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Tesla’s in-house Dojo chip teased by legendary engineer ahead of AI Day

@DennisHongRobot | Twitter

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Ahead of Tesla’s AI Day scheduled for August 19th, legendary mechanical engineer Dennis Hong has teased a picture of what could be Tesla’s Dojo Chip. While Dojo is a Supercomputer that Tesla Head of Autonomy Andrej Karpathy released photographs of recently, Dojo uses an in-house chip, according to Elon Musk, along with a computer architecture optimized for Neural Net Training.

Hong, who has been a professor at the University of California, Los Angeles Samueli School of Engineering for several years, has an interest in robotic platforms, autonomous vehicles, and machine design. Interestingly, in 2011, Hong presented a TED Talk about the possibilities of making a car for blind people. During the presentation, Hong told attendees about the DARPA Urban Challenge, where he and his team of engineers developed a fully autonomous car that would automatically reach its destination without intervention. In 2007, when the Urban Challenge was completed, Hong and Co. placed third in the competition, taking home a cool $500,000 prize to continue developing self-driving techniques, among other things.

Hong dished out some added anticipation to Tesla’s AI Day event by sending out a picture of what is likely the in-house chip that Musk talked about in September 2020. “Dojo uses our own chips,” Musk said. Unlike most automakers, Tesla aims to develop most of its software and hardware in-house, especially when it comes to its autonomy projects. While Hong was unwilling to confirm or deny what his professional relationship with Tesla is, his expertise could likely have contributed to the development of Dojo and the autonomous driving project that the company has worked on for years.

Tesla has been developing its own chips since 2016, led by Jim Keller. Ultimately, Tesla wanted to design chips in-house so it knew all of the components and could likely sell the chip to other manufacturers later on. In 2019 at Autonomy Day, it unveiled Hardware 3.0, a chip that Elon Musk said was “objectively the best chip in the world.” Earlier this year, it was rumored that Tesla was working with Samsung to develop a new 5nm semiconductor chip that would assist with autonomous driving software.

Dojo is undoubtedly being developed in-house, but that does not mean Tesla will not attempt to gain the expertise and experience of some of the world’s most intelligent and accomplished engineers. With at least 14 years of experience in the field of self-driving cars, Hong may be the perfect candidate to help Tesla perfect and unveil the future of autonomous driving later this month. At AI Day, it is unknown what will be talked about or released as of right now, but there is obvious speculation that details regarding Tesla’s long-awaited Dojo could be released.

After announcing Dojo last year, Musk and Co. have remained relatively quiet regarding its development, but the company has continuously released updates to its Full Self-Driving Beta suite. Musk says updates will come “every 2 weeks on Friday” at midnight Pacific Standard Time.

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Despite Tesla’s development and incremental improvements with nearly every software update, it is nowhere near completed. Instead, the strategy was to transition Tesla’s entire FSD strategy from what Musk called ~2.5D to 4D. Essentially, Musk wanted to transition the FSD Neural Network to a video format. Adding timestamps for more accuracy, the complexity of Dojo is likely something that will not only improve the accuracy of Tesla’s vehicles when FSD and Autopilot are operational, but it also will increase performance at a more drastic rate due to the increased rate of data capture. The massive amount of data that Dojo will comprehend requires one of the world’s strongest and most robust computer systems.

While Tesla hinted toward the release of Dojo late last year, it will not be ready until late 2021 at the earliest. It is unknown if Tesla will unveil Dojo at the event or give a simple progress update.

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Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.teslarati.com

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Tesla isn’t joking about building Optimus at an industrial scale: Here we go

Tesla’s Optimus factory in Texas targets 10 million robots yearly, with 5.2 million square feet under construction.

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Tesla’s Q1 2026 Update Letter, released today, confirms that first generation Optimus production lines are now well underway at its Fremont, California factory, with a pilot line targeting one million robots per year to start. Of bigger note is a shared aerial image of a large piece of land adjacent to Gigafactory Texas, that Tesla has prominently labeled “Optimus factory site preparation.”

Permit documents show Tesla is seeking to add over 5.2 million square feet of new building space to the Giga Texas North Campus by the end of 2026, at an estimated construction investment of $5 billion to $10 billion. The longer term production target for that facility is 10 million Optimus units per year. Giga Texas already sits on 2,500 acres with over 10 million square feet of existing factory floor, and the North Campus expansion is being built to support multiple projects, including the dedicated Optimus factory, the Terafab chip fabrication facility (a joint Tesla/SpaceX/xAI venture), a Cybercab test track, road infrastructure, and supporting facilities.

Credit: TESLA

Texas makes strategic sense beyond the existing infrastructure. The state’s tax structure, lower labor costs relative to California, and the proximity to Tesla’s AI training cluster Cortex 1 and 2, both located at Giga Texas and now totaling over 230,000 H100 equivalent GPUs, means the Optimus software stack and the factory producing the hardware will share the same campus. Tesla’s Q1 report also confirmed completion of the AI5 chip tape out in April, the inference processor designed specifically to power Optimus units in the field.

As Teslarati reported, the Texas facility is intended to house Optimus V4 production at full scale. Musk told the World Economic Forum in January that Tesla plans to sell Optimus to the public by end of 2027 at a price between $20,000 and $30,000, stating, “I think everyone on earth is going to have one and want one.” He has previously pegged long term demand for general purpose humanoid robots at over 20 billion units globally, citing both consumer and industrial use cases.

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Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues

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Credit: Tesla

Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.

The earnings results come after Tesla reported a miss on vehicle deliveries for the first quarter, delivering 358,023 vehicles and building 408,386 cars during the three-month span.

