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Tesla’s newest Autopilot Vision head: Who is Andrej Karpathy?

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The EV world was rocked when it was announced that Tesla replaced its Vice President of Autopilot Software, Chris Lattner, with Andrej Karpathy. Karpathy is the company’s new Director of AI and Autopilot Vision, but who he is?

Karpathy most recently worked as a research scientist with Elon Musk’s OpenAI, specializing in deep neural networks.

He also had three summer stints at Google. In 2011 and 2013, Karpathy interned for the tech behemoth working on large scale deep learning and video content analysis. In 2015, he was with Google DeepMind, focusing on deep reinforcement learning.

In 2009, Karpathy graduated from University of Toronto with a Bachelor’s of Science in computer science and in physics. From there, he went to the University of British Columbia and got Master’s Degree in computer science and researched motor control, primarily learning controllers for physically simulated figures.

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After finishing graduate school in 2011, Karpathy went to Stanford University to pursue a Ph.D in computer science. He researched machine learning, with an emphasis on deep learning for computer vision and natural language processing. He worked under adviser Fei-Fei Li, the director of Stanford’s AI lab and chief director of Google Cloud. According to his Stanford profile, Karpathy graduated in 2015 before jumping to Google DeepMind and eventually OpenAI.

Karpathy has been published in scholarly journals and for conferences, including the International Conference on Learning Representations. He also published a couple of blogs to keep his followers posted on research development and a lighter one on topics such as a survival guide to a Ph.D.

In February of this year he joined the steering committee of distill.pub, a journal focusing on machine learning research.

Karpathy will report directly to Musk, and work closely with chip expert and Vice President of Autopilot Hardware Jim Keller on advancing Tesla’s self-driving technology.

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Tesla released the following statement regarding the hiring of Karpathy:

Andrej Karpathy, one of the world’s leading experts in computer vision and deep learning, is joining Tesla as Director of AI and Autopilot Vision, reporting directly to Elon Musk. Andrej has worked to give computers vision through his work on ImageNet, as well as imagination through the development of generative models, and the ability to navigate the internet with reinforcement learning. He was most recently a Research Scientist at OpenAI.

Andrej completed his computer vision PhD at Stanford University, where he demonstrated the ability to derive complex descriptions of images using a deep neural net. For example, identifying not simply that there is a cat in a given picture, but that it is an orange, spotted cat, riding on a skateboard with red wheels on brown hardwood flooring (http://cs.stanford.edu/people/karpathy/main.pdf). He also created and taught “Convolutional Neural Networks for Visual Recognition,” the first and still leading deep learning course at Stanford.

Andrej will work closely with Jim Keller, who now has overall responsibility for Autopilot hardware and software.

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To see Karpathy in action discussing deep learning, check him out here:

Interim East Coast Editor for Teslarati, contributor for NextMobility. Share tips at mdolzer@teslarati.com

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Elon Musk

Tesla owners surpass 8 billion miles driven on FSD Supervised

Tesla shared the milestone as adoption of the system accelerates across several markets.

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Credit: Tesla

Tesla owners have now driven more than 8 billion miles using Full Self-Driving Supervised, as per a new update from the electric vehicle maker’s official X account. 

Tesla shared the milestone as adoption of the system accelerates across several markets.

“Tesla owners have now driven >8 billion miles on FSD Supervised,” the company wrote in its post on X. Tesla also included a graphic showing FSD Supervised’s miles driven before a collision, which far exceeds that of the United States average. 

The growth curve of FSD Supervised’s cumulative miles over the past five years has been notable. As noted in data shared by Tesla watcher Sawyer Merritt, annual FSD (Supervised) miles have increased from roughly 6 million in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and 4.25 billion in 2025. In just the first 50 days of 2026, Tesla owners logged another 1 billion miles.

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At the current pace, the fleet is trending towards hitting about 10 billion FSD Supervised miles this year. The increase has been driven by Tesla’s growing vehicle fleet, periodic free trials, and expanding Robotaxi operations, among others.

Tesla also recently updated the safety data for FSD Supervised on its website, covering North America across all road types over the latest 12-month period.

