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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.
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Tesla Cybercab gets crazy change as mass production begins
Tesla has officially kicked off mass production of its groundbreaking Cybercab robotaxi at Giga Texas, and the first units rolling off the line feature a striking transformation that’s turning heads across the EV community.
Tesla Cybercab has evidently received a pretty crazy change from an aesthetic standpoint, as the company has made the decision to offer an additional finish on the vehicle as mass production is starting.
Tesla has officially kicked off mass production of its groundbreaking Cybercab robotaxi at Giga Texas, and the first units rolling off the line feature a striking transformation that’s turning heads across the EV community.
VIN Zero—the very first production Cybercab—showcases a vibrant champagne gold exterior with a high-gloss finish, a dramatic departure from the flat, matte-wrapped prototypes that debuted at the 2024 “We, Robot” event.
Presenting VIN Zero — the very first production Cybercab built at Giga Texas. pic.twitter.com/8bXo4CJAlr
— TechOperator (@TechOperator) April 23, 2026
This glossy sheen is a pretty big pivot from what was initially shown by Tesla. The company has maintained a pretty flat tone in terms of anything related to custom colors or finishes.
A specialized clear coat or process delivers the deep, reflective gloss without conventional painting. The result is a premium, mirror-like shine, and it looks pretty good, and gives the compact two-seater a more luxurious and futuristic presence than the subdued matte prototypes.
Photos shared by Tesla community members reveal VIN Zero in a showroom-like setting at Giga Texas, highlighting refined panel gaps, large aero wheel covers, and the signature no-steering-wheel, no-pedals interior optimized for full autonomy.
The open frunk in some images offers a glimpse of practical storage, while the overall build quality appears more polished than that of test mules.
This glossy evolution aligns with Tesla’s broader production ramp. After the first unit in February 2026, the company has shifted to volume manufacturing, with dozens of units already spotted in outbound lots. CEO Elon Musk and the team aim for hundreds per week, paving the way for unsupervised FSD robotaxi networks that could slash ride costs to pennies per mile.
The Cybercab holds Tesla’s grand ambitions of operating a full-service ride-hailing service without any drivers in its grasp. Tesla has yet to solve autonomy, but is well on its way, and although its timelines are usually a bit off, improvements often come through the Over-the-Air updates to the Full Self-Driving suite.
Tesla has confirmed today that its steering wheel-less and pedal-less Cybercab, the vehicle geared toward launching the company’s autonomous ride-hailing hopes, has officially entered production at its Giga Texas production facility outside of Austin.
The Cybercab is a sleek two-door, two-passenger coupe engineered from the ground up as an electric self-driving vehicle. It features no steering wheel or pedals, relying instead on Tesla’s advanced vision-only Full Self-Driving system powered by multiple cameras and artificial intelligence.
Purpose-built for autonomy
Cybercab in production now at Giga Texas pic.twitter.com/Y9qG3KyWBa
— Tesla (@Tesla) April 23, 2026
The minimalist cabin centers on a large display screen that serves as the primary interface for passengers, creating an open, futuristic space optimized for comfort during unsupervised rides. A compact 35-kilowatt-hour battery pack delivers exceptional efficiency at 5.5 miles per kilowatt-hour, providing an estimated 200-mile range.
Additional innovations include inductive charging compatibility and a lightweight design that enhances aerodynamics and performance.
Production at Giga Texas builds on earlier prototypes and initial units completed earlier in 2026. The facility, already a hub for Model Y and Cybertruck assembly, now ramps up dedicated lines for the Cybercab.
This shift to volume manufacturing reflects Tesla’s strategy to scale affordable autonomous vehicles rapidly.
By focusing on a dedicated platform rather than adapting existing models, the company aims to keep costs low while prioritizing safety and reliability through continuous AI improvements.
The Cybercab’s debut in production carries broad implications for urban mobility. As the cornerstone of Tesla’s Robotaxi network, it promises on-demand, driverless rides that could slash transportation expenses, reduce traffic accidents caused by human error, and lower emissions through its all-electric powertrain.