As Tesla transitions more toward AI and sees itself as less of a car company, expectations for deliveries will begin to become less of a central point in the consensus of how the quarter is perceived.

Nevertheless, Tesla is leaning on its strong foundation as a car company to carry forward its AI ambitions. The first quarter is a good ground layer for the rest of the year.

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Tesla Q1 2026 Earnings Results

Tesla’s Earnings Results are as follows:

  • Non-GAAP EPS – $0.41 Reported vs. $0.36 Expected
  • Revenues – $22.387 billion vs. $22.35 billion Expected
  • Free Cash Flow – $1.444 billion
  • Profit – $4.72 billion

Tesla beat analyst expectations, so it will be interesting to see how the stock responds. IN the past, we’ve seen Tesla beat analyst expectations considerably, followed by a sharp drop in stock price.

On the same token, we’ve seen Tesla miss and the stock price go up the following trading session.

Tesla will hold its Q1 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.

You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.

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SpaceX is following in Tesla’s footsteps in a way nobody expected

In the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.

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Credit: Grok

When Elon Musk founded Tesla in 2003, it was a plucky electric car startup betting everything on lithium-ion batteries and a niche luxury Roadster.

Two decades later, Tesla is far more than a car company. Its valuation increasingly hinges on Full Self-Driving software, the Optimus humanoid robot, the Robotaxi program, and the Dojo supercomputer cluster purpose-built for AI training.

Musk has repeatedly described Tesla as an AI and robotics company that happens to sell vehicles. The cars, in this view, are merely the first scalable platform for real-world AI.

Now, SpaceX is tracing an eerily similar path, only faster and in a direction almost no one anticipated. Founded in 2002 to make spaceflight routine and eventually multiplanetary, SpaceX spent its first two decades perfecting reusable rockets, landing Falcon 9 boosters, and building the Starlink megaconstellation.

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Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry

It was an engineering and manufacturing powerhouse, not a software play. Yet, in the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.

The xAI deal, announced on February 2, was structured as an all-stock transaction that valued the combined entity at roughly $1.25 trillion—SpaceX at $1 trillion and xAI at $250 billion. In a memo to employees, Musk framed the merger as the creation of “the most ambitious, vertically-integrated innovation engine on (and off) Earth.”

The new SpaceX now owns Grok, the large language model family that powers the chatbot of the same name, along with xAI’s massive training infrastructure. More importantly, it has a declared mission to move AI compute off-planet.

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Earth-based data centers are hitting hard limits on power, cooling, and land. Musk’s solution is orbital data centers, or constellations of solar-powered satellites that act as supercomputers in the sky.

SpaceX has already asked regulators for permission to launch up to one million such satellites. Starship, the company’s fully reusable heavy-lift vehicle, is the only rocket capable of delivering the necessary mass at the required cadence.

Each orbital node would enjoy near-constant sunlight, vast radiator surfaces for passive cooling, and zero terrestrial real-estate costs. Musk has predicted that within two to three years, space-based AI inference and training could become cheaper than anything possible on the ground.

This is not a side project; it is the strategic centerpiece Musk has envisioned for SpaceX. Starlink already provides the global low-latency backbone; next-generation V3 satellites will carry onboard AI accelerators. Rockets deliver the hardware, while AI optimizes every aspect of launch, landing, and constellation management.

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The feedback loop is self-reinforcing, too. Better AI makes better rockets, which launch more AI infrastructure.

Just yesterday, on April 21, SpaceX doubled down.

It secured an option to acquire Cursor—the fast-growing AI coding tool beloved by software engineers—for $60 billion later this year, or pay a $10 billion partnership fee if the full deal does not close.

Cursor’s models already help engineers write code at superhuman speed. Pairing that technology with SpaceX’s Colossus-scale training clusters (the same ones powering Grok) positions the company to dominate AI developer tools, much as Tesla dominates autonomous driving software.

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Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO

The parallels with Tesla are striking. Both companies began in a single, capital-intensive sector: Tesla with EVs, SpaceX with launch vehicles. Both used early hardware success to fund AI at scale. Tesla’s Dojo supercomputers train neural nets on billions of miles of real-world driving data; SpaceX now trains on telemetry from thousands of orbital assets and re-entries.

Tesla’s FSD chip runs inference on cars; SpaceX’s future satellites will run inference in orbit.

Tesla’s Optimus robot will work in factories; SpaceX envisions lunar factories manufacturing more AI satellites, eventually using electromagnetic mass drivers to fling them into deep space.

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Critics once dismissed Musk’s multi-company empire as unfocused. The 2026 moves reveal the opposite: deliberate convergence.

SpaceX is no longer merely a rocket company that sells internet from space. It is an AI company whose competitive moat is literal orbital infrastructure and the only vehicle that can service it at scale. The forthcoming IPO, expected later this year, will almost certainly be pitched not as a space play but as the purest bet on AI infrastructure the public market has ever seen.

Whether the orbital data-center vision survives regulatory scrutiny, astronomical concerns about light pollution, or the sheer engineering challenge remains to be seen.

Yet the strategic direction is unmistakable. Just as Tesla proved that software and AI could redefine the century-old automobile, SpaceX is proving that rockets are merely the delivery mechanism for the next great computing platform—one that floats above the clouds, powered by the sun, and limited only by the physics of orbit.

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In that unexpected sense, history is repeating. Tesla stopped being “just a car company” years ago. SpaceX has now stopped being “just a rocket company.” Both are becoming something far larger: AI powerhouses with hardware moats so deep that competitors will need their own reusable megaconstellations to keep up.

The age of terrestrial AI is ending. The age of space-based AI is beginning—and SpaceX is building the launchpad.

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