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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.
Elon Musk
Tesla AI boss reveals how big Optimus is going to get
Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.
![Tesla Optimus Gen 3 [Credit: Tesla]](https://www.teslarati.com/wp-content/uploads/2026/03/tesla-optimus-gen3-diner.jpg)
Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”
The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.
The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.
Correction, 10 million robots https://t.co/0z4nyQNTzp
— Ashok Elluswamy (@aelluswamy) July 30, 2026
Tesla Optimus project fires up as Musk sees production line progress
Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.
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Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.
The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.
The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.
Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.
There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.
Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:
- Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances. - Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years. - Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant. - Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS). - Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.
Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:
- FMVSS 102 – Transmission shifting
- FMVSS 103/104 – Windshield defrosting and wiping
- FMVSS 110 – Tire placards
- FMVSS 135 – Braking systems
- FMVSS 101 – Controls and displays
- FMVSS 108 – Vehicle lighting
- FMVSS 111 – Mirrors and rearview display
- FMVSS 126 – Electronic stability control systems
- FMVSS 201/208 – Sun visors and warning labels
These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.
Elon Musk is, in many respects, one of the biggest and most influential figures in modern-day artificial intelligence.
Given that Tesla, SpaceX, and xAI are all looked at in their respective fields as leaders to an extent, each of them has a heavy influence on the future of AI, even though two of them are not thought of, at face value, as AI companies.
Musk has grand expectations for what is to come with AI, not only as a form of assistance to make human lives easier, but to make humans multiplanetary and solve some of the biggest issues that face us today. But even he is astounded by AI’s pace of progress.
He believes that in two years, AI will be so mind-blowing it might be unrecognizable.
Given that AI from 2 years ago feels so old that it should be in a museum, then obviously AI 2 years from now will be mind-blowing https://t.co/TcsKZ8o8OE
— Elon Musk (@elonmusk) July 30, 2026
This progress can be seen in a variety of ways, but perhaps the most popular way people have shown AI’s progress, especially on social media, is through an incredibly arbitrary way of watching Will Smith eat spaghetti:
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The progression in AI of Will Smith eating spaghetti (2023 – 2026) pic.twitter.com/VDv82mB5gs
— internet hall of fame (@InternetH0F) February 10, 2026
This is a great way to show people how AI is improving, especially from a perspective that examines how it can manufacture images and video from prompts. AI is an incredibly complex concept, however, and it goes much deeper than Will Smith eating Italian food.
Musk’s most widely adopted method of AI is likely Tesla Full Self-Driving, which impacts millions of people as they utilize it to increase safety with their travel. Musk has routinely pushed incredibly aggressive timelines for self-driving, especially unsupervised.
Perhaps this perspective is why he feels that things will be solved in a timeframe that is much more aggressive than most of us would think. Regardless, the progress of AI is moving fast, and it seems that Musk’s expectations for it could be high.
But if it can actually achieve full-length motion pictures and even more realistic production value, it will be hard to distinguish between reality and AI very soon.
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![Tesla Optimus Gen 3 [Credit: Tesla]](https://www.teslarati.com/wp-content/uploads/2026/03/tesla-optimus-gen3-diner-80x80.jpg)
Tesla AI boss reveals how big Optimus is going to get
Autonomous vehicle red tape gets slashed by Trump Administration
