According to sources close to the company, Baidu is currently in discussions with PostAuto, a division of Swiss Post, to roll out a robotaxi service in Switzerland. The company aims to begin testing Apollo Go in Switzerland before the end of this year. These plans, which were first highlighted by the Wall Street Journal, signal Baidu’s intention to compete internationally with other autonomous driving firms.

Baidu’s international ambitions come as more Chinese self-driving startups pursue growth abroad. WeRide, another China-based autonomous technology firm listed in the U.S., has already expanded operations into more than 30 cities across ten countries, including China, the UAE, France, and Singapore. Partnerships are also forming with global players — Uber, for instance, has teamed up with WeRide, Pony, and Momenta Technology to offer robotaxi services on its platform in markets such as the UAE and Europe.

In China, Baidu’s Apollo Go operates one of the largest fleets of autonomous taxis, with service in major cities such as Beijing, Guangzhou, and Wuhan. However, the rollout has not been without controversy. In Wuhan, both residents and taxi drivers have expressed concerns about the impact of self-driving vehicles on local jobs, highlighting the complex social challenges that can come with rapid technological change.

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The new company, based in Sweden, is building a team of up to 20 engineers and has already secured early-stage investment from a number of prominent backers. Investors include angel investors alongside firms such as Earlybird, Village Global, AENU, and Planet A. While the size of the investment remains undisclosed, the level of interest signals confidence in the leadership team and their vision for the future of industrial automation.

Drawing from their experience at Northvolt, Khullar explained that the team will combine expertise from multiple disciplines to solve complex challenges in machine learning, particularly those faced in battery R&D and manufacturing. Their goal is to create AI-powered software platforms that can optimize every stage of industrial production, driving greater efficiency and performance across a wide range of industries.

Aris Machina’s platform will target not only battery manufacturing, but also sectors such as semiconductors, biopharmaceuticals, robotics, and defense. The startup’s mission is to streamline processes and unlock new levels of productivity by leveraging the latest advancements in AI.

The venture also marks Peter Carlsson’s first significant position since leaving Northvolt in November. According to Khullar, their shared background at Northvolt is a unique strength for Aris Machina. “Unless you experienced Northvolt from the inside, it’s difficult to understand what an incredibly hard mission we were after,” he said, emphasizing the determination and expertise both bring to their new project.

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In a filing made public this month, the USPTO issued a “nonfinal office action” regarding Tesla’s trademark application, giving the company three months to respond before the application is officially abandoned. This means Tesla still has an opportunity to appeal or submit additional arguments to keep the application active.

A separate Tesla application for the “Robotaxi” trademark, intended for an upcoming autonomous ride-hailing service, is still under review. However, its outcome remains uncertain as the office scrutinizes whether such widely used terms can receive exclusive legal protection.

Meanwhile, Tesla’s efforts to trademark the term “Cybercab” have also faced roadblocks, as other companies are seeking similar “Cyber” trademarks, further complicating the company’s branding strategy for its new mobility services.

Tesla has not yet responded to requests for comment on the USPTO decisions. The company recently announced that its rollout of a paid autonomous ride-hailing service remains on track for June in Austin, Texas, with the new robotaxi fleet expected to begin offering rides later this year.

Despite these product plans, Tesla warned investors in April that changing global trade dynamics could impact growth forecasts and create challenges for its automotive and energy supply chains. The company acknowledged that shifting political sentiment in the U.S. and abroad could have a meaningful effect on short-term demand for its products.

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“The more we move into AI, the more we are moving into a phase where we need a more efficient computer,” Massing explained, emphasizing that software is now a key factor setting electric vehicles apart. He noted that Tesla and Chinese manufacturers such as BYD are racing ahead with advancements in vehicle software and AI, forcing European automakers to form partnerships with Silicon Valley and Chinese tech firms to keep up with the competition.

European policymakers have repeatedly stressed the need to reduce dependency on foreign technology, arguing that it is vital for security and supply chain resilience. Yet, as Massing pointed out, real progress has been slow. “I see few European initiatives that are investing in this hardware, in high performance computers for the car,” he said.

Efforts to strengthen Europe’s position have included Volkswagen Group’s recent collaborations with Rivian Automotive in the U.S. and Horizon Robotics in China, aimed at speeding up electric vehicle development. Mercedes itself has invested in the Chinese AI startup Momenta to support its driver-assistance systems. Despite these moves, Europe still lacks homegrown leaders in core technologies like cloud infrastructure and advanced automotive chips.

Massing specifically mentioned the widespread use of lidar (light-detection and ranging) sensors in the industry, which are almost exclusively manufactured in the U.S. and China. “We have in Europe neither a cloud nor a hardware that can train these models,” he warned, underlining the urgent need for European investment in high-performance computing and cloud solutions to ensure the long-term competitiveness of the continent’s automotive sector.

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GM and Nvidia Forge Expansive AI Partnership

The biggest headline out of GTC: General Motors will use Nvidia’s cutting-edge computing and AI solutions to underpin its next generation of automated vehicles and upgrade its manufacturing processes. Ali Kani, Nvidia’s automotive VP, called it a cornerstone of the company’s “trillion-dollar opportunity” in the global auto sector.

Halos: Raising the Bar on Self-Driving Safety

With autonomous vehicles finally edging into the mainstream, Nvidia CEO Jensen Huang declared, “The time for autonomous vehicles has arrived.” Yet with that arrival comes a new demand for transparency and explainability in AI-driven decisions. Enter Halos, Nvidia’s new safety platform designed to verify AI reliability across every step of self-driving development and deployment.

Halos unifies simulation, real-world testing, and system monitoring using Nvidia’s DGX training systems, Omniverse simulation, Cosmos world models, and Drive AGX compute. “No other company has Nvidia’s breadth in AI safety,” Kani emphasized, calling Halos a breakthrough for AV trust and validation.

Volvo and Gaussian Splatting: The Next Level of AV Simulation

Volvo, collaborating with software arm Zenseact, is using real-world sensor data to create 3D incident reconstructions in simulated environments—amplified by the advanced “Gaussian splatting” technique. This method lets Volvo turn a single driving event into thousands of training scenarios, blending data from multiple sensors for unmatched realism in AV training.

2027: Self-Driving Trucks Ready to Roll with Nvidia Drive AGX

Three major players are betting big on autonomous trucks each choosing Nvidia’s Drive AGX as their brain. Gatik will integrate the platform into production vehicles with Isuzu in South Carolina by 2027. Torc Robotics, Daimler’s automated truck unit, plans to deploy Freightliner Cascadia Class 8 trucks powered by Drive AGX, working with Flex Ltd. for large-scale production. Meanwhile, Plus will leverage Nvidia Cosmos to advance its SuperDrive system, also targeting 2027 for rollout.

Magna Pilots Smart In-Cabin Experiences

Global supplier Magna launched a pilot to develop next-gen automated driving and in-cabin features on the Nvidia Drive AGX platform. “We aim to explore new standards for next-generation, software-defined vehicle intelligence and autonomy,” said Steven Jenkins, Magna Electronics’ VP of technology strategy.

Foretellix and Nexar: Expanding Simulation and Validation

Israeli startups Foretellix and Nexar announced deeper integration with Nvidia products. Foretellix will use Nvidia’s world foundation models to simulate more diverse weather and road conditions for AV validation essential for robust independent safety testing. Nexar is tapping into Nvidia’s edge-case data and Cosmos simulation to strengthen its AV mapping, training, and predictive modeling capabilities.

Key Takeaways: GTC’s Auto Tech Momentum

• GM’s embrace of Nvidia AI signals a new era for smart, automated vehicles and manufacturing systems.
• Nvidia Halos sets a new standard for AV safety, with tools that span the full AI lifecycle.
• 2027 is shaping up as the launch year for autonomous trucks from Gatik, Torc, and Plus—all running Nvidia hardware and software.
• Simulation and training especially with techniques like Gaussian splatting—are accelerating the path to safe autonomy.
• From in-cabin AI to real-world validation, Nvidia’s automotive partnerships are pushing the boundaries of what’s possible for both drivers and industry.

With partnerships, pilots, and new platforms rolling out at record pace, Nvidia GTC 2024 leaves no doubt: AI is driving the future of mobility, and the world’s top automakers are all in.

