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SpaceX CEO Elon Musk talks Starship explosion: “We were too dumb”
Two days after a last-second failure caused Starship SN9 to smash into the ground and explode, SpaceX CEO Elon Musk has returned to Twitter with some harsh preliminary reactions.
Right off the bat, in response to a question about why Starships SN8 and SN9 both attempted their unsuccessful landings with only two of three available Raptor engines, Musk frankly stated that “we were too dumb.” At face value, it’s a decent question, given that there are no obvious showstoppers to explain why Starships couldn’t make the most of the redundancy their three Raptor engines can offer.
After completing an otherwise flawless 6.5 minutes launch, ascent, and belly-flop descent, Starship SN9 began a critical ~120-degree flip maneuver, sequentially igniting two Raptor engines and using that thrust to flip from a belly-down attitude to a tail-first landing configuration. Unfortunately, though the first Raptor did fire up and put in a good effort, the second engine failed to ignite, leaving the building-sized rocket to impact the ground traveling far too quickly.
Ironically, more than three years ago, Musk himself revealed in a Reddit Ask Me Anything thread that he and his engineers had decided to modify Starship’s (then known as BFS) design by adding a third Raptor to its central cluster of two engines.
“Btw, we modified the [Starship] design since IAC [2017] to add a third medium-area-ratio Raptor engine partly for that reason (lose only 1/3 thrust in engine out) and allow landings with higher payload mass for the Earth to Earth transport function.”
Elon Musk – Reddit AMA – October 2017
Primarily meant to enable more efficient landings in Earth’s atmosphere, adding a third engine to that cluster would logically increase the chances of a successful (or at least survivable) landing in the event that one engine fails. Greater thrust and an improved thrust-to-weight ratio both during launch and landing would fundamentally improve the efficiency of Starship, likely making up for most or all of the added weight.
In retrospect, it’s not entirely surprising to learn that a three-engine landing burn is probably the most logical option if three landing-class engines have been included in the design. In SpaceX and Musk’s defense, however, there are also several good reasons to use as few Raptor engines as possible.
It was foolish of us not to start 3 engines & immediately shut down 1, as 2 are needed to land— Elon Musk (@elonmusk) February 4, 2021
Throttling high-performance rocket engines is exceptionally difficult and Raptor is not yet a fully mature engine, meaning that it’s throttle capabilities are likely less than optimal. That’s relevant because the higher a rocket’s thrust-to-weight ratio during landing, the more aggressive its landings have to be. SpaceX is apparently extremely conservative with Starship in this regard, prioritizing slow, gentle landings by only using two of three available engines.
Ironically, it’s possible that that attempt at risk reduction resulted in harder landings for both Starship SN8 and SN9, as three-engine landing burns could have potentially slowed them down significantly more before impact.
At the same time, though it may have mitigated the severity of both landing failures, three-engine landing burns would not have resolved the fundamental issues that caused them. In SN8’s case, low fuel header tank pressure doomed the Starship, while SN9 is more ambiguous. Aside from the clear Raptor ignition failure, which a three-engine burn could have resolved by downselecting to two healthier engines, the one Raptor that did ignite appeared to suffer some kind of uncontained failure seconds before landing.
Impressively, despite that apparent combustion chamber or preburner failure, the engine’s landing burn seemed to continued uninterrupted until the moment of impact. As such, it’s hard to say if that lone Raptor was still producing substantial thrust or if it was in the throes of a catastrophic failure. If it could have held on for another 5-10 seconds and the third Raptor (the engine that didn’t reignite) was able to restart and perform without issue, a three-engine landing burn could have easily made SN9’s demise less violent or even have enabled a soft landing.
While a three-engine burn all the way to touchdown appears to be extremely risky or impossible for present-day Starships, Musk implied that there was nothing preventing SpaceX from reigniting all three engines during the initial flip and landing burn and using that time to determine the health of all three engines. If all three were healthy, Starship would shut down one for a soft landing. If one engine failed to restart or lost thrust shortly after ignition, the other two would already be active and able to take over.
Musk says that Starship SN10, already at the launch pad and likely days away from its first tests, will attempt to adopt that approach on an upcoming test flight expected as few as 2-3 weeks from now.
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Tesla intertwines FSD with in-house Insurance for attractive incentive
Every mile logged under FSD now carries a documented financial value—lower risk, lower cost—based on Tesla’s internal driving data rather than external crash statistics alone.
