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SpaceX CEO Elon Musk says major Starship engine bug is fixed as Raptor testing continues

Starhopper awaits its first truly flightworthy Raptor as CEO Elon Musk says SpaceX may have solved the technical bug delaying hop tests. (NASASpaceflight - bocachicagal, SpaceX)

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SpaceX CEO Elon Musk has revealed the latest official photo of the company’s Raptor engine in action and indicated that a major technical issue with vibration appears to have been solved, hopefully paving the way for Starhopper’s first untethered flights.

Partly due to Musk’s own involvement in the program, SpaceX’s propulsion development team have struggled to get any single Raptor engine to survive more than 50-100 seconds of cumulative test fires. According to information from sources familiar with the program, Musk has enforced an exceptionally hardware-rich development program for the first full-scale Raptor engines to such an extent that several have been destroyed so completely that they could barely be used to inform design optimization work. Although likely more strenuous and inefficient than it needed to be, the exceptionally hardware-rich test program appears to have begun to show fruit, with the sixth engine built (SN06) passing its first tests without exhibiting signs of a problem that has plagued most of the five Raptors that came before it.

Resonance: not even once

In his tweet, Musk cryptically noted that a “600 Hz Raptor vibration problem” appears to have been fixed as of SN06’s first few static fire tests since arriving in McGregor, Texas. More likely than not, the self-taught SpaceX executive is referring to the hell that is mechanical resonance in complex machines and structures. Shown below, the Tacoma Narrows Bridge’s 1940 collapse – quite possibly the single most famous civil engineering failure of all time – is an iconic example of the unintuitive power of resonance in complex systems.

An excellent overview of the challenges and fairly young history of mechanical resonance in modern engineering.

When it was inaugurated, the first Tacoma Narrows Bridge was one of the longest suspension bridges ever built and implemented new techniques and technologies that had never been tried at such a large scale. As Grady (Practical Engineer) aptly notes, mechanical resonance – in this case, triggered by consistent winds running through the Puget Sound – simply wasn’t something that period engineers knew they had to worry about. When rapidly pushing the envelope of engineering and construction, the chances of discovering entirely novel failure modes also increases – it’s simply one of the costs of extreme innovation.

The first finalized Raptor engine (SN01) completed a successful static fire debut on the evening of February 3rd. (SpaceX)
Just five days after its first ignition, SpaceX successfully tested Raptor SN01 at more than twice the thrust of Merlin 1D. (SpaceX)
The latest official photo of Raptor testing in McGregor. This engine is likely SN06, the sixth Raptor produced in 2019. (SpaceX/Elon Musk)

Luckily for SpaceX, the company doesn’t have to clash with the immense challenge of testing something as large, complex, and expensive as a suspension bridge. Raptor, Starship, and Super Heavy need not necessarily be perfect on SpaceX’s first try, whereas civil bridges must essentially be flawless on the first try, despite being one of a kind. This is why SpaceX has been chewing through an average of one Raptor engine per month since February 2019 – by testing engines to destruction and aggressively comparing engineering expectations with observed behavior and post-test hardware conditions, rapid progress can (theoretically) be made.

Instead of spending another year or more analyzing models and testing subscale engines and components, SpaceX dove into integrated testing of a sort of minimum-viable-product Raptor design, accepting that the path to a flightworthy, finalized design would likely be paved with one or several dozen destroyed engines. According to Musk, the biggest pressing design deficiency involved a mode of mechanical resonance that may or may not have been predicted over the course of the design process. Dealing with unprecedented conditions, it’s not particularly surprising that some sort of new resonance mode was discovered in Raptor.

For the time being, SpaceX continues to work around the clock to build its first two orbital Starship prototypes (one in Texas, one in Florida), while also outfitting Starhopper and completing any possible engine-less tests in anticipation of the first flightworthy Raptor’s arrival. If Musk’s early analysis proves correct and Raptor SN06 makes it through lengthier static fire tests unscathed over the next week or so, the engine could potentially be delivered to Boca Chica as early as mid-July.

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Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

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Credit: TESLARATI

Turn-by-turn navigation is not new technology.

For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.

Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.

Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much

Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.

Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.

Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes,Ā we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.

But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.

This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.

More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.

It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?

Multiple Data Sources

First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.

Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.

Persistent Learning

FSD seems to struggle with persistent learning from driver interventions.

Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.

This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.

I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.

Reasoning, Scaling, and Intuition

Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.

Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.

Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.

Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.

Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.

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Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK

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A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”

Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:

“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”

The Cybertruck in question was, according to theĀ BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.

The Greater Manchester Police Department then added:

“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”

The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.

Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.

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Apple is developing the missing link for Tesla to get CarPlay: report

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Credit: Michał Gapiński/YouTube

A new report claims that Apple is in the process of developing what would be the missing link for Tesla to get CarPlay.

Apple and Tesla have been reportedly working together for some time to give Tesla owners the opportunity to utilize CarPlay within their vehicles. While many owners are more than happy with Tesla’s in-house UI, which is seamless, effective, and smooth, some still want CarPlay, which does have its advantages.

A report fromĀ 9to5Mac now states that a new CarPlay technology that was highlighted during the Worldwide Developers Conference (WWDC) would potentially be the bridge between Tesla and Apple. With the addition of a feature known as “Route Sharing,” which gives a navigation app the ability to share routing data with the vehicle, Tesla would be able to launch CarPlay in its vehicles, the report states.

CarPlay has not been a priority for Tesla because it has done extremely well with its in-house UI, but some drivers are just used to it. Additionally, it could improve Tesla’s subpar Navigation or offer improved app capabilities, especially with iMessage.

Route Sharing is an intended addition to CarPlay’s iteration in iOS 26.4, which was released in March:

The addition of CarPlay would undoubtedly be welcome, but at the same time, it seems like Tesla realizes it is not of the utmost priority. There are so many things that Tesla is working on currently within its own vehicles, especially attempting to solve self-driving.

Back in February,Ā Bloomberg had reported that Tesla was still working on bringing CarPlay to its vehicles, but it had not due to app compatibility issues and incredibly low adoption rates of iOS 26.

This bottleneck could buy Tesla the proper amount of time to develop CarPlay for its vehicles. It would be a welcome addition, and could be brought on with either the Summer or Fall 2026 Software Updates.

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