Connect with us

News

NVIDIA says Tesla raised the bar for self-driving tech, car makers must deliver

Tesla's Full Self-Driving computer. | Image: Tesla

Published

on

NVIDIA, a prominent and highly successful leader in computer chip design, says that Tesla has raised the bar in autonomous driving software, and other car makers will have to deliver similar performance if they want to compete in the long-term future of the auto industry, according to a recent NVIDIA company blog.

“It’s financially insane to buy anything other than a Tesla,” CEO Elon Musk stated during the company’s Autonomy Day event. He then compared the purchase of any other car as equivalent to buying a horse for one’s transportation purposes. NVIDIA, for its part, agrees with Musk and Tesla’s sentiments about the future of self-driving and the need for powerful computers to push its progress.

“Self-driving cars—which are key to new levels of safety, efficiency, and convenience—are the future of the industry. And they require massive amounts of computing performance… This is the way forward. Every other automaker will need to deliver this level of performance,” the chip maker wrote.

The type of autonomous driving technology Tesla is pushing is predicted to be the inevitable standard, and the company’s lead in the arena will likely increase even further as more of their vehicles take to the road. “By end of this quarter, about half a million Teslas will have full self-driving hardware (pending computer swap) & we will make another half million FSD cars by mid next year,” Musk tweeted, emphasizing this point and echoing what he’d explained the day prior.

Tesla’s recent Autonomy Day presentation drew comparisons between the all-electric car maker’s Full Self-Driving (FSD) computer chip and those produced by NVIDIA, the only computer processing unit maker delivering performance in line with Tesla’s. NVIDIA currently has two self-driving chips in the works: the Xavier SoC (system on a chip) for assisted driving AutoPilot features, and the DRIVE AGX Pegasus computer for full self-driving. The comparisons in Tesla’s presentation were directed at the Xavier in a single-chip configuration.

The technical performance specifications required to run powerful artificial intelligence (AI) neural networks (NN) for autonomous driving require operations performed per second to be measured in the trillions – abbreviated as TOPS (tera operations per second). Tesla’s FSD computer chip can perform at a rate of 72 TOPS (x2 chips in the computer for 144 TOPS total), and the Xavier does 30 TOPS (mistakenly claimed to be 21 TOPS at Tesla’s event, per NVIDIA’s blog).

NVIDIA also expressed in the blog piece its opinion that the match between FSD and Xavier wasn’t quite an apples-to-apples comparison, given the purposes of the two chips. The chip designer prefers its DRIVE AGX Pegasus for the line-up, a computer intended for fully autonomous driving and capable of 320 TOPS. Tesla is assumingly aware of this product and obviously acknowledges the high level of technology developed by NVIDIA given that Hardware 2.5, the computer currently running Tesla’s Autopilot features, was made by the company.

A Tesla with driver features “deleted” under the Tesla Network. | Image: Tesla

There are additional specifications such as power consumption that further differentiate FSD from NVIDIA’s products with a more similar purpose to Tesla’s latest computer. Thus, a different product match may not have mattered towards the overall point being made in the presentation. Either way, a more important distinction between the two companies is the current status of their technologies.

Advertisement
-->

Tesla’s chip was crowned as “objectively the best in the world” by Musk, and this looks to be true, given the fact that all Tesla Model S, 3, and X vehicles being produced now have the hardware installed and will add to the already accruing real world self-driving data the company’s cars provide. NVIDIA has partnered with other car manufacturers to develop its products, but they are not incorporated in production vehicles the way Tesla’s FSD has been yet.

The performance Tesla has achieved in its FSD computer is impressive, and that was and continues to be the point. “[Autonomy] is basically our entire expense structure,” Musk told an investor inquiring about where the California-based company was incurring the most cost. Tesla is hedging its fiscal future on the success of autonomous driving in the marketplace, and the company is doing so with bullish energy driven by its famous top executive.

Musk expects Tesla’s Full Self-Driving software to be complete by the end of this year and fully operational by the second quarter of next year.

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

Advertisement
Comments

News

Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo

“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.

Published

on

Credit: Grok Imagine

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. 

Advertisement
-->

“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.”

Advertisement
-->

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.

Continue Reading

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.

Published

on

Credit: xAI/X

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.”

Advertisement
-->

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. 

Continue Reading

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. 

Published

on

xAI-supercomputer-memphis-environment-pushback
Credit: xAI

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.”

Advertisement
-->

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. 

Continue Reading