News
Tesla argues human error caused fatal 2019 crash, not Autopilot: report
Tesla now faces the jury’s verdict in a trial alleging that Autopilot caused a fatality, and the trial is expected to set a precedent for future cases surrounding advanced driver assistance systems (ADAS). During closing arguments on Tuesday, an attorney for the plaintiffs pointed to an analysis Tesla conducted two years before the accident, claiming that the automaker knowingly sold the Model 3 with a safety issue related to its steering.
The trial began in California late last month after a 2019 incident in which 37-year-old Micah Lee veered off a highway outside Los Angeles at 65 miles per hour, suddenly striking a palm tree before the vehicle burst into flames. According to court documents, the crash killed Lee and injured both of his passengers, one of whom was an 8-year-old boy.
Lee’s passengers and estate initiated a civil lawsuit against Tesla, alleging that the company knew that Autopilot and its other safety systems were defective when it sold the Model 3.
Tesla has denied any liability in the accident, claiming that Lee had consumed alcohol before getting behind the wheel and saying it could not detect if Autopilot was engaged at the time of the crash.
This and other trials come as regulatory requirements for ADAS suites are just emerging, and the cases are expected to help navigate future court cases related to accidents with the systems.
According to Reuters, the attorney for the plaintiffs, Jonathan Michaels, showed the jury an internal safety analysis from Tesla in 2017 during closing arguments, in which employees identified “incorrect steering command” as a potential safety issue. Michaels said the issue involved an “excessive” steering wheel angle, arguing that Tesla was aware of related safety problems before selling the Model 3.
“They predicted this was going to happen. They knew about it. They named it,” Michaels said.
Michaels also said that Tesla created a specific protocol to deal with affected customers and that the company instructed workers to avoid accepting liability for the issue. Michaels also echoed prior arguments, saying that Tesla knew it was releasing Autopilot in an experimental state, though it needed to do so to boost market share.
“They had no regard for the loss of life,” Michaels added.
Michael Carey, Tesla’s attorney, said that the 2017 analysis wasn’t meant to identify the defect but instead was meant to help avoid any potential safety issues that could theoretically occur. Carey also said that Tesla developed a system to prevent Autopilot from making the same turn that had caused the crash.
Carey said that the subsequent development of the safety system “is a brick wall standing in the way of plaintiffs’ claim,” adding that there haven’t been any other cases where a Tesla has maneuvered the way that Lee’s did.
Instead, Carey argued to the jury that the crash’s simplest explanation was human error, asking jurors to avoid awarding damages on behalf of the severe injuries encountered by the victims.
“Empathy is a real thing, we’re not saying its not,” Carey argued. “But it does not make cars defective.”
Earlier this month, a federal judge in California ruled in Tesla’s favor in a similar case looking at whether the automaker misled consumers about its Autopilot system’s capabilities. In that case, which had the chance to become a class-action lawsuit, the judge ruled that most of the involved plaintiffs had signed an arbitration clause when purchasing the vehicle, requiring the claims to be settled outside of court.
The cases are expected to set precedents in court for future trials involving Tesla’s Autopilot and Full Self-Driving (FSD) beta systems and the degree of the automaker’s responsibility in accidents related to their engagement. Tesla is also facing additional information requests from the U.S. Department of Justice related to its Autopilot and FSD beta.
Tesla has received more requests regarding Autopilot and FSD from DOJ
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News
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.
NVIDIA CEO Jensen Huang has offered high praise for Tesla’s Full Self-Driving (FSD) system during a Q&A at CES 2026, calling it “world-class” and “state-of-the-art” in design, training, and performance.
More importantly, he also shared some insights about the key differences between FSD and Nvidia’s recently announced Alpamayo system.
Jensen Huang’s praise for Tesla FSD
Nvidia made headlines at CES following its announcement of Alpamayo, which uses artificial intelligence to accelerate the development of autonomous driving solutions. Due to its focus on AI, many started speculating that Alpamayo would be a direct rival to FSD. This was somewhat addressed by Elon Musk, who predicted that “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.”
During his Q&A, Nvidia CEO Jensen Huang was asked about the difference between FSD and Alpamayo. His response was extensive:
“Tesla’s FSD stack is completely world-class. They’ve been working on it for quite some time. It’s world-class not only in the number of miles it’s accumulated, but in the way it’s designed, the way they do training, data collection, curation, synthetic data generation, and all of their simulation technologies.
“Of course, the latest generation is end-to-end Full Self-Driving—meaning it’s one large model trained end to end. And so… Elon’s AD system is, in every way, 100% state-of-the-art. I’m really quite impressed by the technology. I have it, and I drive it in our house, and it works incredibly well,” the Nvidia CEO said.
Nvidia’s platform approach vs Tesla’s integration
Huang also stated that Nvidia’s Alpamayo system was built around a fundamentally different philosophy from Tesla’s. Rather than developing self-driving cars itself, Nvidia supplies the full autonomous technology stack for other companies to use.
“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.
He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.
“So our system is really quite pervasive because we’re a technology platform provider. That’s the primary difference. There’s no question in our mind that, of the billion cars on the road today, in another 10 years’ time, hundreds of millions of them will have great autonomous capability. This is likely one of the largest, fastest-growing technology industries over the next decade.”
He also emphasized Nvidia’s open approach, saying the company open-sources its models and helps partners train their own systems. “We’re not a self-driving car company. We’re enabling the autonomous industry,” Huang said.
Elon Musk
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.
xAI, Elon Musk’s artificial intelligence startup, has purchased five additional 380 MW natural gas turbines from South Korea’s Doosan Enerbility to power its growing supercomputer clusters.
The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.
xAI’s turbine deal details
News of xAI’s new turbines was shared on social media platform X, with user @SemiAnalysis_ stating that the turbines were produced by South Korea’s Doosan Enerbility. As noted in an Asian Business Daily report, Doosan Enerbility announced last October that it signed a contract to supply two 380 MW gas turbines for a major U.S. tech company. Doosan later noted in December that it secured an order for three more 380 MW gas turbines.
As per the X user, the gas turbines would power an additional 600,000+ GB200 NVL72 equivalent size cluster. This should make xAI’s facilities among the largest in the world. In a reply, Elon Musk confirmed that xAI did purchase the turbines. “True,” Musk wrote in a post on X.
xAI’s ambitions
Recent reports have indicated that xAI closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. The funding, as per the AI startup, “will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products.”
The company also teased the rollout of its upcoming frontier AI model. “Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote in a post on its website.
Elon Musk
Elon Musk’s xAI closes upsized $20B Series E funding round
xAI announced the investment round in a post on its official website.
xAI has closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development.
xAI announced the investment round in a post on its official website.
A $20 billion Series E round
As noted by the artificial intelligence startup in its post, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others.
Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.
As xAI stated, “This financing will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products reaching billions of users, and fuel groundbreaking research advancing xAI’s core mission: Understanding the Universe.”
xAI’s core mission
Th Series E funding builds on xAI’s previous rounds, powering Grok advancements and massive compute expansions like the Memphis supercluster. The upsized demand reflects growing recognition of xAI’s potential in frontier AI.
xAI also highlighted several of its breakthroughs in 2025, from the buildout of Colossus I and II, which ended with over 1 million H100 GPU equivalents, and the rollout of the Grok 4 Series, Grok Voice, and Grok Imagine, among others. The company also confirmed that work is already underway to train the flagship large language model’s next iteration, Grok 5.
“Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote.
Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo
Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines
