News
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’s two recently-defunct flagship models, the Model S and Model X, are getting a big upgrade, according to the company’s Head of AI, Ashok Elluswamy.
Older Hardware 3 Model S and Model X vehicles have been the last major holdouts in Tesla’s Full Self-Driving v14 Lite rollout, and that wait now appears to be ending.
Tesla brings closure to flagship ‘sentimental’ models, Musk confirms
At Tesla’s Cybercab launch, AI chief Ashok Elluswamy told Ryan McCaffrey that he thought the S and X build “was supposed to go out last week.” Evidently, Elluswamy expects the suite to be rolled out to those HW3 Model S and Model X very soon:
For my @Tesla friends – and specifically Model S & X owners with HW3 who are waiting on FSD v14 Lite – I spoke to @aelluswamy at the Cybercab launch, & when I asked for an ETA on v14 Lite for S/X owners, he said, “Oh, I thought it was supposed to go out last week.”
So: soon! 🙌
— Ryan McCaffrey (@DMC_Ryan) September 7, 2026
Those cars are not the current Model S and Model X, which already ship with Hardware 4. They are the pre-refresh flagships built around Tesla’s older Autopilot computer, often called HW3 or AI3.
Tesla stopped putting that computer in new vehicles years ago, which is why owners treat these S and X cars as a closed generation. Model 3 and Model Y vehicles on the same computer began receiving v14 Lite in late June 2026 and saw a wider North American expansion in July. South Korea followed as an early international market. The S and X versions of the same software never joined that wave.
v14 Lite is Tesla’s way of squeezing the current v14 driving stack onto hardware that cannot run the full AI 4 model. The company describes the process as distillation: behaviors learned on the newer computer, including reinforcement learning and offline models, are compressed so the older chip and cameras can use them as a guide.
Early descriptions put the distilled network at roughly 15 percent of the original size. The result is still supervised Level 2 driving. Tesla has been clear that HW3 cannot support unsupervised Full Self-Driving or robotaxi operation because of memory and bandwidth limits.
The feature list is what made the wait so frustrating for S and X owners, as plenty of new features are to be shipped with it.
Official notes for the first Lite build, firmware 2026.20.5.1, added parking, unparking, and reversing; arrival options for a parking lot, street, driveway, or curbside; speed profiles that stay available at all times; and start-from-park engagement. Tesla also claimed better handling of merges, forks, pedestrians, traffic lights, and cut-ins, plus fewer false slowdowns and smoother lane centering.
A mid-July follow-on build, 2026.20.6.10, added more of the Hardware 4 interface, including a standalone Self-Driving app and the ability to start a trip from Park without a brake-pedal confirmation.
Elluswamy called that version the one “likely going to wide release.”
That wide release already reached most other HW3 cars in the United States and Canada. International timing still depends on regional validation and regulatory approval. For S and X owners, the remaining work appears to be model-specific validation rather than a new software stack.
There is no official Tesla changelog or build number for those two models yet, only Elluswamy’s offhand timeline. Some HW3 drivers who already have Lite report large gains over v12.6; others have described new indecision or phantom braking. The next test will be whether the same software lands cleanly on the older flagships that have waited the longest.
Yesterday, we reported on Tesla Cybertruck getting some major adjustments from a manufacturing standpoint in an effort to make the all-electric pickup more cost-effective, more reliable, more serviceable, and more easily produced.
Tesla Cybertruck engineer reveals new changes in ‘constantly evolving’ pickup
One of those changes was the addition of a self-reinforcing polypropylene aero shield that sits underneath the truck. Previously, Tesla utilized aluminum for this, but the self-reinforcing polypropylene was more durable while also being cheaper and lighter.
Tesla has revealed another small change it made to the Cybertruck, and it has to do with the side repeater cameras.
Tesla does not wait for a new model year to improve its vehicles. On September 8, Cybertruck lead engineer Wes Morrill posted side-by-side photos of an updated side repeater camera housing now rolling off the line at Gigafactory Texas.
The triangular camera pod mounted on the front fender looks almost identical at first glance. A closer look reveals a revised contour that uses the air already flowing around the truck to keep the lens clearer in rain and road spray.