Tesla intertwined its Full Self-Driving (Supervised) suite with its in-house Insurance initiative in an effort to offer an attractive incentive to drivers.
Tesla announced that its new Safety Score 3.0 will automatically have a perfect score of 100 with every mile driven with Full Self-Driving (Supervised) enabled.
The change is designed to boost customers’ average safety scores and deliver noticeably lower monthly premiums.
The move marks the clearest link yet between Tesla’s autonomous driving technology and its proprietary insurance product. Tesla Insurance already relies on real-time vehicle data—such as acceleration, braking, following distance, and speed—to calculate a Safety Score between 0 and 100. Higher scores have long translated into cheaper rates.
Under the previous system, however, even brief manual interventions could drag down the average, frustrating owners who rely heavily on FSD. Version 3.0 eliminates that penalty for supervised autonomous miles, effectively treating FSD-driven segments as the safest possible driving behavior.
The incentive is immediate and financial. Drivers who keep FSD engaged for the majority of their trips will see their overall score rise, potentially shaving hundreds of dollars off annual premiums.
Tesla framed the update as a direct response to customer feedback, many of whom had complained that the old scoring model punished the very behavior it was meant to encourage.
For now, the program applies only to new policies in six states: Indiana, Tennessee, Texas, Arizona, Virginia, and Illinois.
Existing policyholders are not yet included, a point that drew swift questions from the Tesla community. Many owners in other states, including California and Georgia, expressed hope that the benefit would expand nationwide soon.
The announcement arrives as Tesla continues to roll out FSD Supervised updates and push for regulatory approval of more advanced autonomy. By tying insurance savings directly to FSD usage, the company is putting its own actuarial weight behind the technology’s safety claims.
Every mile logged under FSD now carries a documented financial value—lower risk, lower cost—based on Tesla’s internal driving data rather than external crash statistics alone.
Tesla has not disclosed exact premium reductions or the full rollout timeline beyond the six launch states.
Still, the message is clear: the more drivers trust FSD Supervised, the more Tesla Insurance will reward them. In an era when legacy insurers remain cautious about autonomous tech, Tesla is betting that its own data will prove the safest miles are the ones driven hands-free.
Elon Musk
Tesla finalizes AI5 chip design, Elon Musk makes bold claim on capability
The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.
Tesla has finalized its chip design for AI5, as Elon Musk confirmed today that the new chip has reached the tape-out stage, the final step before mass production.
But in a brief reply on X, Musk clarified Tesla’s AI hardware roadmap, essentially confirming that the new chip will not be utilized for being “enough to achieve much better than human safety for FSD.”
He said that AI4 is enough to do that.
Instead, the AI5 chip will be focused on Tesla’s big-time projects for the future: Optimus and supercomputer clusters.
Musk thanked TSMC and Samsung for production support, noting that AI5 could become “one of the most produced AI chips ever.” Yet, the key pivot came in his direct answer: vehicles no longer need the bleeding-edge silicon.
And thank you to @TaiwanSemi_TSC and @Samsung for your support in bringing this chip to production! It will be one of most produced AI chips ever.
— Elon Musk (@elonmusk) April 15, 2026
Existing AI4 hardware, which is already deployed in hundreds of thousands of HW4-equipped Teslas, delivers safety metrics superior to human drivers for Full Self-Driving. AI5 will instead accelerate Optimus robot development and massive Dojo-style training clusters.
The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.
Now, with AI4 proving sufficient, the company avoids costly retrofits across its fleet while redirecting next-generation compute toward higher-value applications: dexterous robots and exponential training scale.
But is it reasonable to assume AI4 enables unsupervised self-driving? Yes, but with important caveats.
On the hardware side, the claim is credible. Tesla’s FSD stack runs end-to-end neural networks trained on billions of miles of real-world data. Internal safety data reportedly shows AI4-equipped vehicles already outperforming average human drivers by a significant margin in controlled metrics (collision avoidance, reaction time, edge-case handling).
Dual-redundant AI4 chips provide ample headroom for the driving task, leaving bandwidth for future model improvements without new silicon. Musk’s assertion aligns with Tesla’s pattern of over-provisioning compute early, then optimizing ruthlessly, exactly as HW3 once sufficed before HW4 scaled further.
Optimus and our supercomputer clusters.
AI4 is enough to achieve much better than human safety for FSD.
— Elon Musk (@elonmusk) April 15, 2026
Unsupervised autonomy, meaning Level 4 or higher, is not solely a compute problem. Regulatory approval remains the primary gate.
