

  • AI-supported vehicle development to shorten model design cycles.

  • Industrial applications to streamline manufacturing.

  • High-performance IT infrastructure to support digital transformation.

For us, AI is the key to greater speed, quality and competitiveness — along the entire value chain, from vehicle development to production,” said Hauke Stars, Volkswagen’s chief IT officer.

Volkswagen is undergoing deep restructuring in its two main markets, Germany and China, as it prepares new electric models and implements cost-cutting programs at home. On Sunday, the company presented its ID.CROSS, a new small electric SUV concept aimed at making EVs more affordable.

The company sees AI as a catalyst for faster innovation and efficiency, positioning itself to better compete in the evolving automotive landscape.