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Tesla 3D labeling is the next big leap for Autopilot
Tesla’s 3D labeling efforts are integral to the development of its Full Self-Driving suite. Using over 2.2 billion miles of real-world driving data from its electric vehicle fleet, the electric car maker has a treasure trove of information about how human drivers behave.
Elon Musk recently confirmed that Tesla is finishing work on Autopilot core foundation code and 3D labeling, and once these are done, users can expect the electric carmaker to roll out more functionalities in a potentially more efficient manner. More advanced features such as Reverse Summon will also be rolled out.
Tesla 3D Labeling: The Next Big Thing
The Tesla CEO has tagged 3D labeling as the next big thing for the company’s efforts to achieve full self-driving. “In terms of labeling, labeling with video in all eight cameras simultaneously. This is a really, I mean in terms of labeling efficiency, arguably like a three order of magnitude improvement in labeling efficiency where Tesla vehicles use all of its eight cameras simultaneously, and that the company has improved significantly in terms of labeling efficiency,” Musk said during the Q4 2019 earnings call.
During Autonomy Day last year, Tesla’s AI head Andrej Karpathy gave the electric vehicle community an idea of how labeling is done. He said annotating data is a very expensive process that initially involved people processing data, but Tesla has also been using information from its fleet to automate the process of labeling using different mechanisms.
For example, in predicting cut-ins, Tesla taps into its fleet for data on such incidents. This information is then automatically annotated and used to train the neural network, which in turn learns from recognizable patterns. This information is then spun until the neural network is trained enough. Improvements in the neural network can then be rolled out as an update for Autopilot.
The same is true according to Karpathy when it comes to object detection. Tesla sources data from its fleet to learn more about different objects and anomalies on the road. With automated 3D labeling, the neural network can more efficiently process the information and learn even about the rarest things one can encounter on the road.
Karpathy and Musk explained how annotations from its fleet help with path prediction. Using trajectories collected from the real-world, the neural network can improve its driving behavior, say while approaching a corner that it doesn’t actively see. This smarter neural network is perfectly demonstrated by an older Model X with early-gen Autopilot negotiating a muddy rural backroad recently, after a storm in the United Kingdom.
All of these things form part of the equation to achieve Full Self-Driving capabilities. Likely through 3D labeling improvements in the past year or so, Tesla has immensely improved driving visualizations in vehicles equipped with Hardware 3, which now identify traffic lights, garbage cans, and detailed road markings, among others. Thus, Elon Musk’s explanation about rewriting the Autopilot foundational code and 3D labeling could be a way of emphasizing that Tesla owners’ investment in the company’s Full Self-Driving suite would be proven worth it and more soon.
Tesla’s FSD computer and autonomy software will transform how humans travel. The company’s vehicles will be smart enough to drive like humans and eventually make the roads a few times safer for everyone. This may also pave the way for Robotaxis and help achieve Musk’s vision of Teslas earning for their owners while they are busy with work or even while relaxing at home. Tesla Robotaxis would be an attractive form of transportation as they will be more cost-efficient compared to driving personal cars, as predicted by ARK Invest.
Autonomy As Key To Profitability
Autonomy will spell profits for Tesla, as Elon Musk explained during the company’s Q4 2019 earnings call. In order to achieve sustained profitability, Tesla needs to produce high volume units with high margins. Musk appears to consider autonomy as key to Tesla’s high margins as well.
“As we’re close to Full Self-Driving, that is just going to become more and more compelling. So that’s for our financial standpoint, that’s the real mind-blowing situation is high-volume, high-margin because of autonomy,” Musk said.
With FSD capabilities, Tesla adds more value proposition that can help sway even more customers to purchase its electric vehicles from the Model 3, Model Y, Model S, Model X, or the Cybertruck. Depending on regulations in specific regions, Tesla can tap into most of its earnings potential, which bodes well since the company has current plans to expand its presence worldwide with Gigafactories in multiple regions.
Tesla’s path to autonomy is only one of the aspects that make it the leader in the electric vehicle industry. Add to that its advancements on car connectivity and battery technology and one will complete the equation why legacy carmakers with the deepest of pockets can only watch in amazement as a relatively young electric car maker dominates the emerging EV industry.
Elon Musk
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.
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.
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.
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.
Q1 2026 Earnings Call at 4:30pm CT https://t.co/pkYIaGJ32y
— Tesla (@Tesla) April 22, 2026
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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.
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.
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.
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.
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.
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.
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.
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.
Tesla isn’t joking about building Optimus at an industrial scale: Here we go
Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues
