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SpaceX Mars landing expert talks Starship recovery challenges in new interview

Starship Mk1 is in the late stages of assembly and integration at SpaceX's Boca Chica, Texas facilities. (SpaceX)

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Formerly responsible for developing Falcon 9 (and Heavy) into the routinely-landing reusable rocket it is today, senior SpaceX engineer Lars Blackmore says he now has one primary focus: figuring out how to land Starship on Earth, the Moon, and Mars.

A graduate of University of Cambridge and MIT, the latter of which interviewed him on October 23rd for an “Alumni Stories” blog, Lars Blackmore has become famous for his groundbreaking work in guidance, navigation, and control (GNC). After graduating with honors from Cambridge and earning a PhD from MIT, Dr. Blackmore joined NASA in 2007 and immersed himself in “precision Mars landing”, part of a more general focus on figuring out how to autonomously control vehicles in uncertain conditions.

In his last year at NASA, Blackmore co-invented an algorithm known as G-FOLD (Guidance for Fuel Optimal Large Divert) that should theoretically enable precision landings on Mars, improving the state of the art by two full orders of magnitude (+/- 10 km to +/- 100 m). In 2011, he departed NASA and joined SpaceX, where he lead the development of the GNC technology needed to successfully and reliably recovery Falcon 9 boosters. Although the same could be said for any number of critical, groundbreaking systems that had to be developed, the onboard software that autonomously guides Falcon 9 landings on the fly is one of many things that booster recovery and reuse would be wholly impossible without.

After numerous failed attempts, all part SpaceX’s preferred learning process, Falcon 9 successfully landed for the first time on December 21st, 2015. As they say, the rest is history: in the roughly four years since that milestone landing, SpaceX has successfully completed 57 orbital launches, recovered boosters 43 more times, and reused flight-proven boosters on 23 launches. Since that first success, more than half of all SpaceX launches have been followed by a successful booster landing (or two).

Three of SpaceX’s thrice-flown Falcon 9 boosters are pictured here: B1046, B1048, and B1049. (Tom Cross & Pauline Acalin)

Back to Mars

In 2018, Dr. Blackmore officially took on a new full-time role as SpaceX’s Principal Mars Landing Engineer. As the namesake suggests, this meant handing (now semi-routine) Falcon 9 and Heavy GNC development to a strong team and beginning to tackle an array of new problems that will need to be solved for SpaceX to reach the Moon, Mars, and beyond.

Following radical design modifications made to Starship in 2018 and again in 2019, SpaceX is pursuing a radically different method of recovery with Starship (the upper stage), while Super Heavy will more directly follow in the footsteps of Falcon 9/Heavy. Starship, however, is being designed to perform a guided descent more akin to a skydiver falling straight down, using flaps at its nose and tail (explicitly “not wings”) to accurately guide its fall.

As little as a few hundred meters above the ground, Starship will then perform a radical maneuver, igniting its Raptor engines to flip around, burn in the opposite direction to counteract that sideways boost, and finally coming in for a precise landing on Earth/Mars/the Moon.

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Beyond the new GNC software and knowledge needed to make that maneuver real, Blackmore is also responsible for Starship atmospheric entry, no less critical to enabling precise, repeatable landings from orbital velocity to touchdown. In his recent interview with University of Cambridge staff, Lars revealed that his role as Principal Mars Landing Engineer involved a far wider scope than his previous GNC-centered work, with the goal instead being to design a launch vehicle (Starship) from the ground up to be easily recovered and reused. Falcon 9 Block 5 may be radically different than the ‘V1.0’ rocket that debuted in 2010, but it’s still ultimately a product of retroactive engineering.

With Starship and Super Heavy, SpaceX instead wants to take the vast wealth of knowledge and experience gained from F9/FH and build the vehicle from the ground up to be optimized for full reuse. Ultimately, Dr. Blackmore stated that “landing Starship will be much harder than landing Falcon 9, but if [SpaceX] can do it, it will be revolutionary.”

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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 Full Self-Driving v14.1 first impressions: Robotaxi-like features arrive

Tesla Full Self-Driving v14.1 is here, and we got to experience it for ourselves.

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Tesla rolled out its Full Self-Driving v14.1 yesterday, its first public launch of its most robust and accurate FSD iteration yet. Luckily, I was able to get my hands on it through the Early Access Program.

The major changes in FSD v14.1 were revealed in the release notes, which outline several notable improvements in areas such as driving styles, parking, and overall navigation. Here’s what Tesla outlined fully in its release notes:

  • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
  • Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
  • Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
  • Added additional Speed Profile to further customize driving style preference.
  • Improved handling for static and dynamic gates.
  • Improved offsetting for road debris (e.g. tires, tree branches, boxes).
  • Improve handling of several scenarios including: unprotected turns, lane changes, vehicle cut-ins, and school busses.
  • Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
  • Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!

