News
SpaceX Starship nails ‘flip’ maneuver in explosive landing video
Update: SpaceX has published a video taken near the launch pad of Starship nailing an exotic ‘flip’ maneuver shortly before a hard landing destroyed the rocket.
Both the company, test directors, and CEO Elon Musk have all made it abundantly clear that despite the explosive end, Starship SN8’s maiden flight was a spectacular success, proving that the rocket is capable of performing several previously-unproven maneuvers and surviving the associated stresses. Notably, according to tweets posted by Musk not long after, Starship SN8 performed almost perfectly, failing a soft landing (already proven by SN5 and SN6) solely because of low pressure in the rocket’s secondary ‘header’ fuel tank.

For unknown reasons, that tank or its associated plumbing were unable to maintain the pressure needed to feed Raptor with enough propellant, resulting in fuel starvation mid-burn. A lack of fuel and surplus of oxygen effectively turned the landing engine into a giant oxygen torch, melting the copper walls of its combustion chamber (hence the green plume). Had the header tank maintained the correct pressure, SN8 would have very likely landed intact (or at least had a much softer landing).
In simpler terms, it seems that Raptor isn’t to blame for Starship SN8’s failed landing and fixing a pressurization problem will be dramatically faster and easier than rectifying a rocket engine design flaw.

In perhaps the most spectacular aerospace demonstration since Falcon Heavy’s 2018 debut, SpaceX’s first full-size Starship prototype came within a hair’s breadth of sticking the landing after an otherwise successful ~12.5 km (7.8 mi) launch debut.
To quote SpaceX’s test director, heard live on the company’s official webcast moments after Starship serial number 8 (SN8) exploded on impact, “Incredible work, team!” For most, praise shortly after a rocket explosion could easily feel nonsensical, but in the context of SpaceX’s iterative approach to development, a Starship prototype failing just moments before the end of a multi-minute test can be considered a spectacular success.
Chock full of surprises, Starship SN8 ignited its three Raptor engines for the third time and lifted off at 4:45 pm CST (UTC-6) on the program’s high-altitude launch debut.

About 100 seconds after liftoff, already representing the longest-known ignition of one – let alone three – Raptor engines, one of those three engines appeared to shut down, causing the two remaining engines to gimbal wildly in an effort to retain control. Another two minutes after that, one of those Raptors also shut down, leaving one engine active. That one engine continued to burn for another minute and a half, producing just enough thrust to more or less maintain Starship SN8’s altitude at apogee while performing a bizarre horizontal slide maneuver.



Finally, at a bit less than five minutes after liftoff, Starship cut off all Raptor engines and began falling back to earth. Looking spectacularly similar to fan-made renders and CGI videos of the highly-anticipated ‘skydiver’ or ‘belly-flop’ maneuver, Starship – belly down – spent around two minutes in a rock-solid freefall, using four large flaps to maintain stability.



Around 4:52 pm, Starship SN8 performed exactly as expected, igniting one – and then two – Raptor engines while fully parallel to the ground to complete an aggressive 90-degree flip, transitioning into vertical flight for an attempted landing. Unfortunately, although it’s difficult to judge what was intentional and what was not, things began to go wrong after that point -visible in the form of one of the two reignited Raptors flashing green before shutting down.
At the same time, the plume of the lone remaining engine flashed an electric green, quite literally consuming its copper-rich internals in an unsuccessful attempt to slow Starship down. According to SpaceX CEO Elon Musk, Raptor performed “great” throughout the launch and landing attempt, with the bright-green plume likely explained by extremely oxygen-rich combustion caused by low “fuel header tank pressure.”




Regardless of the specific cause, Starship SN8 smashed into the ground around 10-20 seconds early, traveling about 30 m/s (~70 mph) too fast. To be clear, in SpaceX’s eyes, the test – primarily focused on demonstrating multi-engine ascent, freefall stability, header tank handover, engine reignition, and a flip-over maneuver – was a spectacular success, completing almost every single objective and seemingly doing so without any major issues.
Clocking in at an incredible (and unexpected) ~400 seconds (~6.5 minutes) from liftoff to explosion, it’s difficult to exaggerate the sheer quantity of invaluable data SpaceX has likely gathered from SN8’s sacrifice. Thanks to SN8’s primarily successful debut, SpaceX’s Starship test and launch facilities (minus the rocket’s remains on the landing zone) appear to be almost completely unharmed, likely requiring only minor repairs and refurbishment. Further, Starship SN9 is effectively complete and patiently waiting a few miles down the road, ready to roll to the launch pad almost as soon as SpaceX has understood the cause of SN8’s hard landing.
Stay tuned for more analysis, photos, and videos as the dust settles.
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.
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.
Investor's Corner
Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues
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
News
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.