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VW announced that testing will commence later this year, with a commercial rollout planned for 2026 through Uber’s platform in Los Angeles. During the early phases, human safety operators will accompany the autonomous vans to monitor and refine the system’s performance.

According to VW, a fleet of thousands of all-electric, fully autonomous ID Buzz vehicles is envisioned to be operational over the next ten years, offering a new level of mobility service to the public.

Deployment and Regulatory Approvals

The introduction of the autonomous fleet is contingent on gaining approval from federal, state, and municipal authorities. VW and Uber are preparing to navigate the necessary regulatory pathways to ensure a successful launch in compliance with all relevant standards.

Positioning Against Competitors

With this collaboration, VW and Uber aim to join companies like Waymo, which already operates more than 700 robotaxis across select U.S. markets. Meanwhile, General Motors’ Cruise division has withdrawn from the robotaxi sector to focus on advanced driver-assistance technologies. Tesla is also preparing to enter the space with its upcoming Cybercab designed for autonomous ride-hailing services.

MOIA’s Role and Strategic Vision

Volkswagen’s autonomous mobility brand, MOIA, will be responsible for delivering the necessary technology for this initiative. This includes the ID Buzz AD model and the software-driven system that will power the Uber autonomous fleet.

Christian Senger, CEO of Volkswagen Autonomous Mobility, stated, “Volkswagen is not just a car manufacturer – we are shaping the future of mobility, and our collaboration with Uber accelerates that vision.”

Kjell Gruner, President and CEO of Volkswagen Group of America, added that the partnership will enable both companies to “unleash the potential of autonomous mobility” while helping to familiarize a wider audience with the ID Buzz in the years ahead.

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Small Car, Big Tech

Despite being positioned as the entry point into Volkswagen’s electric range, the ID.EVERY1 will be the first model to benefit from the high-performance software developed in collaboration with Rivian. Priced around £17,000, the vehicle is not just a budget-friendly EV – it’s a signal of a broader transformation in Volkswagen’s approach to electrification.

Kai Grünitz, head of technical development at VW, emphasized the significance of this shift, calling the ID.EVERY1 the “front-runner” for the next-generation ID.Golf in terms of its technological architecture. He explained that the vehicle would be the first to integrate VW’s new software stack – designed in part with Rivian’s help – which aims to offer more flexibility, faster response, and a smoother user experience.

A Pivotal Year for Volkswagen

Unveiled in Düsseldorf to the soundtrack of Queen’s “Under Pressure”, the launch of the ID.EVERY1 comes at a critical moment for Volkswagen. Company CEO Thomas Schäfer didn’t sugarcoat the challenges. “2024 has undoubtedly been the most difficult year in Volkswagen’s modern history,” he said, admitting that “the Volkswagen feeling” had faded across its product lineup and that previous EV models had stumbled when it came to software integration.

The early versions of VW’s ID models – including the ID.3 and ID.4 – were criticized for buggy infotainment systems and sluggish interfaces. Drivers often found themselves frustrated with software glitches, delayed updates, and underwhelming digital experiences. With Rivian’s involvement, VW hopes to put those problems in the rearview mirror.

Who Is Rivian – and Why VW Turned to Them

Founded in 2009, Rivian has quickly earned a reputation as one of the most innovative EV manufacturers in the U.S., building electric trucks and SUVs like the R1T and R1S that blend performance, utility, and tech. At one point in 2021, the company was valued at more than $100 billion following its IPO – briefly making it the second-most valuable U.S. automaker behind Tesla.

While that valuation has since dropped significantly, to around $10 billion, Rivian remains at the forefront of software development in the EV space. Its vehicles offer advanced driver assistance systems, intuitive interfaces, and a software-first approach that attracted VW’s interest. With future vehicles like the R2 and R3 in the pipeline – designed with European markets in mind – Rivian is aiming for more compact, versatile, and accessible options.

What Rivian Brings to the Table

Unlike Volkswagen’s previous tech-sharing agreement with Ford, this deal isn’t about platform or parts exchange. There won’t be Rivian chassis under VW cars or badge-swapped models in showrooms. Instead, VW gains access to Rivian’s advanced software stack, tools, and development environment – a move meant to accelerate software deployment and product iteration across VW’s lineup.

