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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 Full Self-Driving v14.2.2.5 might be the most confusing release ever
With each Full Self-Driving release, I am realistic. I know some things are going to get better, and I know some things will regress slightly. However, these instances of improvements are relatively mild, as are the regressions. Yet, this version has shown me that it contains extremes of both.
Tesla Full Self-Driving v14.2.2.5 hit my car back on Valentine’s Day, February 14, and since I’ve had it, it has become, in my opinion, the most confusing release I’ve ever had.
With each Full Self-Driving release, I am realistic. I know some things are going to get better, and I know some things will regress slightly. However, these instances of improvements are relatively mild, as are the regressions. Yet, this version has shown me that it contains extremes of both.
It has been about three weeks of driving on v14.2.2.5; I’ve used it for nearly every mile traveled since it hit my car. I’ve taken short trips of 10 minutes or less, I’ve taken medium trips of an hour or less, and I’ve taken longer trips that are over 100 miles per leg and are over two hours of driving time one way.
These are my thoughts on it thus far:
Speed Profiles Are a Mixed Bag
Speed Profiles are something Tesla seems to tinker with quite frequently, and each version tends to show a drastic difference in how each one behaves compared to the previous version.
I do a vast majority of my FSD travel using Standard and Hurry modes, although in bad weather, I will scale it back to Chill, and when it’s a congested city on a weekend or during rush hour, I’ll throw it into Mad Max so it takes what it needs.
Early on, Speed Profiles really felt great. This is one of those really subjective parts of the FSD where someone might think one mode travels too quickly, whereas another person might see the identical performance as too slow or just right.
To me, I would like to see more consistency from release to release on them, but overall, things are pretty good. There are no real complaints on my end, as I had with previous releases.
In a past release, Mad Max traveled under the speed limit quite frequently, and I only had that experience because Hurry was acting the same way. I’ve had no instances of that with v14.2.2.5.
Strange Turn Signal Behavior
This is the first Full Self-Driving version where I’ve had so many weird things happen with the turn signals.
Two things come to mind: Using a turn signal on a sharp turn, and ignoring the navigation while putting the wrong turn signal on. I’ve encountered both things on v14.2.2.5.
On my way to the Supercharger, I take a road that has one semi-sharp right-hand turn with a driveway entrance right at the beginning of the turn.
Only recently, with the introduction of v14.2.2.5, have I had FSD put on the right turn signal when going around this turn. It’s obviously a minor issue, but it still happens, and it’s not standard practice:
How can we get Full Self-Driving to stop these turn signals?
There’s no need to use one here; the straight path is a driveway, not a public road. The right turn signal here is unnecessary pic.twitter.com/7uLDHnqCfv
— TESLARATI (@Teslarati) February 28, 2026
When sharing this on X, I had Tesla fans (the ones who refuse to acknowledge that the company can make mistakes) tell me that it’s a “valid” behavior that would be taught to anyone who has been “professionally trained” to drive.
Apparently, if you complain about this turn signal, you are also claiming you know more than Tesla engineers…okay.
Nobody in their right mind has ever gone around a sharp turn when driving their car and put on a signal when continuing on the same road. You would put a left turn signal on to indicate you were turning into that driveway if that’s what your intention was.
Like I said, it’s a totally minor issue. However, it’s not really needed, and nor is it normal. If I were in the car with someone who was taking a simple turn on a road they were traveling, and they signaled because the turn was sharp, I’d be scratching my head.
I’ve also had three separate instances of the car completely ignoring the navigation and putting on a signal that is opposite to what the routing says. Really quite strange.
Parking Performance is Still Underwhelming
Parking has been a complaint of mine with FSD for a long time, so much so that it is pretty rare that I allow the vehicle to park itself. More often than not, it is because I want to pick a spot that is relatively isolated.
However, in the times I allow it to pull into a spot, it still does some pretty head-scratching things.
Recently, it tried to back into a spot that was ~60% covered in plowed snow. The snow was piled about six feet high in a Target parking lot.
A few days later, it tried backing into a spot where someone failed the universal litmus test of returning their shopping cart. Both choices were baffling and required me to manually move the car to a different portion of the lot.
I used Autopark on both occasions, and it did a great job of getting into the spot. I notice that the parking performance when I manually choose the spot is much better than when the car does the entire parking process, meaning choosing the spot and parking in it.
It’s Doing Things (For Me) It’s Never Done Before
Two things that FSD has never done before, at least for me, are slow down in School Zones and avoid deer. The first is something I usually take over manually, and the second I surprisingly have not had to deal with yet.
I had my Tesla slow down at a school zone yesterday for the first time, traveling at 20 MPH and not 15 MPH as the sign suggested, but at the speed of other cars in the School Zone. This was impressive and the first time I experienced it.
I would like to see this more consistently, and I think School Zones should be one of those areas where, no matter what, FSD will only travel the speed limit.
Last night, FSD v14.2.2.5 recognized a deer in a roadside field and slowed down for it:
🚨 Cruising home on a rainy, foggy evening and my Tesla on Full Self-Driving begins to slow down suddenly
FSD just wanted Mr. Deer to make it home to his deer family ❤️ pic.twitter.com/cAeqVDgXo5
— TESLARATI (@Teslarati) March 4, 2026
Navigation Still SUCKS
Navigation will be a complaint until Tesla proves it can fix it. For now, it’s just terrible.
