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Tesla’s race to autonomy: No one said it would be easy
Need to type up a quick memo before work? Forgot to eat breakfast before driving to school? In just a few years, driving may be a more hands-off endeavor than ever before if companies like Tesla, Uber, Volvo, Alphabet, General Motors, or Ford have anything to do about it. You could be a passenger in your own self-driving car, weaving in and out of traffic with ease and parallel parking like a pro every time. It seems like most every company even tangentially related to cars is pouring money into the race for autonomy.
The freedom of self-driving cars is still heavily dependent on regulatory whim and technological availability, but some are setting demanding goals in an effort to finish first in that race. Tesla for example, plans to showcase its Full Self-Driving Capability by driving one of its fleet cars from California to New York, without human involvement, by the end of this year. But their competitors are moneyed, motivated and many.
The Self-Driving Battle Arena
For Uber, success in autonomous driving research could be a sweet distraction from the recent troubles of the company. Its self-driving program has been based in Pittsburgh, right next to Carnegie Mellon with its highly regarded robotics program since it began in 2015. Then-CEO Travis Kalanick was determined to stay on top of the industry. “It starts with understand that the world is going to go self-driving and autonomous,” Kalanick said in a 2016 interview with Business Insider. “So if that’s happening, what would happen if we weren’t a part of that future? If we weren’t part of the autonomy thing? Then the future passes us by basically, in a very expeditious and efficient way.”
Plagued by lawsuits, investigations, and subsequent executive upheaval that saw Kalanick’s resignation from the enterprise he founded, Uber is still one of the best places for researchers and engineers to work on their projects. The company has armies of vehicles across the country, vast datasets of information from the millions of miles its cars have covered through its ride-hailing branch, and the money to fund its engineers’ work.
This does not mean that Uber’s self-driving program has remained untouched. Waymo, the autonomous car division of Google’s parent company, Alphabet, is currently suing Uber over files allegedly by Anthony Levandowski when he moved from Waymo to Uber. According to Reuters, in recent court filings, Waymo has claimed that Uber knew of the stolen intellectual property and even conspired with Levandowski to use it. Uber denies the allegations and actually fired Levandowski on May 30, claiming he had not cooperated with their internal investigation– and probably hoping to win some goodwill from the judge who has already said Waymo had produced a convincing case.
It is unlikely the scandals will affect the decisions of most researchers to stay with the company. As Wired’s Aarian Marshall points out, the long timeline of building a safe autonomous car makes engineers less likely to leave at a moment’s notice in a period of executive instability. And the branch’s position in Pittsburgh rather than Silicon Valley means the roiling news is less sensationalized and the researchers less affected. The ride-sharing company’s failure to live up to certain promises, including backing one of Pittsburgh’s federal grant proposals or hiring from neighborhoods near its test tracks, have drawn ire from many local activists and politicians, as reported by the New York Times. Even so, it has helped the city break away from its steel past and into a high-tech future.
Meanwhile, Uber’s main competitor in the ride-sharing industry, Lyft, has been making strides to continue chipping away Uber’s monopoly in any field, including self-driving cars, as Uber deals with scandal after scandal. As reported by Recode, Lyft is steadily gaining ground on Uber in terms of the share of ride-hailing app downloads as its ratings in the IOS App Store rise and Uber’s falls. This recent shift in market share comes as Waymo and Lyft start a new partnership that will combine Waymo’s advanced technology with Lyft’s vast amounts of data on people, where and how they drive. “Lyft’s vision and commitment to improving the ways cities move with help Waymo’s self-driving technology reach more people, in more places,” a Waymo spokesperson told Wired. Extending Waymo’s dataset beyond the few cities, including Phoenix and Pittsburgh, allows the enterprise to collect the small details of average people’s driving habits much faster and accurately than its test drives around Silicon Valley will.
But despite Waymo’s eight years of self-driving research, it still has to play catch up to Uber in some regards. Waymo just started testing autonomous trucks earlier this month, while Uber first used a self-driving truck to deliver a shipment last August, advancing its technology quickly after it snatched up the self-driving truck startup Otto—founded by Anthony Levandowski after he left Waymo— in January of 2016. Yet, Waymo has the benefit of its parent company’s huge cash reserves and data.
Growing Pains
Tesla is moving its autonomous program forward at an increasingly demanding pace, trying to meet that goal of driving from Los Angeles to New York by the end of this year. It, like Uber, is going through some executive shakeup: after just six months with Tesla, Chris Lattner, Vice President of its Autopilot Software program, left the company after reported tensions with Elon Musk. Tesla explained that the former Apple engineer was not a “good fit.” It stands to mention that working under Musk is notoriously a high-pressure gig. According to LinkedIn Insights, the average tenure of a Tesla employee is only 2.2 years, while companies like General Motors keeps its employees for almost 9. But Lattner’s exit is just one example of many of talented Tesla self-driving engineers leaving the company or being poached by the competition, like Waymo.
