

News
SpaceX recaps historic Starship landing in 4K as next ship readies for flight
SpaceX has published a new 4K video recapping Starship’s first intact landing after a high-altitude launch right as the company is preparing the next ship for flight.
On March 3rd, Starship serial number 10 (SN10) briefly became the first prototype to successfully launch to 10 km (6.2 mi), ‘skydive’ back to Earth, flip around, and land in one piece. Put simply, Starship SN10 made it unequivocally clear that the exotic, unproven method of landing selected by SpaceX could be made to work. Unfortunately, while Starship SN10 did land in one piece, the landing was much harder than planned.
Due to some combination of that hard landing and an apparent onboard fire that started in the last ~20 seconds of flight, SpaceX only had around six minutes to contemplate its success before Starship SN10’s propellant tanks were breached, violently depressurizing the rocket and causing a large explosion and fire.
Previously discussed on Teslarati, SpaceX CEO Elon Musk later took to Twitter to offer some educated guesses as to why Starship SN10 exploded.
“Starship SN9 ultimately failed a few seconds earlier than Starship SN8 when one of its Raptor engines failed to ignite, precluding a true flight test of the helium pressurization fix. As it turns out, Musk believes that that very fix may have doomed Starship SN10.
As Starship SN10 forged ahead past the points of failure that killed SN8 and SN9, the SpaceX CEO thinks that one or more of the vehicle’s three Raptor engines began to ingest some of that helium as they drained the methane header tank. As a result, engine thrust fell below expected values, preventing Starship SN10 from fully slowing down for a soft landing. Instead, the Starship hit the ground traveling a solid 25 mph (~10 m/s), obliterating its tiny landing legs and damaging its skirt section.”
Teslarati.com – March 10th, 2021
In other words, the losses of Starships SN8, SN9, and SN10 all share a relatively common point of failure – propulsion reliability. Technically, only Starship SN9’s failure can be blamed specifically on Raptor, one of which failed to ignite during its flip and landing maneuver. SN8 and SN10 both failed because of issues in the complex network of plumbing and pressurization systems responsible for feeding Raptors the right amount of propellant.
For SN8, the ship’s pressurization system failed to provide the necessary fuel head pressure at the last second, starving the Starship’s Raptors. SN10 ironically failed because the quick fix inspired by SN8’s failure – partially replacing a methane pressurant with helium – likely contaminated its methane fuel with helium, effectively watering down Raptor’s performance. While likely frustrating for SpaceX, the failures are still extremely valuable and loss of hardware remains a routine and intentional part of the company’s approach to iterative rocket development.
On the plus side, the FAA has already cleared SpaceX’s next Starship for flight after SN10’s momentary success and subsequent explosion. Spurred by that brief taste of total success, SpaceX wasted no time to prepare that next prototype – Starship SN11 – for flight and rolled the rocket to the launch pad mere days after SN10’s March 3rd flight. That very same day, SpaceX completed ambient pressure testing – a basic verification that Starship SN11 is leak-free.
A few days later, SN11 appeared to pass its first cryogenic proof test, replacing room-temperature gas with cryogenic liquid nitrogen. Three days after that, SpaceX attempted to put the Starship through its first triple-Raptor static fire test but appeared to suffer an abort milliseconds after a partial ignition of one or two of its three engines. Starship SN11 briefly caught fire and burned for at least 20-40 seconds after the abort, unsurprisingly triggering several days of delays. Nevertheless, if SN11 can make it through a second static fire attempt without issue on Thursday or Friday, the Starship is still well on track to take flight weeks earlier than any of its predecessors.
News
Tesla Model 3 gets perfect 5-star Euro NCAP safety rating
Tesla prides itself on producing some of the safest vehicles on the road today.

