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Tesla’s applications for Dojo in FSD, Optimus and potentially more

Credit: Tesla

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Much excitement surrounding Tesla’s Dojo supercomputing cluster has been swirling in recent months since the system went online, and the automaker already expects it to be one of the world’s most powerful supercomputers by early next year. But one reporter recently noted that Dojo could someday have additional uses beyond processing vast amounts of data for Tesla’s Full Self-Driving (FSD) system and humanoid robot.

Dojo can process millions of terabytes of video data per second from the company’s vehicles, training its neural network at an incredible rate. The company has said that the video foundation models input to Dojo would effectively serve as the brain of its vehicles and its Optimus robot.

In a recent video segment about how Dojo is expected to revolutionize self-driving, however, Yahoo Finance reporter Pras Subramanian also talked about the supercomputing cluster’s potential applications beyond FSD and Optimus.

The short discussion, hosted by Seana Smith, details how the Dojo system will use Tesla’s AI model to train FSD. However, Subramanian also says the supercomputer could someday be used for vessels other than cars, including motorcycles, bicycles and boats. The conversation also touched on how Dojo works, the complexity of training AI to handle roads and Ford and Volkswagen’s decision to end Argo AI operations, among other topics.

You can watch a short clip from the video segment below or see the full conversation here.

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As for cars, Musk has previously talked about the potential of using Dojo to perform traffic control simply with the system’s inputs for things like accidents, potholes, road closures or other data that would be useful for a Tesla to access in real-time. Musk said in June that Dojo had been “online and running useful tasks for a few months,” helping out with production workloads and spurring on the current round of excitement surrounding the computing cluster.

In June, Tesla posted about Dojo on X, detailing how its neural networks were already being accessed in its cars and adding that the company is “building the foundation models for autonomous robots.” Below is an excerpt from the thread:

“Our multi-modal neural networks are already in customer vehicles—these networks take in arbitrary modalities such as camera videos, maps, navigation, IMU (Inertial Measurement Unit), GPS etc.

Tasks such as Occupancy prediction are already quite general in what they represent—in some ways, they are ontology-free & simply predict the probability that some 3D position is occupied.

Such occupancy can be used for collision avoidance by any robot.

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All of this is enabled by fleet scale auto-labelling. By using video data from multiple trips in the same location, we can reconstruct the entire scene

In addition, we’re building off state-of-the-art generative modeling techniques—enabling us to predict possible outcomes given past observations, in a jointly consistent manner across multiple camera views”

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In 2021, Musk said that Dojo could likely someday reduce traffic fatalities by 90 percent and eventually it may be able to reduce them by more than 99 percent.

Last month, a report showed that Tesla had doubled its order of D1 Dojo chips for next year from Taiwan Semiconductor Manufacturing Company (TSMC), now totaling 10,000 units. According to the report, the company also plans to increase its order in 2025. Morgan Stanley also said last month that Dojo could add $500 billion to Tesla’s enterprise value.

Tesla Dojo trade secrets lawsuit officially settles out of court

What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send your tips to us at tips@teslarati.com.

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Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Tesla Diner defies the ‘Doom’ narrative: Profitable, Popular, and Here to Stay

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tesla diner
Credit: Tesla

The Tesla Diner has been subject to many points of criticism since its launch in mid-2025, and skeptics and disbelievers claim the company’s latest novel concept is on its way down, but there’s a lot of evidence to state that is not the case.

The piece cites anecdotal evidence like empty parking lots, more staff than customers during a December visit, removed novelty items, like Optimus robot popcorn service and certain menu items, the departure of celebrity chef Eric Greenspan in November 2025, slow service, high prices, and a shift in recent Google/Yelp reviews toward disappointment.

The piece frames this as part of broader Tesla struggles, including sales figures and Elon Musk’s polarizing image, calling it a failed branding exercise rather than a sustainable restaurant.

This narrative is overstated and sensationalized, and is a good representation of coverage on Tesla by today’s media.

Novelty Fade is Normal, Not Failure

Any hyped launch, especially a unique Tesla-branded destination blending dining, Supercharging, and a drive-in theater, naturally sees initial crowds taper off after the “Instagram effect” wears down.

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Tesla makes major change at Supercharger Diner amid epic demand

This is common for experiential spots in Los Angeles, especially pop-up attractions or celebrity-backed venues. The article admits early success with massive lines and social media buzz, but treats the return to normal operations as “dying down.”

In reality, this stabilization is a healthy sign of transitioning from hype-driven traffic to steady patronage.