Accessibility features, such as space for service animals or assistive devices, further broaden its appeal. Regulators and cities worldwide will soon evaluate its deployment, but the vehicle’s design already addresses key hurdles in scaling unsupervised autonomy.
Challenges persist, including full regulatory clearance and building charging infrastructure. Yet this production launch signals momentum. With Cybercabs poised to roll out in increasing numbers, Tesla edges closer to a future where personal ownership meets shared fleets of intelligent vehicles.
The start of Cybercab production is more than just a new vehicle entering mass manufacturing for Tesla, as it’s a signal autonomy is near. Being developed without manual controls is such a massive sign by Tesla that it trusts its progress on Full Self-Driving.
While the development of that suite continues, Tesla is making a clear cut statement that it is prepared to get its fully autonomous vehicle out in public roads as it prepares to revolutionize passenger travel once and for all.
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Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
There were two new lines of improvements in the release notes: one addressing Actually Smart Summon (ASS), and another that now allows drivers to choose a reason for an intervention via a small menu during disengagement.
Tesla Full Self-Driving v14.3.2 began rolling out to some owners earlier this week, and there are some notable improvements that came with this update.
There were two new lines of improvements in the release notes: one addressing Actually Smart Summon (ASS), and another that now allows drivers to choose a reason for an intervention via a small menu during disengagement.
Overall operation saw a handful of slight improvements, especially with parking performance, which has been the most notable difference with the arrival of FSD v14.3. However, there are still some very notable shortcomings, most notably with region-specific signage and navigation.
Tesla Assisted Smart Summon (ASS) improvements
There are noticeable improvements to ASS operation, which has definitely been inconsistent in terms of performance. Tesla wrote in the release notes for v14.3.2:
“Unified the model between Actually Smart Summon, FSD, and Robotaxi for more capable and reliable behavior.”
As recently as this month, I used Summon with no success. It had pulled around the parking lot I was in incorrectly, leaving the range at which Summon can be operated and losing a signal while moving in the middle of the lot.
This caused me to sprint across the lot to retrieve the vehicle:
It was pouring when I left the gym so I tried to Summon my Model Y
It turned the opposite way and drove out of range, stopping here and forcing me to walk even further across the lot in the rain for it 🤣
One day pic.twitter.com/iD10c8sriB
— TESLARATI (@Teslarati) April 5, 2026
Unfortunately, Summon was not dependable or accurate enough to use regularly. It appears Tesla might have bridged the gap needed to make it an effective feature, as two tests in parking lots proved that Summon was more responsive and faster to navigate to the location chosen.
It also did so without hesitation, confidently, and at a comfortable speed. I was able to test it twice at different distances:
🚨 Tesla FSD v14.3.2 ASS testing part 1
This was a significant improvement than recent tries using ASS. The parking lot was pretty empty but getting it to come to my location in one singular motion and maneuver was encouraging. https://t.co/vF7TS48GGV pic.twitter.com/sYt8tyHgNn
— TESLARATI (@Teslarati) April 23, 2026
Tesla Full Self-Driving v14.3.2 ASS testing part 2 https://t.co/lxfWfnLUxf pic.twitter.com/2R0r3ohI3M
— TESLARATI (@Teslarati) April 23, 2026
I plan to test this more thoroughly and regularly through the next few weeks, and I avoided using it in a congested parking lot initially because I have not had overwhelming success with Summon in the past. I wanted to set a low baseline for it to see if it could simply pull up to the place I pinned in the Tesla app.
It was two for two, which is a big improvement because I don’t think I ever had successful Summon attempts back-to-back. It just seems more confident than ever before.
New Disengagement Categories
This is a really good idea from Tesla, but there are some issues with it. The categories you can select are Critical, Comfort, Preference, and Other.
I think the reasons why people choose to take over would be a better way to prompt drivers, like, “Traveling Too Fast,” “Incorrect Maneuver,” “Navigation Error,” would be more beneficial.
