Tesla chief Elon Musk redirects AI talent after Dojo shutdown

After Dojo’s shutdown on August 7, employees have been redistributed across different teams within Tesla. This change follows about 20 people leaving Tesla to launch their own AI company, DensityAI.

Agencies
Days after tech billionaire Elon Musk announced the shutdown of Tesla’s in-house artificial intelligence (AI) training platform Dojo, the company has reportedly reassigned its engineering staff, Bloomberg reported on Wednesday.

Dojo’s shutdown on August 7 led to employees being redistributed across different teams within Tesla.

The report added that several software-focussed personnel now report to Ashok Elluswamy, who leads Tesla’s artificial intelligence (AI) efforts across robotaxis and humanoid robots.


Additionally, engineers in the semiconductor unit report to Aaron Rodgers, who oversees hardware for Tesla’s autonomous driving efforts, whereas firmware staff are led by Silvio Brugada, who has taken charge of the security engineering role at the EV giant.

ET reported on August 8 that Dojo’s team leader, Peter Bannon, is leaving the company and that other team members will be moved to other data centres and computing projects at Tesla.

This change came after about 20 people left Tesla to launch their own AI company, DensityAI. The startup was founded by former Dojo head Ganesh Venkataramanan and ex-Tesla engineers Bill Chang and Ben Floering.
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Shutting down Dojo marks a big change in Tesla’s strategy. Musk had long said that Dojo would be key to the company’s AI goals and its path to full self-driving. He even mentioned it briefly during Tesla’s second quarter earnings call, according to TechCrunch.

Also Read: Tesla gets Texas robotaxi license amid safety lawsuit, Dojo shutdown

Elon Musk said in a post on X that it no longer made sense to split resources between two AI chip architectures, adding that the focus will now be on Tesla’s own AI5 and AI6 chips.

Tesla signed a major $16.5 billion deal to source chips from Samsung Electronics. These chips are expected to power its self-driving cars, humanoid robots, and data centres.
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