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SpaceX’s Starship rocket just breathed fire for the first time (and survived)
SpaceX’s Starship rocket is a step closer to flight after the fourth full-scale prototype successfully fired up its high-performance Raptor engine for the first time and survived the ordeal.
By far the biggest technical milestone SpaceX’s Starship program has passed since its creation, the Starship serial number 4 (SN4) prototype’s May 5th static fire was just the latest in a series of rapid-fire tests completed over the last several days. The ship’s journey began back in late March when SpaceX technicians began integrating the first sections of its steel hull. Less than a month later, SpaceX officially completed Starship SN4’s tank and engine section – missing only a nosecone and header tanks – and rolled the rocket to the launch and test pad on April 23rd.
Barely two days later, Starship SN4 entered the testing phase, passing what CEO Elon Musk described as an “ambient pressure test” used to verify the structural integrity of the rocket’s propellant tanks with harmless nitrogen gas. Less than a day after that pressure test was completed, SpaceX kicked off a “cryogenic proof test” with the Starship – the same test that destroyed three full-scale prototypes in the five months prior.
In the early morning of April 26th, Starship SN4 thus became the first full-scale prototype to pass (and survive) a cryogenic proof test, in which the ship’s normal liquid oxygen and methane was replaced with similarly frigid but non-explosive liquid nitrogen. According to Musk, SN4 was only pressurized to 4.9 bar (~70 psi), quite a distance away from the ~8.5 bar needed for safe orbital flight but reportedly more than enough to perform a small flight test.
Of course, Starship SN4 would first have to complete a bevy of additional tests – all arguably riskier than the cryogenic proof test it was the first to pass. That second, more challenging phase of testing began six days later on May 2nd.
After some limited fueling effectively marking Starship SN4’s first partial wet dress rehearsal (WDR), SpaceX aborted the first test attempt on May 2nd. On May 3rd, Starship SN4 was successfully loaded with propellant once more and wound up performing what is known as a spin prime test with its lone Raptor engine. Over the course of a few hours, SpaceX then recycled (and rechilled) the ship’s methane propellant and successfully performed a preburner test, igniting two gas generators that spin up Raptor’s turbines and eventually mix in the combustion chamber.
Less than 24 hours later, SpaceX turned Starship SN4 around for the grand finale – an actual Raptor ignition test, also known as a static fire. Per NASASpaceflight’s unofficial livestream of the event, made possible thanks to local resident BocaChicaGal, Starship ignited its Raptor engine – a historic first for the launch vehicle program – at 8:57pm CDT on May 5th (01:57 UTC, May 6). Musk confirmed just a few hours after that the ignition test – lasting about 3 seconds – had been completed successfully.
With that crucial milestone now behind it, Starship SN4 – perhaps pending an additional test or two – should effectively be clear to begin preparations for a 150m (500 ft) hop test later this month. Almost entirely contingent upon receiving a Federal Aviation Administration (FAA) launch license, that process could be finished tomorrow or take several days – or even weeks – to complete. Starship already has landing legs installed and wont need a nosecone for such a short and slow hop, but SpaceX may also need to install some kind of attitude control system (likely gas thrusters) before SN4 can safely fly.
Stay tuned for updates as we learn more about when a full-scale SpaceX Starship is scheduled to fly for the first time.
Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
