Tesla’s Chip & Dojo Supercomputer Chief Exits—Elon’s AI Ambitions Hit a Speed Bump

Tesla's silicon brain drain continues as its chip and Dojo supercomputer lead walks out—right as competitors rev up their AI engines.

Another 'production hell' for Musk? The departure throws a wrench into Tesla's in-house AI chip dreams, which were supposed to cut reliance on Nvidia and save billions (or at least impress Wall Street between earnings misses).

Dojo's now dancing solo. The custom supercomputer—Tesla's bet to process millions of self-driving videos—just lost its choreographer. Timing couldn't be worse: legacy automakers are finally getting their act together on autonomy.

Bonus jab: Maybe the exec sold his Tesla stock at the top and realized teaching cars to drive is harder than tweeting memes.

Musk orders reboot of AI strategy

Elon Musk is changing Tesla’s AI strategy. Instead of developing its own computing hardware, Tesla will outsource more to vendors like Nvidia, AMD, and Samsung.

The deal signed with Samsung by Tesla for its future-gen A16 AI chips is estimated at $16.5 billion. The company is also rapidly ramping up using Nvidia’s AI training high-performance GPUs.

The move is a significant departure from Musk’s initial vision for Dojo, which was intended to become the AI equivalent of Tesla’s well-regarded Supercharger network and a point of differentiation that WOULD help it outpace rivals. 

The Dojo project has faced technical challenges and delays since its unveiling in 2021.

Many engineers who worked on the system have left the company. Around 20 have already moved on to launch an AI startup called DensityAI.

Tesla’s decision to close the Dojo team effectively ends its in-house supercomputing push. The company will now channel resources into other AI infrastructure and driver-assistance projects.

On the company’s July earnings call, Musk had said Tesla expected the latest Dojo version to run at scale next year. But the abrupt shutdown suggests priorities have shifted.

Tesla eyes partnerships for compute needs

The service marks a shift for Tesla, which, up until now, has been doing all training computing internally. Most of the heavy lifting will be done by Nvidia’s latest GPUs. AMD is also likely to contribute processing for some projects.

Samsung will play a key role in Tesla’s chip production. It’s a way for Tesla to tap into state-of-the-art hardware at little risk and cost instead of just building its gargantuan supercomputers from scratch. 

The move comes as Tesla tests limited Robotaxi services in Austin and San Francisco. In Austin, a human safety supervisor still rides in the passenger seat. In San Francisco, human drivers operate the vehicles while users hail them through a “Tesla Robotaxi” app.

Tesla has seen an exodus of senior talent this year, with the departure of Bannon adding to the list. Former Optimus robotics head Milan Kovac, software VP David Lau, and Musk’s former chief of staff Omead Afshar have also left.

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