While Autopilot can do many impressive things— change lanes, brake before obstacles, and generally act as a rational human driver— it is far from perfect. The program is still technically in “public beta” testing, and rated by the National Transportation Safety Board as a 2 out of 5 on its scale of autonomy.
The fatal crash of a Model S owner Joshua Brown in May 2016 serves as a good reminder that drivers are cautioned to pay attention and keep their hands on the wheel at all times while using Autopilot. Tesla’s driving-assist feature, at the time, could not distinguish the difference between the bright sky and the white truck. Tesla and Autopilot were cleared of responsibility by the NTSB because Brown was given several warnings to take back control of the wheel. But it is a poignant example that Autopilot does not function as a self-driving car and still requires a driver’s full attention. After the accident, Tesla was forced to start developing its own hardware for Autopilot. Mobileye, which previously supplied Tesla’s image processing chips, ended its partnership in a public spat with Musk.
According to Lattner’s public resume, the transition to its own hardware presented “many tough challenges” to the Tesla team. Musk commented to shareholders in June that Tesla is “almost there in terms of exceeding the ability” of the original hardware. All of Tesla’s vehicles in production, including the upcoming Model 3, have the capability to engage Autopilot (for a price) and the necessary hardware to enable full self-driving someday. Autopilot will continue using the camera-based system that Tesla swears by, even as most of the industry focuses on developing LiDAR technology based on light and lasers.
And while Tesla prefers to work mostly alone, the rest of the industry is also pairing up, making deals, partnerships, and contracts between manufacturers, data giants, and service teams. Musk is taking a move out of Steve Jobs’ playbook by vertically integrating everything within the business, from top-to-bottom. Waymo and Honda, Lyft and Waymo, Autoliv and Volvo, Hertz and Apple, Intel and Mobileye, Audi and NVIDIA, and almost every other combination you could think of. Predictions for when the first company will reach the finish line range from within a year to two decades from now. And even if the car is made, there is still the question of if cities and states will allow autonomous vehicles to drive on their streets. The technology is closer than ever, but for now, please keep your eyes on the road.
Tesla just trademarked ‘MEGAPOD’ with the United States Patent and Trademark Office (USPTO), its latest move in what seems to be a hint that the company is incredibly focused on its AI efforts and storage needs as compute increases.
The application carries serial number 99893717 and lists the applicant as Tesla, Inc., located at 1 Tesla Road, Austin, Texas 78725.
The filing remains in ‘live pending’ status, and it is a new application waiting for assignment to an examining attorney. It has not yet been published or registered.
Tesla just trademarked MEGAPOD
Summary:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and… pic.twitter.com/3l85DsKadl— Robin (@xdNiBoR) June 19, 2026
According to the official goods and services description in the application, Tesla describes ‘MEGAPOD’ as:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and cooling systems, sold as a unit; self-contained modular computing hardware systems for artificial intelligence workloads; integrated computer hardware platforms for artificial intelligence computing, namely, enclosures containing computer hardware, power distribution hardware, and cooling hardware, sold as a unit; downloadable software for monitoring, managing, optimizing, and regulating modular artificial intelligence computing hardware systems.”
This description specifies complete, self-contained modular units that integrate servers and specialized AI processing hardware with networking components, power distribution, and cooling systems. It also includes associated downloadable software for oversight and optimization of these systems. The language emphasizes hardware sold “as a unit” and enclosures that combine the necessary elements for AI computing workloads.
Tesla has an established history of developing and commercializing modular hardware systems. Its Megapack product line, for example, consists of utility-scale battery energy storage systems designed as containerized units for grid applications. The MEGAPOD filing follows a similar pattern of protecting a name for modular, integrated hardware platforms, this time focused on artificial intelligence computing infrastructure.
This could be an early move, especially as Tesla did not have trademark rights to the word ‘Cybercab,’ the name of its self-driving, ride-hailing-focused vehicle.
Trademark applications of this type allow companies to secure priority rights to a name for defined categories of goods and services. The USPTO examines applications for compliance with legal requirements, including distinctiveness and absence of conflicts with prior marks. If the application proceeds successfully through examination, publication, and any opposition period, it could result in a federal trademark registration providing nationwide protection. This is what Tesla’s obvious intention is with ‘MEGAPOD.’
Public reports and analysis suggest MEGAPOD could represent modular, container-style AI computing pods designed for easy deployment. These would bundle servers, AI accelerators, power systems, and cooling into self-contained units suitable for distributed AI workloads. This approach aligns with Tesla’s announced AI compute strategy.
In March 2026, Elon Musk outlined plans for “Digital Optimus” (also referred to as Macrohard), a joint Tesla-xAI project for AI agents capable of handling complex digital tasks. The plans include running these agents on Tesla’s AI4 hardware in parked vehicles as well as dedicated compute units installed at Supercharger stations, which collectively offer substantial unused electrical capacity.
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A modular hardware platform like the one described in the ‘MEGAPOD’ filing would support scalable, rapid deployment of such distributed compute resources. It could complement Tesla’s other AI infrastructure efforts, including the Dojo supercomputer used for training models and the development of AI systems for autonomous driving and robotics, by enabling edge or regional AI inference without reliance on traditional centralized data centers.
