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SpaceX rocket catch simulation raises more questions about concept
CEO Elon Musk has published the first official visualization of what SpaceX’s plans to catch Super Heavy boosters might look like in real life. However, the simulation he shared raises just as many questions as it answers.
Since at least late 2020, SpaceX CEO Elon Musk has been floating the idea of catching Starships and Super Heavy boosters out of the sky as an alternative to having the several-dozen-ton steel rockets use basic legs to land on the ground. This would be a major departure from SpaceX’s highly successful Falcon family, which land on a relatively complex set of deployable legs that can be retracted after most landings. The flexible, lightweight structures have mostly been reliable and easily reusable but Falcon boosters occasionally have rough landings, which can use up disposable shock absorbers or even damage the legs and make boosters hard to safely recover and slower to reuse.
As a smaller rocket, Falcon boosters have to be extremely lightweight to ensure healthy payload margins and likely weigh about 25-30 tons empty and 450 tons fully fueled – an excellent mass ratio for a reusable rocket. While it’s still good to continue that practice of rigorous mass optimization with Starship, the vehicle is an entirely different story. Once plans to stretch the Starship upper stage’s tanks and add three more Raptors are realized, it’s quite possible that Starship will be capable of launching more than 200 tons (~440,000 lb) of payload to low Earth orbit (LEO) with ship and booster recovery.
One might think that SpaceX, with the most capable rocket ever built potentially on its hands, would want to take advantage of that unprecedented performance to make the rocket itself – also likely to be one of the most complex launch vehicles ever – simpler and more reliable early on in the development process. Generally speaking, that would involve sacrificing some of its payload capability and adding systems that are heavier but simpler and more robust. Once Starship is regularly flying to orbit and gathering extensive flight experience and data, SpaceX might then be able refine the rocket, gradually reducing its mass and improving payload to orbit by optimizing or fully replacing suboptimal systems and designs.
Instead, SpaceX appears to be trying to substantially optimize Starship before it’s attempted a single orbital launch. The biggest example is Elon Musk’s plan to catch Super Heavy boosters – and maybe Starships, too – for the sole purpose of, in his own words, “[saving] landing leg mass [and enabling] immediate reflight of [a giant, unwieldy rocket].” Musk, SpaceX executives, or both appear to be attempting to refine a rocket that has never flown. Further, based on a simulation of a Super Heavy “catch” Musk shared on January 20th, all that oddly timed effort may end up producing a solution that’s actually worse than what it’s trying to replace.
Based on the simulated telemetry shown in the visualization, Super Heavy’s descent to the landing zone appears to be considerably gentler than the ‘suicide burn’ SpaceX routinely uses on Falcon. By decelerating as quickly as possible and making landing burns as short as possible, Falcon saves a considerable amount of propellant during recovery – extra propellant that, if otherwise required, would effectively increase Falcon’s dry mass and decrease its payload to orbit. In the Super Heavy “catch” Musk shared, the booster actually appears to be landing – just on an incredibly small patch of steel on the tower’s ‘Mechazilla’ arms instead of a concrete pad on the ground.
Aside from a tiny bit of lateral motion, the arms appear motionless during the ‘catch,’ making it more of a landing. Further, Super Heavy is shown decelerating rather slowly throughout the simulation and appears to hover for almost 10 seconds near the end. That slow, cautious descent and even slower touchdown may be necessary because of how incredibly accurate Super Heavy has to be to land on a pair of hardpoints with inches of lateral margin for error and maybe a few square feet of usable surface area. The challenge is a bit like if SpaceX, for some reason, made Falcon boosters land on two elevated ledges about as wide as car tires. Aside from demanding accurate rotational control, even the slightest lateral deviation would cause the booster to topple off the pillars and – in the case of Super Heavy – fall about a hundred feet onto concrete, where it would obviously explode.
What that slow descent and final hover mean is that the Super Heavy landing shown would likely cost significantly more delta V (propellant) than a Falcon-style suicide burn. Propellant has mass, so Super Heavy would likely need to burn at least 5-10 tons more to carefully land on arms that aren’t actively matching the booster’s position and velocity. Ironically, SpaceX could probably quite easily add rudimentary, fixed legs – removing most of the bad aspects of Falcon legs – to Super Heavy with a mass budget of 10 tons. But even if SpaceX were to make those legs as simple, dumb, and reliable as physically possible and they wound up weighing 20 tons total, the inherent physics of rocketry mean that adding 20 tons to Super Heavy’s likely 200-ton dry mass would only reduce the rocket’s payload to orbit by about 3-5 tons or 1-3%.
Further, per Musk’s argument that landing on the arms would enhance the speed of reuse, it’s difficult to see how landing Super Heavy or Starship in the exact same corridor – but on the ground instead of on the arms – would change anything. If Super Heavy is accurate enough to land on a few square meters of steel, it must inherently be accurate enough to land within the far larger breadth of those arms. The only process landing on the arms would clearly remove is reattaching the arms to a landed booster or ship, which it’s impossible to imagine would save more than a handful of minutes or maybe an hour of work. SpaceX’s Falcon booster turnaround record is currently 27 days, so it’s even harder to imagine why SpaceX would be worrying about cutting minutes or a few hours off of the turnaround and reuse of a rocket that has never even performed a full static fire test – let alone attempted an orbital-class launch, reentry, or landing.
Put simply, while Starbase’s launch tower arms will undoubtedly be useful for quickly lifting and stacking Super Heavy and Starship, it’s looking more and more likely that using those arms as a landing platform will, at best, be an inferior alternative to basic Falcon-style landings. More importantly, even if everything works perfectly, the arms actually cooperate with boosters to catch them, and it’s possible for Super Heavy to avoid hovering and use a more efficient suicide burn, the apparent best-case outcome of all that effort is marginally faster reuse and perhaps a 5% increase in payload to orbit. Only time will tell if such a radical change proves to be worth such marginal benefits.
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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