I wanted to try it for myself. My big must-dos were my complaints with v13.2.9, which included parking when arriving at a destination, Navigation when leaving a destination, and definitely a general improvement in the car traveling at an acceptable rate of speed, even when using the “Hurry” driving style.

Here’s what I noticed with the new Full Self-Driving v14.1:

Speed Profiles are More Realistic

I am driving on “Hurry” about 95% of the time when utilizing Full Self-Driving. In past versions, most notably v13.2.9, my Tesla would slowly reach the speed limit, and it would tend to hang out at about 1-2 MPH either above or below it.

My first observation with v14.1 was the vehicle’s tendency to get right up to speed and, since I was still on Hurry, drive slightly above the speed limit. It never got out of line; it traveled at speeds I would typically drive at manually.

I think this is a big improvement on its own, because I felt that I was pressing the accelerator too frequently in past FSD versions. Oftentimes, it just wasn’t going fast enough to justify the “Hurry” label; it felt more conservative and more like a student driver than anything.

Check it out:

This was among my favorite improvements, and it was the first thing I noticed as the car navigated me to the Supercharger, where my next positive is.

Navigating into parking lots, self-parking at Supercharger

One of the changes noted in the Release Notes was the addition of Arrival Options, which allows the car to select the appropriate parking situation. Since I was going to charge, the car had already chosen “Charger” as the parking option.

Pulling into a gas station or convenience store, especially during work days, can be stressful, as they are usually congested and full of foot and vehicle traffic. In past FSD versions, I have noticed the car being slightly “jumpy” and even hesitant to proceed through the lot.

Driving through parking lots was a noticeable improvement. It seems as if the car is much more confident in making its way through, while still being aware and cautious enough to safely navigate to the Supercharger.

It then backed straight into a Supercharger stall, which was recently repaired and is once again active. I was actually upset it chose this specific stall because it had been inactive for a while. However, Tesla got this stall back up and running, the car chose it, and backed into the spot flawlessly:

This was super cool to experience, and I think it is a testament to how hard the Tesla AI team has worked. CEO Elon Musk recently stated that FSD would enable automatic parking at Superchargers, which was really awesome to experience firsthand.

I decided to leave the Supercharger and go to an auto parts store to pick up some interior cleaner and some microfiber towels. I love keeping my Tesla clean!

I also thought it would be a great opportunity to see how it would react to another parking lot, how it would navigate it, and let it choose a parking spot. It did it all flawlessly:

I had zero complaints about everything here. All of it was done really well.

Making a choice after being caught in the middle of an intersection

I arrived at a tight intersection in Dallastown, PA, and what my car did next has catalyzed quite a conversation on X.

It proceeded out into the middle of the intersection as the light was green. It had to yield to oncoming traffic, and while waiting, the light turned yellow, then red.

Most people, including myself, would have turned right and proceeded through the intersection since the car was already past the line. However, FSD chose to back up and wait for the next light cycle, which I felt was also a more than acceptable option:

There are some conflicting perspectives on what it chose to do here. Some said they would have proceeded and would want FSD to also proceed. I can agree with that perspective, but I also think it is not the worst thing in the world to back up. In Pennsylvania, I couldn’t find the exact law that says what is right or wrong. Instead, I did see that a left turn on red is only feasible when you’re going from a One-Way street to another One-Way.

I’m not totally sure what is “correct” here, but I think either option is fine. I have personally done both, and I’ve seen other drivers do both. I was more than fine with the car doing this, and I was honestly impressed that it did.

Navigated a busy grocery store lot, found suitable parking

This is not the busiest my local grocery store gets, but it was still congested enough for me to be impressed.

FSD decided to do one loop in the parking lot before it found a spot that it felt was good enough for me. I was perfectly fine with where it chose to park, and I thought it did a really great job. I was impressed with how stress-free I felt, as I have noted in the past that parking lots are definitely an area where Tesla needs to improve.

I was happy with its performance:

Strange right turn signal as if it saw an emergency vehicle

This was the first bug I noticed with FSD v14.1. While traveling on a local road, it put the right turn signal on and approached the curb as if it was pulling over for an emergency vehicle or as if it was going to park on the street.

It then realized its mistake and proceeded:

I’m not super sure what caused this, but I was a tad bit confused. There were no police cars, ambulances, or anyone with flashing lights to my rear. There was a dump truck on the other side of the road, and I almost felt like the way it navigated “around” that was probably what triggered it.

Navigation is still making strange decisions

I’ve written about navigation and my discontent with some of its decisions. It seems v14.1 didn’t resolve much of anything with navigation, and it did a couple of things wrong.

The first was that it tried to take the illogical and pointless path out of the Supercharger. I wrote about this a few days ago, as FSD tried to take my car the wrong way.

It did it again, but I overrode the decision, and it was all okay:

This is a minor issue, but it is still pretty frustrating. Hopefully, the navigation will learn after performing this adjustment after enough times.

The next navigation issue was more frustrating than the Supercharger one, especially considering it completely ignored the route. The navigation had the vehicle very clearly heading straight, but out of nowhere, the right turn signal went on. I overrode it, but the car still turned right, ignoring the navigation completely:

I ended up taking over here and driving until I could get to a stop sign.

Final Thoughts

I am really impressed with all of the changes Tesla made with FSD v14.1, and while there were a handful of bugs, things were tremendously better than v13.2.9.

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Nvidia CEO Jensen Huang regrets not investing more in Elon Musk’s xAI

The CEO stated that Nvidia is already an investor in xAI, but he wished he had given the artificial intelligence startup more money.

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Credit: Elon Musk/X

Nvidia CEO Jensen Huang revealed that one of his investment regrets is not putting more money into Elon Musk’s artificial intelligence startup, xAI. 

Speaking in a CNBC interview, Huang said Nvidia is already an investor in xAI but wished he had given the artificial intelligence startup more money. This was due to Musk’s record of building transformative companies such as Tesla and SpaceX.

A new wave of transformative AI firms

Huang said he’s very excited about xAI’s latest financing round. He described Musk’s company as part of a powerful new generation of AI developers, alongside OpenAI and Anthropic. that are reshaping the computing landscape.

“I’m super excited about the financing opportunity they’re doing. The only regret I have about xAI, we’re an investor already, is that I didn’t give him more money. You know almost everything that Elon’s pat of, you really want to be part of as well,” the Nvidia CEO stated.

The CEO also clarified Nvidia’s investment in xAI, revealing that Elon Musk had offered the investment opportunity to the chipmaker. “He (Musk) gave us the opportunity to invest in xAI. I’m just delighted by that,” Huang stated.

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AI investment boom

Huang contrasted today’s AI-driven economy with the early days of the internet. “Back then, all the internet companies combined were maybe $30 or $40 billion in size,” he said. “If you look at the hyperscalers now, that’s about $2.5 trillion of business already operating today.”

He also stated that the ongoing shift from CPU-based computing to GPU-powered generative AI represents a “multi-trillion-dollar buildout” that Nvidia is looking to support. Huang added that every Nvidia engineer now works with AI coding assistants such as Cursor, which he called his “favorite enterprise AI service,” and it has led to a major productivity boost across the company.

Watch Nvidia CEO Jensen Huang’s CNBC interview in the video below.

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Investor's Corner

Stifel raises Tesla price target by 9.8% over FSD, Robotaxi advancements

Stifel also maintained a “Buy” rating for the electric vehicle maker.

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Credit: Tesla China

Investment firm Stifel has raised its price target for Tesla (NASDAQ:TSLA) shares to $483 from $440 over increased confidence in the company’s self-driving and Robotaxi programs. The new price target suggests an 11.5% upside from Tesla’s closing price on Tuesday.

Stifel also maintained a “Buy” rating despite acknowledging that Tesla’s timeline for fully unsupervised driving may be ambitious.

Building confidence

In a note to clients, Stifel stated that it believes “Tesla is making progress with modest advancements in its Robotaxi network and FSD,” as noted in a report from Investing.com. The firm expects unsupervised FSD to become available for personal use in the U.S. by the end of 2025, with a wider ride-hailing rollout potentially covering half of the U.S. population by year-end.

Stifel also noted that Tesla’s Robotaxi fleet could expand from “tiny to gigantic” within a short time frame, possibly making a material financial impact to the company by late 2026. The firm views Tesla’s vision-based approach to autonomy as central to this long-term growth, suggesting that continued advancements could unlock new revenue streams across both consumer and mobility sectors.

https://twitter.com/AIStockSavvy/status/1975893527344345556

Tesla’s FSD goals still ambitious

While Stifel’s tone remains optimistic, the firm’s analysts acknowledged that Tesla’s aggressive autonomy timeline may face execution challenges. The note described the 2025 unsupervised FSD target as “a stretch,” though still achievable in the medium term.

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“We believe Tesla is making progress with modest advancements in its Robotaxi network and FSD. The company has high expectations for its camera-based approach including; 1) Unsupervised FSD to be available for personal use in the United States by year-end 2025, which appears to be a stretch but seems more likely in the medium term; 2) that it will ‘probably have ride hailing in probably half of the populations of the U.S. by the end of the year’,” the firm noted.

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