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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.

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.

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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.

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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SpaceX just locked up a NASA record no other U.S. spacecraft can touch

SpaceX’s Crew-13 Dragon reached the ISS in under eight hours, and NASA confirmed a record.

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SpaceX now owns every spot on the list of the five fastest trips a U.S. spacecraft has ever made to the International Space Station, and its newest entry beat the old mark by more than four hours.

Crew Dragon Grace docked to the forward port of the station’s Harmony module at 7:05 p.m. ET on October 1, just 7 hours and 55 minutes after lifting off from Space Launch Complex 40 at Cape Canaveral. NASA confirmed the milestone in a space station blog update, writing that the flight “marked the fastest launch‑to‑docking of a U.S. spacecraft in the history of the International Space Station.”

The previous U.S. record also belonged to Dragon. SpaceX’s uncrewed CRS-31 cargo mission reached the station in a little over 12 hours in November 2024. The fastest crewed trip before last week was Crew-11, which took 14 hours and 43 minutes in August 2025, according to Space.com.

A post that Elon Musk reposted on Monday filled out the rest of the ranking. Behind Crew-13, CRS-31 and Crew-11 sit Axiom’s Ax-2 mission at 15 hours and 35 minutes and NASA’s Crew-4 at 15 hours and 44 minutes. All five flew on Dragon.

SpaceX turned a heralding moment for Starship into its greatest

Crew-13 carried NASA astronauts Jessica Watkins and Luke Delaney, Canadian Space Agency astronaut Joshua Kutryk, and Roscosmos cosmonaut Sergey Teteryatnikov. NASA had projected a docking around 8 p.m. ET, as Teslarati reported the day before launch, and Dragon arrived nearly an hour early. Our launch day coverage noted that the flight was lined up to be the quickest Crew Dragon transit yet.

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The speed came from timing more than hardware. SpaceX’s Julianna Scheiman said the station “was in an opportune spot in space,” which let Dragon start closing the gap almost immediately after reaching orbit. “This is close to the fastest it could be,” she added. Most Crew Dragon flights still take close to a day, using a series of Draco thruster burns to raise and phase their orbit before arrival.

Dragon’s next job at the station is a departure. NASA said Monday it is targeting 8:05 a.m. ET on Wednesday, October 7, for Crew-12 to undock, setting up a splashdown off the coast of California around 11:34 a.m. on Thursday. Clearing that port makes room for CRS-35, a cargo Dragon carrying the final set of iROSA solar arrays.

Dragon remains NASA’s only operational ride to the station while Boeing’s Starliner stays grounded, and the agency recently added Crew-15, Crew-16 and Crew-17 to SpaceX’s contract in a $946 million modification.

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Elon Musk teases TSMC as potential Terafab partner

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SpaceX Terafab rendering
SpaceX Terafab rendering

Elon Musk has acknowledged that early discussions with Taiwan Semiconductor Manufacturing Company (TSMC) could bring the company into his ambitious Terafab semiconductor project, signaling a possible partnership with the world’s leading contract chipmaker.

Musk confirmed that early talks are underway, but as of right now, they are “just discussions.” There is no confirmation of a deal nor dismissal of the possibility of one, leaving open the prospect of one of the largest advanced-chip collaborations under discussion in the U.S.

The report that speculated on potential discussions between Terafab and TSMC comes from Tim Culpan, who outlined a few ways the collaboration could operate. One is TSMC using the project as an “anchor customer” for future facilities in Texas, potentially contributing process expertise, operational know-how, or capacity while Terafab provides capital, long-term purchase commitments, or both.

Tesla and SpaceX jointly developed the Terafab project, with Intel already participating on the tech side. Elon Musk announced the project in March, and it intends to produce more than one terawatt of AI compute capacity annually once fully built.

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Elon Musk’s Terafab project locks up massive new partner

Company statements place the first phase at approximately $16.8 billion in cost, with later filings pointing to a total that could reach well into the tens of billions across multiple stages.

Intel joined the effort in April 2026 and is expected to supply its 14A manufacturing process for the full-scale plant.

Musk has said existing suppliers, including Samsung and TSMC, remain important for near-term needs; Tesla already has production arrangements with Samsung for AI5 and AI6 chips, but that future demand from Optimus robots, Cybercab vehicles, and planned space-based data centers will eventually exceed what the global industry can currently deliver.

Terafab is positioned as the long-term answer to that projected shortfall, and Tesla did something similar during COVID to avoid a chip shortage. This is just a much larger-scale solution.

If the partnership were to materialize, it would add TSMC’s industry-leading strategies to a project that already combines Tesla’s and SpaceX’s capital and offtake with Intel’s process technology. For now, the only public confirmation is Musk’s brief acknowledgement that conversations are occurring.

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Tesla reveals early Robotaxi charging strategy, showing scrappy DNA

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Credit: Tesla

Tesla’s early strategy for charging units operating within its Robotaxi fleet reveals that the company surely has not lost any of that scrappy DNA that took it from an unlikely success story to the most valuable carmaker in the world.

An observer at a Tesla Supercharger in Austin spotted ten total Robotaxi vehicles arrive: one Cybercab and nine Model Y units. A Tesla employee was waiting at the lot and allowed each unit to park itself; every car that arrived had nobody in it.

Tesla wins FCC approval for wireless Cybercab charging system

The Tesla employee would walk around and plug each car in, adjusting the parking if needed:

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It’s a very interesting strategy, but extremely understandable at this early point in the Robotaxi program. It’s only been out for about 15 months, and Cybercab just entered the fleet in early September.

On top of that, Tesla is still working tirelessly on its wireless charging apparatus, and a new patent was just published regarding that product last week.

However, this is just another example of how Tesla still has plenty of that scrappy DNA leftover from the “production hell” days, when CEO Elon Musk slept on the floor of the factory, employees were working crazy hours, Tesla was building Sprung Structures to build cars in, and the company was tiptoeing on the brink of bankruptcy.

For now, Tesla is utilizing a simple system for recharging its ride-hailing vehicles, and that is a Tesla employee doing it manually until another solution presents itself. Sure, it’s not the most high-tech thing, and it certainly is not what people might have expected at this point in time, but it works, and it’s keeping the entire suite running.

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