Connect with us

News

SpaceX celebrates 2018 Hyperloop competition success, opens 2019 registration

Published

on

SpaceX has released a video commemorating the amazing successes of its 2018 Hyperloop Pod Competition at the same time as it’s opened up registration for next year’s follow-up competition, paving (pipelaying?) the way for another throwdown that will seek to once again crown victorious the student team with the fastest pod.

With any luck to next year’s competitors, one or several of those 2019 entrants may once more smash the 2018 world speed record, faster than any production car in history at a whiplash-triggering 467 km/h (290 mph).

With that 290 mph top speed confirmed after WARR’s third 2018 pod run, the Technical University of Munich (TUM) student-led operation solidified itself – for the second time in a row – as the team to beat, breaking their own 2017 Competition 2 speed record of 324 km/h (202 mph) by nearly 50%, a record that itself smashed WARR’s own 90 km/h (~56 mph) top speed record from the inaugural Hyperloop Competition just six months prior. Now the proud holder of three of three Hyperloop Competition top-speed trophies, all eyes will once more be on WARR in anticipation of yet another spectacle of smashed records.

Advertisement

 

As noted on SpaceX’s website, that fourth upcoming competition – scheduled for the summer of 2019 – features two major updates to the rules and winning criteria.

As with previous competitions, the competition will be judged solely on one criteria [sic]: maximum speed with successful deceleration (i.e. without crashing) and all Pods must be self-propelled.

1. Teams must use their own communications system. SpaceX will not provide its on-Pod communications system, otherwise known as the Network Access Panel (NAP).

Advertisement

2. Pods must be designed and tested to propel themselves to within 100 feet of the far end of the tube before stopping. This can take the form of a single main run to that point, or a “slow crawl” after the Pod’s main run has been completed. 

In essence, SpaceX is continuing to gradually remove crutches, encouraging student teams to become more and more independent, especially useful for returning groups. Communication with pods is surprisingly difficult, as any solution chosen must function reliably, wirelessly, and in vacuum conditions, meaning that 2019 competitors will face another major challenge while designing new pods or updating older entrants.

WARR Hyperloop poses in front of their third (of three) top-speed trophy and the pod that made it possible. (WARR Hyperloop)

Meanwhile, the decision to require pods to either be able to accurately stop with an error of less than 2% the test Hyperloop’s length (100 feet) or be capable of multiple modes of propulsion (i.e. top-speed runs and “slow-crawl” without assistance from its designers) should add another level of difficulty and intrigue to 2019’s Hyperloop competition. Critically, returning teams – if accepted – will be required to significantly modify their existing pod or design a new pod if they wish to compete in 2019.

Catch SpaceX’s 2018 Competition below and visit SpaceX.com/Hyperloop in the event that you are a student, have a team, and want to build your very own super-fast Hyperloop pod.

Advertisement

For prompt updates, on-the-ground perspectives, and unique glimpses of SpaceX’s rocket recovery fleet check out our brand new LaunchPad and LandingZone newsletters!

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.

Advertisement
Comments

News

SpaceX President Gwynne Shotwell details xAI power pledge at White House event

The commitment was announced during an event with United States President Donald Trump.

Published

on

xAI-supercomputer-memphis-environment-pushback
Credit: xAI

SpaceX President Gwynne Shotwell stated that xAI will develop 1.2 gigawatts of power at its Memphis-area AI supercomputer site as part of the White House’s new “Ratepayer Protection Pledge.” 

The commitment was announced during an event with United States President Donald Trump.

During the White House event, Shotwell stated that xAI’s AI data center near Memphis would include a major energy installation designed to support the facility’s power needs.

“As you know, xAI builds huge supercomputers and data centers and we build them fast. Currently, we’re building one on the Tennessee-Mississippi state line. As part of today’s commitment, we will take extensive additional steps to continue to reduce the costs of electricity for our neighbors… 

Advertisement

“xAI will therefore commit to develop 1.2 GW of power as our supercomputer’s primary power source. That will be for every additional data center as well. We will expand what is already the largest global Megapack power installation in the world,” Shotwell said.

She added that the system would provide significant backup power capacity.

“The installation will provide enough backup power to power the city of Memphis, and more than sufficient energy to power the town of Southaven, Mississippi where the data center resides. We will build new substations and invest in electrical infrastructure to provide stability to the area’s grid.”

Shotwell also noted that xAI will be supporting the area’s water supply as well. 

Advertisement

“We haven’t talked about it yet, but this is actually quite important. We will build state-of-the-art water recycling plants that will protect approximately 4.7 billion gallons of water from the Memphis aquifer each year. And we will employ thousands of American workers from around the city of Memphis on both sides of the TN-MS border,” she noted. 

The Ratepayer Protection Pledge was introduced as part of the federal government’s effort to address concerns about rising electricity costs tied to large AI data centers, as noted in an Insider report. Under the agreement, companies developing major AI infrastructure projects committed to covering their own power generation needs and avoiding additional costs for local ratepayers.

Continue Reading

News

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.

Published

on

Credit: Tesla

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:

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.

Tesla ends Full Self-Driving purchase option in the U.S.

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:

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.

Continue Reading

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.

Published

on

Credit: Tesla

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.

Continue Reading