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Tesla Autopilot veterans launch company to accelerate self-driving development
After working on Tesla’s Autopilot team for 2.5 years, Andrew Kouri and Erik Reed decided to start their own self-driving, AI-based company rightfully named lvl5. Together with iRobot engineer George Tal, lvl5 aims to develop advanced vision software and HD maps for self-driving cars.
Founded in 2016, lvl5 was incubated at renown Silicon Valley incubator Y Combinator and later raised $2 million in seed funding from investor Paul Buchheit, who’s a partner at Y Combinator and creator of Gmail, and Max Altman’s 9Point Ventures.
In just 3 months, lvl5 racked up almost 500,000 miles of US roadway coverage with Payver. (Photo: lvl5)
“Working with lvl5’s founders while they were at Y Combinator, it was clear they have unmatched expertise in computer vision, which is the secret sauce of their solution,” said Buchheit. “I have no doubt this is the team to make self-driving a reality in the near term.”
At the center of lvl5’s technology is their computer vision algorithms. Founder and CTO George Tall previously specialized in computer vision technology at iRobot. In addition to Tall’s experience at iRobot, Kouri and Reed’s experience at Tesla undoubtedly left them with unparalleled expertise in computer vision.
Instead of turning to expensive LiDAR technology, lvl5’s computer vision analyzes its environment for stoplights, signs, potholes, and other objects. The system can be accurate to 10cm, a notable measure considering it’s derived from simple cameras and smartphones. In comparison, LiDAR systems can cost over $80,000 but are accurate to 3cm.
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- Each purple trace through the intersection contributes to building the 3D map from a 2D image. For each frame, lvl5’s computer vision technology computes the position of the vehicle relative to other objects in the intersection and create a point cloud that resembles the output from LiDAR. Each white sideways “pyramid” represents the location of a captured frame in the video trace. (Photo: lvl5)
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- This image is taken from one of lvl5’s neural nets, which is designed to draw a box around the position of traffic lights in an image. (Photo: lvl5)
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- With only two trips through this intersection, lvl5 can start to extract semantic features such as a stop sign. (Photo: lvl5)
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- The three founders of lvl5 in front of their SF home. Left to right: Erik Reed, Andrew Kouri, George Tall (Photo: Lvl5)
So how will lvl5 map roadways in the world using their computer vision technology? Smartphones. Well, for now at least. The company has released an app called Payver that allows anyone’s smartphone to collect data while driving and get paid between $.01-$.05 per mile, depending on a number of factors. Users of the app place their phone in a mount on their dashboard and let the app gather driving data.
The data is sent to lvl5’s central hub and processed by their computer vision technology. “Lvl5 is solving one of the biggest obstacles to widespread availability of self-driving technology,” said Max Altman, one of lvl5’s seed round investors and partner at 9Point Ventures. “Without accurate and efficient HD mapping, as well as the computer vision software that enables it, self-driving vehicles will take much longer to reach mass-market. This will delay everything from safer roads to efficient delivery services.”
GIF: lvl5
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“We have to make self-driving available worldwide – not just in California,” Co-Founder and CEO Andrew Kouri said in a company statement. “Our approach, which combines computer vision software, crowdsourcing and widely available, affordable hardware, means our technology is accessible and will make self-driving a reality today, rather than five years from now.”
The company has already established pilot programs with major automakers and both Uber and Lyft. Companies will pay lvl5 an initial fee to use the maps, along with a monthly subscription to keep the maps continuously updated. “Through its OEM-agnostic approach, lvl5 will be able to collect significant amounts of mapping data from millions of cars in order to scale the technology for the benefit of drivers and pedestrians around the world,” the company’s press release states.
Tesla briefly offered one Robotaxi part in its Parts Catalog for your personal car, only to remove it just a short time after it was first noticed.
Tesla’s Robotaxi camera washer apparatus was briefly available for purchase on the company’s Online Parts Catalog. The camera washer was first noticed on Model Y Robotaxi vehicles about six months ago in Austin.