Investor's Corner
SpaceX is launching a secret spacecraft that could change how things are made in space
SpaceX’s secret disk-shaped Starfall capsule is targeting a market no reentry vehicle has cracked.
SpaceX is targeting Tuesday, June 23 for the first flight of Starfall, a reentry capsule the company has developed almost entirely in private. The Falcon 9 launch window opens at 6:43 a.m. ET from Space Launch Complex 40 at Cape Canaveral Space Force Station, with a backup window available the same time on June 24. SpaceX has made no public announcement about the vehicle, only providing launch details. Everything known about it has come through FAA and FCC regulatory filings.
What makes Starfall different starts with its shape. Rather than the traditional cone used by Dragon and every other cargo return capsule in operation, Starfall is a flat disk that measures roughly 10.2 feet (3.1 meters) wide and just 2.5 feet (0.75 meters) tall, and weighing 4,630 pounds (2,100 kg) and capable of returning up to 2,200 pounds (1,000 kilograms) of payload from orbit. The disk geometry maximizes structural efficiency and payload volume relative to mass, and the heat shield mechanically jettisons just before splashdown, allowing recovery teams to retrieve both the capsule and the shield separately from the Pacific Ocean.
The difference with Starfall from existing competitors, such as Varda Space Industries, which has largely built the orbital manufacturing market and returns heavy payloads per flight is that Starfall’s specification is roughly 30 times more per mission, and is designed to be mass-produced and launched on either Falcon 9 or Starship. That combination of volume and launch access is something no standalone startup can replicate, and it puts SpaceX in direct competition with the companies that currently pay it to reach orbit.
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The intended market is orbital manufacturing: pharmaceuticals, protein crystals, semiconductors, and advanced optical fiber that physically cannot be produced in the presence of gravity. FAA documents describe Starfall’s long-term purpose as building a “self-sustaining commercial in-space manufacturing market” and as a potential successor to the industrial capabilities of the International Space Station, which is set to retire in the late 2020s. Military rapid global cargo delivery is a parallel application under active discussion with the Pentagon.
The reason some industries seek manufacturing in space comes down to gravity. On Earth, gravity causes materials to settle, separate, and deform during production. In microgravity, those constraints disappear.
SpaceX’s already controls launch access, which means it currently functions as the landlord for every competitor in the orbital manufacturing return space. Starfall converts that landlord position into vertical ownership, and it would no longer just carry other companies’ capsules to orbit, but rather operate the capsule, own the return logistics, and capture the service revenue directly. Viewed alongside Starlink, Colossus, and the xAI merger, Starfall fits a consistent pattern: SpaceX identifying infrastructure layers that others depend on and moving to own them outright. Orbital manufacturing return is the next layer on that list.
If Tuesday’s reentry, parachute sequence, and recovery demonstration goes as planned, the second FAA-approved test flight follows. A successful pair of demos would position SpaceX to begin offering Starfall as a commercial service, likely first to pharmaceutical and materials science customers before scaling toward the military and broader manufacturing segments.
The Tesla Semi was spotted mounted with ground truth validation equipment as the company nears its looming launch. The Semi is Tesla’s Class 8 all-electric truck, and has been utilized in its earlier stages by many companies like PepsiCo. and Frito-Lay, who have been using it in a pilot program.
The Semi was spotted in Sunnyvale, California, and sports a typical ground truth validation unit that Tesla routinely uses on its vehicles. Ground truth validation is essentially the process of training supervised algorithms to ensure they can perform reliably. Tesla typically performs this on vehicles that are being released soon:
Spotted the new semi adorned with ground truthing equipment. Haven’t seen anyone post this so figured I’d share.
The future is autonomous!!@SawyerMerritt @wholemars pic.twitter.com/qkPDHPUQZ6
— Danny (@dannywinner1) June 21, 2026
The Semi being spotted with this type of validation rig is important because it means the company is working on solidifying a Full Self-Driving model for its commercial vehicle offering. This would be a massive development for not only Tesla but also the logistics industry as a whole.
There are strict regulations on driving hours for commercial truck drivers, and autonomy is a way to potentially combat these issues. FSD is already a widely effective way that owners of typical passenger vehicles take stress out of travel. Even launching a semi-autonomous platform for truck drivers to use to increase safety, reduce fatigue, and increase productivity would be a huge development.
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The Semi has already proven to be an ideal solution for companies that use commercial logistics. It has increased efficiency and reduced operating costs for many companies that have been able to use it in pilot programs.
There are expected to be some bumps along the way. Tesla saw some challenges with FSD on the Cybertruck, as it had never had a vehicle with cameras at that height, so some of the features with FSD were not immediately available. Just a week ago, Tesla launched Actually Smart Summon (ASS) for Cybertruck, nearly three years after the vehicle was first delivered to customers.
Tesla just trademarked MEGAPOD: here’s what it is
SpaceX is launching a secret spacecraft that could change how things are made in space