Tesla prides itself on producing some of the safest vehicles on the road today. Based on recent findings from the Euro NCAP, the 2025 Model 3 sedan continues this tradition, with the vehicle earning a 5-star overall safety rating from the agency.
Standout Safety Features
As could be seen on the Euro NCAP’s official website, the 2025 Model 3 achieved an overall score of 90% for Adult Occupants, 93% for Child Occupants, 89% for Vulnerable Road Users, and 87% for Safety Assist. This rating, as per the Euro NCAP, applies to the Model 3 Rear Wheel Drive, Long Range Rear Wheel Drive, Long Range All Wheel Drive, and Performance All Wheel Drive.
The Euro NCAP highlighted a number of the Model 3’s safety features, such as its Active Hood, which automatically lifts during collisions to mitigate injury risks to vulnerable road users, and Automatic Emergency Braking System, which now detects motorcycles through an upgraded algorithm. The Euro NCAP also mentioned the Model 3’s feature that prevents initial door opening if someone is approaching the vehicle’s blind spot.
Standout Safety Features
In a post on its official Tesla Europe & Middle East account, Tesla noted that the company is also introducing new features that make the Model 3 even safer than it is today. These include functions like head-on collision avoidance and crossing traffic AEB, as well as Child Left Alone Detection, among other safety features.
“We also introduced new features to improve Safety Assist functionality even further – like head-on collision avoidance & crossing traffic AEB – to detect & respond to potential hazards faster, helping avoid accidents in the first place.
“Lastly, we released Child Left Alone Detection – if an unattended child is detected, the vehicle will turn on HVAC & alert caregivers via phone app & the vehicle itself (flashing lights/audible alert). Because we’re using novel in-cabin radar sensing, your Tesla is able to distinguish between adult vs child – reduced annoyance to adults, yet critical safety feature for kids,” Tesla wrote in its post on X.
Below is the Euro NCAP’s safety report on the 2025 Tesla Model 3 sedan.
Euroncap 2025 Tesla Model 3 Datasheet by Simon Alvarez on Scribd
Elon Musk
USDOT Secretary visits Tesla Giga Texas, hints at national autonomous vehicle standards
The Transportation Secretary also toured the factory’s production lines and spoke with CEO Elon Musk.

United States Department of Transportation (USDOT) Secretary Sean Duffy recently visited Tesla’s Gigafactory Texas complex, where he toured the factory’s production lines and spoke with CEO Elon Musk. In a video posted following his Giga Texas visit, Duffy noted that he believes there should be a national standard for autonomous vehicles in the United States.
Duffy’s Giga Texas Visit
As could be seen in videos of his Giga Texas visit, the Transportation Secretary seemed to appreciate the work Tesla has been doing to put the United States in the forefront of innovation. “Tesla is one of the many companies helping our country reach new heights. USDOT will be right there all the way to make sure Americans stay safe,” Duffy wrote in a post on X.
He also praised Tesla for its autonomous vehicle program, highlighting that “We need American companies to keep innovating so we can outcompete the rest of the world.”
National Standard
While speaking with Tesla CEO Elon Musk, the Transportation Secretary stated that other autonomous ride-hailing companies have been lobbying for a national standard for self-driving cars. Musk shared the sentiment, stating that “It’d be wonderful for the United States to have a national set of rules for autonomous driving as opposed to 50 independent sets of rules on a state-by-state rules basis.”
Duffy agreed with the CEO’s point, stating that, “You can’t have 50 different rules for 50 different states. You need one standard.” He also noted that the Transportation Department has asked autonomous vehicle companies to submit data. By doing so, the USDOT could develop a standard for the entire United States, allowing self-driving cars to operate in a manner that is natural and safe.
News
Tesla posts Optimus’ most impressive video demonstration yet
The humanoid robot was able to complete all the tasks through a single neural network.

When Elon Musk spoke with CNBC’s David Faber in an interview at Giga Texas, he reiterated the idea that Optimus will be one of Tesla’s biggest products. Seemingly to highlight the CEO’s point, the official Tesla Optimus account on social media platform X shared what could very well be the most impressive demonstration of the humanoid robot’s capabilities to date.
Optimus’ Newest Demonstration
In its recent video demonstration, the Tesla Optimus team featured the humanoid robot performing a variety of tasks. These include household chores such as throwing the trash, using a broom and a vacuum cleaner, tearing a paper towel, stirring a pot of food, opening a cabinet, and closing a curtain, among others. The video also featured Optimus picking up a Model X fore link and placing it on a dolly.
What was most notable in the Tesla Optimus team’s demonstration was the fact that the humanoid robot was able to complete all the tasks through a single neural network. The robot’s actions were also learned directly from Optimus being fed data from first-person videos of humans performing similar tasks. This system should pave the way for Optimus to learn and refine new skills quickly and reliably.
Tesla VP for Optimus Shares Insight
In a follow-up post on X, Tesla Vice President of Optimus (Tesla Bot) Milan Kovac stated that one of the team’s goals is to have Optimus learn straight from internet videos of humans performing tasks, including footage captured in third person or by random cameras.
“We recently had a significant breakthrough along that journey, and can now transfer a big chunk of the learning directly from human videos to the bots (1st person views for now). This allows us to bootstrap new tasks much faster compared to teleoperated bot data alone (heavier operationally).
“Many new skills are emerging through this process, are called for via natural language (voice/text), and are run by a single neural network on the bot (multi-tasking). Next: expand to 3rd person video transfer (aka random internet), and push reliability via self-play (RL) in the real-, and/or synthetic- (sim / world models) world,” Kovac wrote in his post on X.
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