🚨 Tesla looks to have installed Camera Washers on the side repeater cameras on Robotaxis in Austin
pic.twitter.com/xemRtDtlRR— TESLARATI (@Teslarati) January 23, 2026
First noticed by Not a Tesla App, the Camera Washer entries appeared for the new “Juniper” Model Y under a category called “Halo,” which has also now disappeared. Interestingly, Halo probably is related to Tesla’s internal “Project Halo,” which was a project that aimed to retrofit customer-owned Model Ys into functional Robotaxis.
This hardware addition would likely be required for the vehicle to operate as a Robotaxi, as the Camera Washer seems to be a non-negotiable part of the vision-based system Tesla utilizes for self-driving efforts.
However, this part has since been removed and is no longer visible on the EPC.
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Now the true question lingers: Why would Tesla add this Camera Washer to the Model Y parts catalog? Is it planning to make it available for owners to utilize on their own cars for personal use, or will it become a prerequisite for Robotaxi operation in customer-owned cars?
While discussing the upgrade options for Hardware 3 vehicles during the Q1 Earnings Call, Tesla CEO Elon Musk had said that the company could establish small, satellite shops that would upgrade cameras and self-driving computers. Perhaps this same strategy could be utilized for vehicles that want to be included in Robotaxi but do not have the correct hardware.
AI4 is currently represented as capable of unsupervised self-driving, and the same was said about HW3 at one point, only for Tesla to admit last quarter that it would, unfortunately, not be possible. Perhaps AI4 vehicles might need this camera washer as a prerequisite, just as HW3 cars will need that camera and computer upgrade.
This could be the first hint of that’s where we are headed.
Tesla has started rolling out a broader change to the ride experience for its Robotaxi fleet by silencing turn signals, but the change is certainly polarizing.
Tesla has generally made it clear that its purpose-built ride-hailing platform, Robotaxi, will cater to the rider in nearly every way possible. This includes having climate preferences, music, and other personal settings loaded up in the car as the rider enters.
But Tesla is taking it a step further by muting turn signal chimes altogether, a change that appears to be a way to make the ride more peaceful:
Tesla has finally turned off the blinker/turn signal noises in their Model Y Robotaxis.
This is a small update, but will definitely be noticeable for riders. It didn’t really make much sense to leave the turn signal sound on when it’s Unsupervised. pic.twitter.com/ITwx60PAMO
— Sawyer Merritt (@SawyerMerritt) July 27, 2026
However, there are a handful of people who are not thrilled about this change. Turn signals are a conditioned part of the human mind for those who ride in a car regularly.
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Taking a turn without one feels strange and odd, and not hearing it click while activated could set off some alarms for riders, who might use the noise as confirmation that other drivers know of their intention to turn.
I kind of like it being on, threw me off when riding with Zoox who has had it disabled
— Dan Burkland (@DBurkland) July 27, 2026
Turn signal noises are still audible in customer cars, so if you use FSD in your personal vehicle, you will still hear the turn signal.
The move is certainly one that is unique, but not one that separates it from other ride-sharing services. In a normal car, the clicking sound confirms to the driver that the blinker is active. In a fully driverless Robotaxi, that feedback serves no purpose for passengers, other than peace of mind.
Tesla released Full Self-Driving version 14.3.6 last week, and after what was potentially one of the best FSD releases in v14.3.5, there has been a bit of a regression. While there are some bright spots, the changes made to v14.3.6 seem to have backtracked some behaviors.
Overall, it is hard to really complain about FSD in any sense; it has revolutionized how I travel literally anywhere. According to my self-driving app, the last time I went a day without using it was 59 days ago.
However, I think it’s also important to recognize when things are just plain bad with FSD. There are times it does truly mind-boggling things, and I’ll dive into those here. Additionally, I only had these issues on local roads, not on highways. Highway operation, generally, is always incredible other than the occasional complaint about speed or left lane camping.
With those things being said, my personal experience may not represent others’ experiences. A handful of people have said they have had a similar experience on v14.3.6, while others have said it is more than normal.