Kai Grünitz noted that Rivian’s development speed has been impressive. “I never had such a fast response before,” he said, praising the agility of the California startup. In return, VW brings scale, compliance knowledge, and decades of experience operating across complex global markets – something Rivian, as a younger company, can leverage as it expands internationally.

What Models Will Get the New Tech?

The new software will debut in the ID.EVERY1 around 2027 and gradually expand to other models. The ID.Golf, expected to succeed the current ID.3, will follow with the same Rivian-influenced platform. Volkswagen has already confirmed that beloved model names such as Golf, Polo, and GTI will continue into the electric age, maintaining brand recognition even as the technology under the hood changes dramatically.

However, not all VW EVs will benefit from the new system right away. The upcoming ID.2.ALL, slated for release in 2026, will reportedly stick with the existing software architecture and may be rebranded as the ID.POLO when it hits production.

Why This Partnership Matters

Legacy automakers like Volkswagen are under growing pressure from Chinese EV startups and Tesla, which can bring new vehicles to market at a faster pace with more advanced tech. Historically, companies like VW have struggled with slow development cycles and legacy systems. Partnering with Rivian offers a way to leapfrog these obstacles and regain competitive momentum.

More than just a financial lifeline for Rivian, the deal represents a strategic bet for VW – one where software takes center stage. If successful, the collaboration could reshape how the brand builds, sells, and updates its vehicles, ushering in a new era where even the most affordable models come equipped with cutting-edge digital features.

In a world increasingly dominated by digital experience, Volkswagen’s message is clear – the future isn’t just electric, it’s smart. And with Rivian in its corner, the German automaker hopes to prove it can still set the pace in an

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AI Beyond the Vehicle: A New Perspective on Road Safety

For Aoude, improving traffic safety isn’t solely about smarter cars it’s about smarter roads. “We can’t wait for every vehicle on the road to become autonomous,” he says. “But we can make intersections intelligent now.” Derq’s platform does just that by embedding AI into existing infrastructure like traffic lights and roadside sensors. The goal is to make roads more predictive, responsive, and ultimately, safer especially for the most vulnerable users like pedestrians and cyclists.

Near-Misses as Predictive Indicators

Derq’s software is designed to detect and analyze near-miss incidents in real time moments where a crash was narrowly avoided. These events have long been considered red flags for future accidents, but capturing them has traditionally required laborious, months-long studies. With Derq’s tech, that process is automated and continuous, enabling city officials to respond to trouble spots before they become tragedies.

• AI analyzes data from cameras and sensors at intersections
• Heat maps reveal high-risk zones across a city
• Alerts can be sent instantly to transportation departments or fleet operators

In practice, this might lead to banning right turns on red in certain areas or redesigning traffic flows where patterns show consistent risk. It’s a dynamic, data-informed approach to urban planning one that adjusts as conditions change, not years later.

Recognition and Support from U.S. Authorities

Derq’s vision has earned national attention. In January, the company became the only private enterprise to be named a top-tier winner of the U.S. Department of Transportation’s Intersection Safety Challenge an initiative aimed at curbing intersection-related crashes, which account for a significant portion of road fatalities.

Industry Validation and Government Collaboration

The Intelligent Transportation Society of America praised the integration of digital infrastructure with physical road systems, calling it a vital path forward. In its 2025 safety blueprint, the group emphasized the importance of technologies like AI, automation, and vehicle-to-everything (V2X) communication in addressing the persistent safety crisis that has kept U.S. road fatalities above 40,000 annually in recent years.

“Technology is a key tool to solving our traffic safety crisis,” the society noted. “It is more apparent than ever that we need to prioritize investments in digital infrastructure.”

From Self-Driving to Smarter Intersections

Aoude’s journey began with the promise of autonomous vehicles he was part of the MIT team exploring AV tech between 2007 and 2011. But by 2016, it became clear that wide-scale adoption would take longer than anticipated. Rather than wait for the cars to catch up, he pivoted the focus of Derq’s AI to the infrastructure they rely on.

No Need for Vehicle Upgrades

Derq’s biggest advantage? Its systems can operate independently of the vehicles on the road. That means no costly overhauls or software installs are needed for drivers safety improvements can be implemented at the city level, and their benefits felt immediately.

Growing Reach and Future Expansion

Backed by investors such as AT&T Ventures, Derq’s AI solutions are now active at around 400 intersections across 25 U.S. cities and Dubai. Its first deployment came through the Michigan Department of Transportation in Detroit, where the company still maintains an office. With ongoing plans to expand in 2025, more urban areas are expected to adopt Derq’s solution to tackle intersection risk.

A Broader Mission

As the U.S. marks a century of automotive innovation, Derq is helping shape what the next 100 years could look like a future where cities can proactively prevent collisions and fatalities, not just react to them. It’s a compelling reminder that smart mobility isn’t just about autonomous cars it’s also about the roads we build, the systems we connect, and the data we act on.

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As Automotive News marks its centennial, the persistent tragedy on American roads more than 40,000 deaths per year in recent records reminds us that technology alone is not enough. It also prompts urgent reflection on what solutions can make a real difference moving forward.

A Crisis That Won’t Subside

On average, 112 Americans lost their lives each day on the road in 2023, according to NHTSA. That’s the equivalent of a daily airline disaster a scale of loss that has not garnered the sustained public outcry or policy urgency it deserves.

Tech’s Missed Expectations

2009 marked a turning point: Volvo debuted automated emergency braking, and Google launched its self-driving car program. The prevailing belief was that such technologies could bring about a dramatic decline in crashes and fatalities. Instead, the opposite happened. Over the past 15 years, U.S. road deaths have increased by 21 percent. Technology didn’t prevent the surge and in some cases, may have complicated it.

Lessons From History

The first known automobile fatality in the U.S. occurred in 1899 when H.H. Bliss was struck by an electric taxi in New York City. Just 25 years later, annual fatalities had climbed to over 18,000. Alarm bells rang including from The New York Times, which compared the automobile to a more deadly machine than a weapon of war but the momentum for reform soon faded.

The Mirage of Automation

Peter Norton, author of Autonorama, argues that society has placed too much faith in future tech while ignoring more practical solutions. “We have learned, mistakenly, to think of technology as a problem solver,” he said, pointing to the continued rise in road deaths despite the proliferation of advanced systems like lane-keeping assistance and automated braking.

Mixed Results from Advanced Safety Features

The Insurance Institute for Highway Safety (IIHS) has studied automation’s impact. Some technologies do help:

• Automated emergency braking (AEB) cuts rear-end crashes by 50 percent
• AEB with pedestrian detection reduces pedestrian crashes by 27 percent
• Blind-spot monitoring lowers injury-causing lane-change crashes by 23 percent

Yet, many systems fall short in real-world scenarios. Pedestrian AEB, for instance, fails at night a time when visibility is lowest and risk is highest. And partial automation features can lull drivers into overconfidence, treating safety tools as conveniences rather than active support systems.

Human Behavior Remains the Biggest Threat

Despite advancements in car design and crash survivability, behavioral factors like speeding and impaired driving continue to dominate fatal crash data. According to the Governors Highway Safety Association, speed contributes to roughly 30 percent of fatal crashes, while drunk driving plays a role in about a third.

Policy Inaction

Jonathan Adkins, executive director of the GHSA, believes federal regulators have not done enough. He criticized the Biden administration for failing to mandate alcohol-detection systems in vehicles. “They sat on their hands,” he said, adding that strong leadership potentially from a returning Trump administration could leave a lasting legacy by requiring such technology.

Adkins also highlighted missed opportunities in trauma care. While emergency transfusions could save lives, current rules restrict federal safety funds from supporting such measures because they might aid non-traffic-related incidents.

Robotaxis: Promise With a Caveat

Waymo, Google’s autonomous vehicle division, has logged more than 25 million driverless miles and serves over 200,000 rides per week in cities like San Francisco and Phoenix. The company claims its robotaxis have reduced injury crashes by 73 percent compared to human drivers.