Even if AI4 achieves “much better than human” safety statistically, agencies like the NHTSA demand exhaustive validation, liability frameworks, and public trust.
Tesla’s supervised FSD has shown rapid gains in recent versions, yet real-world edge cases, like construction zones, emergency vehicles, and adverse weather, still require driver intervention in many jurisdictions. Competitors like Waymo operate limited unsupervised fleets, but only in geofenced areas with extensive mapping. Tesla’s vision-only, fleet-scale approach is more ambitious—and harder to certify globally.
In short, Musk’s post is both pragmatic and bullish. AI4 is likely capable of unsupervised FSD from a technical standpoint. Whether regulators and consumers agree, and how quickly, will determine if Tesla’s bet pays off.
The company’s capital-efficient path keeps existing cars relevant while pouring future compute into robots. If the safety data holds, unsupervised autonomy could arrive sooner than many expect.
Elon Musk
Elon Musk signals expansion of Tesla’s unique side business
Long envisioning the Tesla Diner as more than a charging stop, Musk has clearly adopted the idea that the Supercharger and Restaurant combo is a good thing for the company to have. It’s a blend of classic American drive-in culture with futuristic Tesla flair, complete with a 1950s-inspired design, movie screens, and on-site dining.
Elon Musk has signaled an expansion of Tesla’s unique side business, something that really has nothing to do with cars or spaceships, but fans of the company have truly adopted it as just another one of its awesome ventures.
Musk confirmed on Wednesday that Tesla would build a new Diner location in Palo Alto, Northern California. After hinting last October that it “probably makes sense to open one near our Giga Texas HQ in Austin and engineering HQ in Palo Alto,” it seems one of those locations is being set into motion.
Sure
— Elon Musk (@elonmusk) April 15, 2026
Long envisioning the Tesla Diner as more than a charging stop, Musk has clearly adopted the idea that the Supercharger and Restaurant combo is a good thing for the company to have. It’s a blend of classic American drive-in culture with futuristic Tesla flair, complete with a 1950s-inspired design, movie screens, and on-site dining.
He first floated broader expansion plans shortly after the LA opening in July 2025, noting that if the prototype succeeded, Tesla would roll out similar venues in major cities worldwide and along long-distance Supercharger routes.
Earlier hints included a confirmed second site at Starbase in Texas, tied to SpaceX operations, underscoring the Diner’s role in enhancing Tesla’s ecosystem behind vehicles.
The Los Angeles location on Santa Monica Boulevard in West Hollywood has served as a high-profile test case. Opened in July 2025 at 7001 Santa Monica Blvd., it features the world’s largest urban Supercharging station with 80 V4 stalls open to all NACS-compatible EVs, over 250 dining seats, rooftop views, and 24/7 service.
The retro-futuristic building replaced a former Shakey’s and quickly became a destination. Tesla reported selling 50,000 burgers in the first 72 days—an average of over 700 daily—drawing crowds with Cybertruck-shaped packaging, breakfast extensions until 2 p.m., and movie screenings.
Palo Alto stands out as a logical next step for several reasons. As Tesla’s longstanding engineering headquarters in the heart of Silicon Valley, the city is home to thousands of Tesla employees, engineers, and executives who could benefit from a convenient, branded gathering spot.
The area boasts high EV adoption rates, dense tech talent, and heavy traffic along key corridors, making a large Supercharger-diner an ideal fit for both daily commuters and long-haul travelers.
Proximity to Stanford University and the innovation ecosystem would amplify its appeal, potentially serving as a showcase for Tesla’s vision of integrated mobility and lifestyle experiences. It could be a great way for Tesla to recruit new talent from one of the country’s best universities.
If Tesla and Musk decide to move forward with a Palo Alto diner, it would build directly on the LA prototype’s momentum while addressing Musk’s earlier calls for expansion near core Tesla hubs.
Whether it materializes as a full confirmation or evolves from these hints remains to be seen, but the pattern is clear: Tesla is testing ways to make charging stops memorable. For EV drivers and enthusiasts alike, a Silicon Valley outpost could blend cutting-edge tech with nostalgic comfort, further embedding Tesla into everyday culture. As Musk’s comments suggest, the future of the Diner looks promising.
Tesla intertwines FSD with in-house Insurance for attractive incentive
Tesla finalizes AI5 chip design, Elon Musk makes bold claim on capability