Turning Hesitancy, Inaccuracy
I’ve noticed more inaccuracy turning into multi-lane stretches of road than in any version I can remember. I’ve had at least three instances of FSD turning into a stretch of roadway that has two or more lanes, and not selecting a lane confidently as it has in past versions.
I think Tesla FSD v14.3.6 is a regression from previous .3 branches
This version in particular has been incredibly hesitant, jerky, and indecisive at times. There’s actually been two drives that I have decided to not used FSD for the remainder of the trip. These were local trips… pic.twitter.com/YobHDOKRS6
— TESLARATI (@Teslarati) July 26, 2026
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Instead, the car will drive over one of the dashed road lines, and the steering wheel will jerk back and forth before picking the lane. It should be said that it has always picked the correct lane when choosing based on the navigation, but it is still very indecisive. The steering wheel jerking is reminiscent of some of the later versions of v13.
I admit I really hate to see the steering wheel jerking come back. However, I think when Tesla releases v14.3.7, it won’t be present. When there are occurrences of it in FSD versions, it is usually resolved by the following release.
FSD Disregards Manual Turn Signals
This is my biggest bone to pick with FSD other than Navigation issues, but this one seems like it would be such an easy fix.
If Tesla is going to put the word “Supervised” on the end of “Full Self-Driving,” then when I tell the car to do something, it should do it. If I input an increase in speed by pressing the accelerator, the car will immediately respond. It does not disregard my input because it feels it is traveling at the right speed.
FSD should never disobey and turn off turn signals that the driver inputs. Trying to direct the car into the correct lane, I had initiated the left turn signal not once, not twice, but three times, with the car turning it off all three times and continuing in a lane that would end in just one block. The only solution at this point would be to zipper merge.
This goes back to the fact that self-driving’s biggest bottleneck might be rider preference. A zipper merge might have been more than reasonable, might have saved me time that I spent sitting through an additional light cycle, and might be something many drivers would do. I was in no hurry, I traditionally do not try to zipper merge because it feels inconsiderate, and lastly, the car should have just followed my input.
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This caused me to disengage and drive manually the rest of the way home. Sometimes I just do not need FSD to try to pass every car it can at intersections.
Bird Braking is a Thing of the Past
The big complaint with recent versions of Full Self-Driving has been what we’ve coined as “bird braking,” which is when the car will brake suddenly as a bird flies past.
There have been zero issues with this so far in v14.3.6, which is an excellent improvement.
FSD Might Already Be Taking Note of Driver Preferences
Another thing I have noticed over the past few days is that v14.3.6 seems to already be taking my preferences with navigation into account.
This is something that is supposed to be rolling out with the Summer Update, but I have a hunch it’s already present and might have been included in this v14.3.6 build. On Friday, FSD pulled into an entrance to a local convenience store that it had never attempted to go into before.
Typically, I manually pull into this entrance because it avoids heavy cross traffic at the main entrance. FSD has always chosen that congested main entrance.
I don’t want to get anyone excited but my Tesla running FSD v14.3.6 just:
✅ Pulled into an entrance at my local Sheetz that I routinely pull into manually but FSD never has entered
-✅ Pulled into my assigned parking space at home despite many other spots being vacant https://t.co/ZUShvknTWO pic.twitter.com/83O5a2S0eh
— TESLARATI (@Teslarati) July 24, 2026
Additionally, FSD has pulled into my assigned parking spot at my townhouse community on multiple occasions with this release. This is something that used to happen ocassionally, but not consistently.
It also navigated back to the same convenience store last night, drove through crazy cars scrambling to gas pumps, navigated out of the parking lot correctly, drove me home, and, once again, parked in my assigned spot.
As previously stated, this release just seems to have a few things that need to be brought to Tesla’s attention, and also to make others who use FSD aware of some things that I’ve experienced. I look forward to the next release that will remedy these issues, just as Tesla has always done in the past.
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Tesla briefly offered this Robotaxi part for your personal car
Tesla Robotaxi gets sweeping but polarizing change