Still, these vehicles are not without flaws. Examples include Waymo cars crashing into the same tow truck and Cruise vehicles driving into wet concrete. There are just over 650 Waymo vehicles in service a drop in the ocean compared to the nearly 290 million cars on U.S. roads. Mass deployment remains years away.

Where Do We Go From Here?

Experts like David Harkey of IIHS emphasize that no single solution will solve this crisis. Instead, layered strategies combining behavioral changes, infrastructure redesign, effective policy, and responsible tech integration are required to make meaningful progress.

“It’s a shared responsibility,” Harkey said. “Small blocks at a time, we can build out and show the success that can be had.”

As we look ahead, the vision of traffic death eradication that once captivated the public remains distant but not impossible. The key may lie not in the perfection of future vehicles, but in how we reimagine our roads, our responsibilities, and the role of technology in serving human lives, not just driving them.

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AI at the Wheel: From Niche to Necessity

Ali Kani, Nvidia’s vice president and general manager of automotive, called the current scale of its automotive business already worth over $1 billion  just the beginning. “This is still in its infancy,” he said, hinting at the vast untapped potential of AI across every link in the automotive chain.

Strategic Partnerships Expand Nvidia’s Reach

Among the most high-profile announcements at GTC was Nvidia’s broadened partnership with General Motors. GM will utilize Nvidia’s AI platforms for a wide range of applications from autonomous driving and smart factory design to operational simulations and software refinement. The automaker joins others like Hyundai and Toyota, both of whom revealed major collaborations with Nvidia at CES earlier this year.

Other new or expanded partnerships include:

• Magna — The global auto supplier will integrate Nvidia’s Drive AGX platform to fast-track development of self-driving features and intelligent cabin tech.
• Automated trucking firms — Gatik, Plus, and Torc Robotics, all current Nvidia partners, plan to deepen their use of the company’s AI computing systems. Gatik announced it will deploy Nvidia hardware in its next-generation autonomous trucks entering production in 2027.

Nvidia’s AI Stack: More Than Just In-Car Computers

Nvidia’s “Drive” ecosystem is built on three powerful pillars designed to accelerate AV development across the board:

• DGX — A high-performance computing system used to train AI models, especially those involved in perception and decision-making.
• Omniverse + Cosmos — Platforms enabling photorealistic simulation and digital twin creation for testing vehicle behavior in virtual environments.
• AGX — A scalable in-vehicle computing solution that powers real-time AI functions directly in cars and trucks.

According to Kani, the success of autonomous vehicles and by extension, Nvidia’s role in that success will be defined by the pace of development. “Speed is the differentiator,” he said. “Our partners’ ability to iterate fast is where we come in.”

Keeping AI Safe at Speed

Amid excitement over AI’s capabilities, Nvidia also addressed rising concerns over safety. At GTC, the company unveiled its new Halos safety platform a system designed to ensure AI systems remain within strict safety bounds throughout the development and deployment pipeline. This includes simulation testing, real-world validation, and performance monitoring.

Safety at Scale

The pressure for safety in autonomous systems is mounting. Regulators and watchdogs have raised alarms over AI decision-making in real-time road scenarios. Nvidia’s Halos represents an industry-first effort to build end-to-end transparency and risk mitigation into the AI lifecycle a move likely to become essential as automated systems scale globally.

AI and Robotics: Beyond the Vehicle

While the automotive sector remains a core focus, Nvidia’s ambitions stretch far beyond four wheels. Company CEO Jensen Huang highlighted how the same AI technology driving vehicle automation is also being applied to humanoid robots machines designed to navigate and manipulate the physical world.

“The ability to understand a three-dimensional world will enable a new era of physical AI and robotics,” Huang said. From cars that drive themselves to robots that assist in factories and homes, Nvidia’s technology aims to create a seamless digital-physical interface.

The Road Ahead

With its expanded role in transportation, Nvidia is no longer just supplying chips it’s becoming an integral architect of mobility’s AI future. Whether training advanced driver-assistance systems or simulating entire supply chains, the company’s AI platforms are reshaping how cars are made, how they drive, and how they learn.

And if Nvidia’s projections hold true, the trillion-dollar horizon it sees may just be the beginning of a much larger transformation one driven as much by silicon and code as by steel and rubber.

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