Actual Performance Metrics Contradict “Ghost Town” Claims

  • In Q4 2025, the Diner generated over $1 million in revenue, exceeding the average McDonald’s location
  • It sold over 30,000 burgers and 83,000 fries in that quarter alone. These figures indicate a strong ongoing business, especially for a single-location prototype focused on enhancing Supercharger experiences rather than competing as a mass-market chain

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Conflicting On-the-Ground Reports

While the article, and other similar pieces, describe a half-full parking lot and sparse customers during specific off-peak visits, other recent accounts push back:

  • A January 2026 X post noted 50 of 80 Supercharger stalls were busy at 11 a.m., calling it “the busiest diner in Hollywood by close to an order of magnitude

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  • Reddit discussions around the same time describe it as not empty when locals drive by regularly, with some calling the empty narrative “disingenuous anti-Tesla slop.”

Bottom Line

The Tesla Diner, admittedly, is not the nonstop circus it was at launch–that was never sustainable or intended. But, it’s far from “dying” or an “empty pit stop.”

It functions as a successful prototype: boosting Supercharger usage, generating solid revenue, and serving as a branded amenity in the high-traffic EV market of Los Angeles.

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Tesla stands to win big from potential adjustment to autonomous vehicle limitations

Enabling scale, innovation, and profitability in a sector that is growing quickly would benefit Tesla significantly, especially as it has established itself as a leader.

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Credit: Patrick Bean | X

Tesla stands to be a big winner from a potential easing of limitations on autonomous vehicle development, as the United States government could back off from the restrictions placed on companies developing self-driving car programs.

The U.S. House Energy and Commerce subcommittee will hold a hearing later this month that will aim to accelerate the deployment of autonomous vehicles. There are several key proposals that could impact the development of self-driving cars and potentially accelerate the deployment of this technology across the country.

These key proposals include raising the NHTSA’s exemption cap from 2,500 to 90,000 vehicles per year per automaker, preempting state-level regulations on autonomous vehicle systems, and mandating NHTSA guidelines for calibrating advanced driver assistance systems (ADAS).

Congress, to this point, has been divided on AV rules, with past bills like the 2017 House-passed measure stalling in the Senate. Recent pushes come from automakers urging the Trump administration to act faster amid competition from Chinese companies.

Companies like Tesla, who launched a Robotaxi service in Austin and the Bay Area last year, and Alphabet’s Waymo are highlighted as potential beneficiaries from lighter sanctions on AV development.

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The NHTSA recently pledged to adopt a quicker exemption review for autonomous vehicle companies, and supporters of self-driving tech argue this will boost U.S. innovation, while critics are concerned about safety and job risks.

How Tesla Could Benefit from the Proposed Legislation

Tesla, under CEO Elon Musk’s leadership, has positioned itself as a pioneer in autonomous driving technology with its Full Self-Driving software and ambitious Robotaxi plans, including the Cybercab, which was unveiled in late 2024.

The draft legislation under consideration by the U.S. House subcommittee could provide Tesla with significant advantages, potentially transforming its operational and financial landscape.

NHTSA Exemption Cap Increase

First, the proposed increase in the NHTSA exemption cap from 2,500 to 90,000 vehicles annually would allow Tesla to scale up development dramatically.

Currently, regulatory hurdles limit how many fully autonomous vehicles can hit the roads without exhaustive approvals. For Tesla, this means accelerating the rollout of its robotaxi fleet, which Musk envisions as a network of millions of vehicles generating recurring revenue through ride-hailing. With Tesla’s vast existing fleet of over 6 million vehicles equipped with FSD hardware, a higher cap could enable rapid conversion and deployment, turning parked cars into profit centers overnight.

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Preempting State Regulations

A united Federal framework would be created if it could preempt State regulations, eliminating the patchwork of rules that currently complicate interstate operations. Tesla has faced scrutiny and restrictions in states like California, especially as it has faced harsh criticism through imposed testing limits.

A federal override of State-level rules would reduce legal battles, compliance costs, and delays, allowing Tesla to expand services nationwide more seamlessly.

This is crucial for Tesla’s growth strategy, as it operates in multiple markets and aims for a coast-to-coast Robotaxi network, competing directly with Waymo’s city-specific expansions.

Bringing Safety Standards to the Present Day

Innovation in the passenger transportation sector has continued to outpace both State and Federal-level legislation, which has caused a lag in the development of many things, most notably, self-driving technology.

Updating these outdated safety standards, especially waiving requirements for steering wheels or mirrors, directly benefits Tesla’s innovative designs. Tesla wanted to ship Cybertruck without side mirrors, but Federal regulations required the company to equip the pickup with them.

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Cybercab is also planned to be released without a steering wheel or pedals, and is tailored for full autonomy, but current rules would mandate human-ready features.

Streamlined NHTSA reviews would further expedite approvals, addressing Tesla’s complaints about bureaucratic slowdowns. In a letter written in June to the Trump Administration, automakers, including Tesla, urged faster action, and this legislation could deliver it.

In Summary

This legislation represents a potential regulatory tailwind for Tesla, but it still relies on the government to put forth action to make things easier from a regulatory perspective. Enabling scale, innovation, and profitability in a sector that is growing quickly would benefit Tesla significantly, especially as it has established itself as a leader.

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Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo

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

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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. 

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“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.”

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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.

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