I say this because it seems that how we each categorize things might be different. For example, I shared a video of an intervention because the car had navigated to an exit to a parking lot and put its left blinker on, despite left turns not being allowed there.
I disengaged and chose Critical as the reason; it’s not a comfort issue, it’s not a preference, it’s quite literally an illegal turn, and it’s also dangerous because it cuts across several lanes of traffic and is 180 degrees.
I chose to label this Navigation error as “Critical” while testing FSD v14.3.2
Here’s why:
✅ This intervention wasn’t “preference,” as the maneuver FSD routed was illegal
✅ If a police officer saw this maneuver, it would result in a ticket https://t.co/znhHb4haAo pic.twitter.com/bZOiLwWmQa— TESLARATI (@Teslarati) April 23, 2026
Some said I should not have labeled this as Critical, but that’s the description I best characterized the disengagement as.
Categorizing interventions is a good thing, but it’s kind of hard to determine how to label them correctly.
Inconsistency with Regional Traffic Patterns
Tesla Full Self-Driving is pretty inconsistent with how it handles regional or local traffic patterns and road rules. The most frequent example I like to use is that of the “Except Right Turn” stop sign, which has become a notorious sighting on our social media platforms.
In the initial rollout of v14.3, my Model Y successfully navigated through one of these stop signs with no issues. However, testing at two of these stop signs yesterday proved it is still not sure how to read signs and navigate through them properly.
🚨 Tesla FSD v14.3.2 attempts the “Except Right Turn” stop sign: https://t.co/W5MjAybaNK pic.twitter.com/P6oeUsk4PN
— TESLARATI (@Teslarati) April 23, 2026
Off camera, I approached another one of these signs and felt the car coming to a stop, so I nudged it forward with the accelerator pedal pressed.
This helped the car go through the sign without stopping, but I could feel the bucking of the vehicle as the car really wanted to stop.
Musk said on the earnings call earlier this week that unsupervised FSD would probably be available in some regions before others, including a state-to-state basis in the U.S.
“It’s difficult to release this like to everyone everywhere all at once because we do want to make sure that they’re not unique situations in a city that particularly complex intersection or — actually, they tend to be places where people get into accidents a lot because they’re just — perhaps there’s — and like I said, an unsafe intersection or bad road markings or a lot of weather challenges. So I think we would release unsupervised gradually to the customer fleet as we feel like a particular geography is confirmed to be safe.”
This could be one of those examples that Tesla just has to figure out.
Highway Operation
Full Self-Driving is already pretty good at routine roadway navigation, so I don’t have too much to report here.
However, I was happy with FSD’s decision-making at several points, including its choice not to pass a slightly slower car and remain in the right lane as we approached the off-ramp:
🚨 Tesla FSD v14.3.2 highway operation: generally happy with the performance here, especially behavior near the exit
Love that the car got over in the right lane after its final pass, and stayed there as the off ramp was approaching https://t.co/qVRVhg6XGR pic.twitter.com/1ELwHf2XKS
— TESLARATI (@Teslarati) April 23, 2026
Better Maneuvering at Stop Signs
Many FSD users report some strange operations at stop signs, especially four-way intersections where there is a stop sign and a line on the road, and they’re not even with one another.
I experienced this quite frequently and found that FSD would actually double stop: once at the stop sign and again at the line.
This created some interesting scenarios for me and I had many cars honk at me when the second stop would happen. Other vehicles that had waved me on to proceed through the intersection would become frustrated at the second stop.
FSD seems to have worked through this particular maneuver:
🚨 Tesla FSD v14.3.2 with a singular stop at the correct spot
No double stopping anymore in my experience https://t.co/Wd0TaNjc1R pic.twitter.com/CdQPvJHaAM
— TESLARATI (@Teslarati) April 23, 2026
FSD should know to go to the more appropriate location (whichever provides better visibility), and proceed when it is the car’s turn to move. The double stop really ruined the flow of traffic at times and generally caused some frustration from other drivers.
Tesla Cybercab gets crazy change as mass production begins
Tesla confirms Cybercab with no steering wheel enters production