The side repeater camera was updated – the version on the left is the newer part which uses passive geometry to create airflow disturbance that better keep water off the lens while driving. No cost penalty, just pure vision improvement. pic.twitter.com/wAbXtcL1Jf
— Wes (@wmorrill3) September 8, 2026
The side repeater cameras sit in an exposed position on the Cybertruck’s angular stainless-steel body.
In wet weather, they readily collect water droplets that can degrade the image Autopilot and Full Self-Driving use for lane changes and blind-spot monitoring. Early production trucks sometimes left owners wiping lenses by hand or accepting temporary restrictions on driver-assistance features.
Tesla has added washers to cameras on certain other models and on Cybercab prototypes, but those active systems add cost, complexity, and extra potential leak points.
The new housing solves the problem with passive geometry. Subtle changes in the surround create localized airflow disturbances as the vehicle moves. Those eddies physically push water droplets away from the optical surface. Morrill called the result “pure vision improvement” achieved at “no cost penalty.” Once the production mold is updated, every subsequent part costs the same as the original.
The advantages compound quickly. Clearer cameras in rain improve the reliability of driver-assistance features precisely when they are needed most. The design consumes no extra energy and introduces no new failure modes.
New Cybertrucks built after the tooling changeover receive the updated part automatically. Some owners of trucks delivered as late as June 2026 have already confirmed they received the revised housing. Retrofit questions have appeared in replies, and the cameras appear electrically compatible, though Tesla has not announced an official service program.
A few millimeters of reshaped housing will not make headlines the way a new battery pack does, but these changes are incremental and increase the Cybertruck’s effectiveness as a vehicle over time.
This improvement illustrates how Tesla continues to refine the Cybertruck after volume production began. Better wet-weather vision, zero added cost, and no extra hardware add up to a meaningful gain in everyday usability and safety.
Tesla is rolling out a new version of its Full Self-Driving suite to some owners that comes with the massive addition of a safety feature.
Tesla is rolling out Automatic Collision Evasion with the 2026.27.6 Software Update, which started rolling out to some vehicles last night. We received the update, along with Full Self-Driving v14.3.9, as well as v14.2 Lite, which has identical release notes as the previous version and seems to have some refinements and improvements in behavior and performance.
🚨 Tesla FSD v14.3.9 is rolling out as well as 2026.27.6 which includes Automatic Collision Evasion
Brand new safety features from a software update. My Tesla gets better everytime I get one of these pic.twitter.com/ctrMiQXWhM
— TESLARATI (@Teslarati) September 8, 2026
However, most of the attention has fallen on the Automatic Collision Evasion feature, which we covered in an article last week.
The function will activate Full Self-Driving to “try to keep your vehicle safe and then continue driving. It can engage in the following situations while you are driving manually:
- Scenario 1: A frontal collision is imminent and braking alone may not avoid it.
- Scenario 2: Your vehicle detects that you are not sufficiently attentive to the road (for example, reaching toward the back seat), or that Full Self-Driving (Supervised) may have been unintentionally disengaged.”
Essentially, FSD will take over when the vehicle determines you are not paying sufficient attention or are heading toward a potential collision. The addition of this feature is incredibly useful as distracted driving is a major issue in today’s world.
Along with the new safety feature is Tesla FSD v14.3.9, which has no additional release notes compared to the previous version, but in my first drives, my first impression is that operation is great, and parking is still sort of a pain point.
Just took a 15-mile round trip to the gym and back
Pretty on par with what FSD is nowadays – really good. Not enough time to see what’s good and what’s bad, but these first rides on any version feel shockingly good. They’re all pretty identical https://t.co/WN1qTg4bhE
— TESLARATI (@Teslarati) September 9, 2026
Additionally, Tesla v14.2. Lite has arrived. A great review of that is available here:
— Zack (@BLKMDL3) September 9, 2026
The addition of an Automatic Collision Evasion feature is similar to that of other collision avoidance systems that are used by companies like Hyundai, Kia, and Genesis. These programs typically utilize radar and camera sensors to apply emergency brakes autonomously, though evasive steering in a manual driving mode is pioneered primarily by Tesla’s newest addition.
Tesla’s two defunct flagship models are getting a big upgrade
This tiny Tesla Cybertruck adjustment has big advantages
