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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
“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.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
