
Tesla has officially stepped back from its Dojo supercomputer initiative aimed at enhancing its Full Self-Driving (FSD) capabilities and other advanced features. The company is now pivoting towards increased collaboration with established tech partners such as NVIDIA and AMD.
Tesla Plans to Expand External Collaborations with NVIDIA & AMD
The Dojo project initially aimed to revolutionize the supercomputer field, targeting mainstream applications. By leveraging collaborations with chipset manufacturers like TSMC, Tesla sought to develop hardware that could amass substantial computing power to support its autonomous vehicle initiatives, including both self-driving technology and humanoid robotic systems. However, a recent Bloomberg report reveals that Tesla has decided to disband its Dojo supercomputer team, coinciding with the departure of team lead Peter Bannon, who is launching his own venture, DensityAI.
This transition has reportedly led to the exit of about 20 employees to Bannon’s new startup. Consequently, the remaining workforce from the Dojo team has been reassigned to Tesla’s data center projects. Significantly, Tesla’s strategy now encompasses greater reliance on external partnerships to secure the computing power essential for their FSD advancements. This decision comes amidst fierce competition in the AI sector and a notable talent exodus from the Dojo project.

The report highlights that Ganesh Venkataramanan, who previously led the Dojo team, has also joined Bannon at DensityAI, further depleting Tesla’s resources. Despite this setback, Elon Musk remains optimistic about Tesla’s trajectory in the AI landscape, particularly with the initiatives at xAI, which is gearing up to meet the computational demands for AI-driven features within Tesla’s ecosystem. As part of this strategy, xAI is developing substantial hyperscalers in the United States to bolster these needs.
With the Dojo program now defunct, attention turns to Tesla’s recent agreement with Samsung for the AI6 chips. This partnership is poised to play a crucial role in Tesla’s ongoing quest to advance its semiconductor capabilities for AI applications.
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