As per Tesla’s figures, vehicles operating with FSD Supervised engaged recorded one major collision every 5,300,676 miles. In comparison, Teslas driven manually with Active Safety systems recorded one major collision every 2,175,763 miles, while Teslas driven manually without Active Safety recorded one major collision every 855,132 miles. The U.S. average during the same period was one major collision every 660,164 miles.

During the measured period, Tesla reported 830 total major collisions with FSD (Supervised) engaged, compared to 16,131 collisions for Teslas driven manually with Active Safety and 250 collisions for Teslas driven manually without Active Safety. Total miles logged exceeded 4.39 billion miles for FSD (Supervised) during the same timeframe.

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The Boring Company’s Music City Loop gains unanimous approval

After eight months of negotiations, MNAA board members voted unanimously on Feb. 18 to move forward with the project.

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(Credit: The Boring Company)

The Metro Nashville Airport Authority (MNAA) has approved a 40-year agreement with Elon Musk’s The Boring Company to build the Music City Loop, a tunnel system linking Nashville International Airport to downtown. 

After eight months of negotiations, MNAA board members voted unanimously on Feb. 18 to move forward with the project. Under the terms, The Boring Company will pay the airport authority an annual $300,000 licensing fee for the use of roughly 933,000 square feet of airport property, with a 3% annual increase.

Over 40 years, that totals to approximately $34 million, with two optional five-year extensions that could extend the term to 50 years, as per a report from The Tennesean.

The Boring Company celebrated the Music City Loop’s approval in a post on its official X account. “The Metropolitan Nashville Airport Authority has unanimously (7-0) approved a Music City Loop connection/station. Thanks so much to @Fly_Nashville for the great partnership,” the tunneling startup wrote in its post. 

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Once operational, the Music City Loop is expected to generate a $5 fee per airport pickup and drop-off, similar to rideshare charges. Airport officials estimate more than $300 million in operational revenue over the agreement’s duration, though this projection is deemed conservative.

“This is a significant benefit to the airport authority because we’re receiving a new way for our passengers to arrive downtown at zero capital investment from us. We don’t have to fund the operations and maintenance of that. TBC, The Boring Co., will do that for us,” MNAA President and CEO Doug Kreulen said. 

The project has drawn both backing and criticism. Business leaders cited economic benefits and improved mobility between downtown and the airport. “Hospitality isn’t just an amenity. It’s an economic engine,” Strategic Hospitality’s Max Goldberg said.

Opponents, including state lawmakers, raised questions about environmental impacts, worker safety, and long-term risks. Sen. Heidi Campbell said, “Safety depends on rules applied evenly without exception… You’re not just evaluating a tunnel. You’re evaluating a risk, structural risk, legal risk, reputational risk and financial risk.”

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Tesla announces crazy new Full Self-Driving milestone

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

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Credit: Tesla

Tesla has announced a crazy new Full Self-Driving milestone, as it has officially confirmed drivers have surpassed over 8 billion miles traveled using the Full Self-Driving (Supervised) suite for semi-autonomous travel.

The FSD (Supervised) suite is one of the most robust on the market, and is among the safest from a data perspective available to the public.

On Wednesday, Tesla confirmed in a post on X that it has officially surpassed the 8 billion-mile mark, just a few months after reaching 7 billion cumulative miles, which was announced on December 27, 2025.

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

The milestone itself is significant, especially considering Tesla has continued to gain valuable data from every mile traveled. However, the pace at which it is gathering these miles is getting faster.

Secondly, in January, Musk said the company would need “roughly 10 billion miles of training data” to achieve safe and unsupervised self-driving. “Reality has a super long tail of complexity,” Musk said.

Training data primarily means the fleet’s accumulated real-world miles that Tesla uses to train and improve its end-to-end AI models. This data captures the “long tail” — extremely rare, complex, or unpredictable situations that simulations alone cannot fully replicate at scale.

This is not the same as the total miles driven on Full Self-Driving, which is the 8 billion miles milestone that is being celebrated here.

The FSD-supervised miles contribute heavily to the training data, but the 10 billion figure is an estimate of the cumulative real-world exposure needed overall to push the system to human-level reliability.

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