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SpaceX backup Starship reaches full height after nosecone installation
SpaceX has installed another Starship’s nosecone, all but completing the second full-size prototype a matter of days before the first fully-assembled Starship’s risky launch debut.
Over the last two months, SpaceX has effectively put Starship number 8 (SN8) through an almost nonstop series of tests, completing at least four separate cryogenic proof tests, four Raptor engine static fires, and much more. The company’s South Texas team have also dodged an array of technical bugs; installed, plumbed, and wired what amounts to ~40% of Starship (the nose section) while fully exposed to the coastal elements; and even narrowly avoided a potentially catastrophic failure.
In spite of the many hurdles thrown up and delays resultant, CEO Elon Musk announced earlier this week that Starship SN8 is scheduled to attempt its 15-kilometer (~50,000 ft) launch debut as early as Monday, November 30th. Musk, however, does not see success as the most probable outcome.
Why, then, push to launch Starship SN8 when, in Musk’s own words, the probability of success is as low as “33%”? As previously discussed many times in the history of Teslarati’s BFR and Starship coverage, SpaceX’s attitude towards technology development is (unfortunately) relatively unique in the aerospace industry. While once a backbone of major parts of NASA’s Apollo Program moonshot, modern aerospace companies simply do not take risks, instead choosing a systems engineering methodology and waterfall-style development approach, attempting to understand and design out every single problem to ensure success on the first try.
The result: extremely predictable, conservative solutions that take huge sums of money and time to field but yield excellent reliability and all but guarantee moderate success. SpaceX, on the other hand, borrows from early US and German rocket groups and, more recently, software companies to end up with a development approach that prioritizes efficiency, speed, and extensive testing, forever pushing the envelope and thus continually improving whatever is built.
In the early stages of any program, the results of that approach can look extremely unusual and rudimentary without context (i.e. Starhopper, above), but building and testing a minimum viable product or prototype is a very intentional foundation. Particularly at the start, those minimal prototypes are extremely cheap and almost singularly focused on narrowing a vast range of design options to something more palatable. As those prototypes rapidly teach their builders what the right and wrong questions and design decisions are, more focused and refined prototypes are simultaneously built and tested.
Done well, the agile approach is often quite similar to evolution, where prototype failures inform necessary design changes and killing off dead-end strategies, designs, and assumptions before they can be built upon. In many cases, compared to cautious waterfall-style development, it will even produce results that are both better, cheaper, and faster to realize. SpaceX’s Starship program is perhaps the most visible example in history, made all the more interesting and controversial by the fact that it’s still somewhere in between its early, chaotic development phase and a clear path to a viable product.
On the build side of things, SpaceX has created a truly incredible ad hoc factory from next to nothing, succeeding to the point that the company is now arguably testing and pushing the envelope too slowly. As of November 2020, no fewer than eight full-size Starships and the first Super Heavy booster prototype are visibly under construction. Most recently, Starship SN9 was stacked to its full height, kicking off nosecone installation while still at the build site (unlike SN8). SN10’s completed tank section is likely ready to begin flap installation within the next few days, while Starship SN11 is perhaps a week or two behind that. Additionally, large tank sections of Starships SN12, SN13, SN14, SN15, and (most likely) SN16 are already completed and have all been spotted in the last few weeks.
Some ~90% of the above work was likely started after Starship SN8 first left the factory and rolled to the launch pad on September 26th. In many regards, SN8 has been the first to reach multiple major milestones, largely explaining the relatively plodding pace of its test program compared to SN4, SN5, and SN6.
Ultimately, SN9’s imminent completion – effectively a superior, more refined copy of SN8 – means that Starship SN8’s utility to SpaceX is rapidly deteriorating. The company would almost assuredly never skip an opportunity to learn, meaning that there’s no plausible future in which SN8 testing doesn’t continue, but that doesn’t mean that SpaceX can’t turn its risk tolerance to 11. In essence, accept a 67% (or higher) chance of Starship SN8’s violent destruction but learn as much as possible in the process. As long as good data is gathered, SN8’s launch debut will be a success for Starship whether the rocket lands in one or several pieces.
News
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