It still has not figured out how to leave my neighborhood. I give it the opportunity to prove me wrong each time I leave my house, and it just can’t do it.
It always tries to go out of the primary entrance/exit of the neighborhood when the route needs to take me left, even though that exit is a right turn only. I always leave a voice prompt for Tesla about it.
It still picks incredibly baffling routes for simple navigation. It’s the one thing I still really want Tesla to fix.
Investor's Corner
Tesla gets tip of the hat from major Wall Street firm on self-driving prowess
“Tesla is at the forefront of autonomous driving, supported by a camera-only approach that is technically harder but much cheaper than the multi-sensor systems widely used in the industry. This strategy should allow Tesla to scale more profitably compared to Robotaxi competitors, helped by a growing data engine from its existing fleet,” BoA wrote.
Tesla received a tip of the hat from major Wall Street firm Bank of America on Wednesday, as it reinitiated coverage on Tesla shares with a bullish stance that comes with a ‘Buy’ rating and a $460 price target.
In a new note that marks a sharp reversal from its neutral position earlier in 2025, the bank declared Tesla’s Full Self-Driving (FSD) technology the “leading consumer autonomy solution.”
Analysts highlighted Tesla’s camera-only architecture, known as Tesla Vision, as a strategic masterstroke. While technically more challenging than the multi-sensor setups favored by rivals, the vision-based approach is dramatically cheaper to produce and maintain.
This cost edge, combined with Tesla’s rapidly expanding real-world data engine, positions the company to scale robotaxis far more profitably than competitors, BofA argues in the new note:
“Tesla is at the forefront of autonomous driving, supported by a camera-only approach that is technically harder but much cheaper than the multi-sensor systems widely used in the industry. This strategy should allow Tesla to scale more profitably compared to Robotaxi competitors, helped by a growing data engine from its existing fleet.”
The bank now attributes roughly 52% of Tesla’s total valuation to its Robotaxi ambitions. It also flagged meaningful upside from the Optimus humanoid robot program and the fast-growing energy storage business, suggesting the auto segment’s recent headwinds, including expired incentives, are being eclipsed by these higher-margin opportunities.
Tesla’s own data underscores exactly why Wall Street is waking up to FSD’s potential. According to Tesla’s official safety reporting page, the FSD Supervised fleet has now surpassed 8.4 billion cumulative miles driven.
Tesla FSD (Supervised) fleet passes 8.4 billion cumulative miles
That total ballooned from just 6 million miles in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and a staggering 4.25 billion in 2025 alone. In the first 50 days of 2026, owners added another 1 billion miles — averaging more than 20 million miles per day.
This avalanche of real-world, camera-captured footage, much of it on complex city streets, gives Tesla an unmatched training dataset. Every mile feeds its neural networks, accelerating improvement cycles that lidar-dependent rivals simply cannot match at scale.
Tesla owners themselves will tell you the suite gets better with every release, bringing new features and improvements to its self-driving project.
The $460 target implies roughly 15 percent upside from recent trading levels around $400. While regulatory and safety hurdles remain, BofA’s endorsement signals growing institutional conviction that Tesla’s data advantage is not hype; it’s a tangible moat already delivering billions of miles of proof.
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Tesla to discuss expansion of Samsung AI6 production plans: report
Tesla has reportedly requested an additional 24,000 wafers per month, which would bring total production capacity to around 40,000 wafers if finalized.
Tesla is reportedly discussing an expansion of its next-generation AI chip supply deal with Samsung Electronics.
As per a report from Korean industry outlet The Elec, Tesla purchasing executives are reportedly scheduled to meet Samsung officials this week to negotiate additional production volume for the company’s upcoming AI6 chip.
Industry sources cited in the report stated that Tesla is pushing to increase the production volume of its AI6 chip, which will be manufactured using Samsung’s 2-nanometer process.
Tesla previously signed a long-term foundry agreement with Samsung covering AI6 production through December 31, 2033. The deal was reportedly valued at about 22.8 trillion won (roughly $16–17 billion).
Under the existing agreement, Tesla secured approximately 16,000 wafers per month from the facility. The company has reportedly requested an additional 24,000 wafers per month, which would bring total production capacity to around 40,000 wafers if finalized.
Tesla purchasing executives are expected to discuss detailed supply terms during their visit to Samsung this week.
The AI6 chip is expected to support several Tesla technologies. Industry sources stated that the chip could be used for the company’s Full Self-Driving system, the Optimus humanoid robot, and Tesla’s internal AI data centers.
The report also indicated that AI6 clusters could replace the role previously planned for Tesla’s Dojo AI supercomputer. Instead of a single system, multiple AI6 chips would be combined into server-level clusters.
Tesla’s semiconductor collaboration with Samsung dates back several years. Samsung participated in the design of Tesla’s HW3 (AI3) chip and manufactured it using a 14-nanometer process. The HW4 chip currently used in Tesla vehicles was also produced by Samsung using a 5-nanometer node.
Tesla previously planned to split production of its AI5 chip between Samsung and TSMC. However, the company reportedly chose Samsung as the primary partner for the newer AI6 chip.
Tesla Full Self-Driving v14.2.2.5 might be the most confusing release ever
Tesla gets tip of the hat from major Wall Street firm on self-driving prowess
