Tesla has reportedly disbanded its Dojo supercomputer team, signalling a shift in the company’s approach to AI development.
Peter Bannon, the head of the Dojo initiative, is leaving the company, reported Bloomberg citing people familiar with the matter.
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This decision comes as Tesla aims to enhance its collaboration with external technology partners, including Nvidia, Advanced Micro Devices, and Samsung Electronics, for computing and chip manufacturing needs.
The Dojo project aimed to be a key element of Tesla’s strategy for developing in-house chips for autonomous driving technology.
However, recent reports indicate that the team has lost approximately 20 employees to a new venture called DensityAI, which is focused on AI hardware and software for various applications, including robotics and automotive sectors.
Remaining members of the Dojo team are being reassigned to other data centre and computing projects within Tesla.
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By GlobalDataOn X platform, Elon Musk said “that doesn’t make sense for Tesla to divide its resources and scale two quite different AI chip designs.
“The Tesla AI5, AI6 and subsequent chips will be excellent for inference and at least pretty good for training. All effort is focused on that.”
The Dojo supercomputer was designed to train machine-learning models for Tesla’s Autopilot and Full Self-Driving systems, as well as its Optimus humanoid robot, utilising a custom chip known as the D1.
So far in 2025, Tesla has seen a notable departure of key personnel including Milan Kovac, head of engineering for Optimus, and David Lau, vice president of software engineering.
In a recent agreement, Tesla secured a $16.5bn deal with Samsung to obtain AI semiconductors through 2033, with plans for a new facility in Texas to manufacture the next-generation AI6 chip.
This move diversifies the company’s supply chain beyond Taiwan Semiconductor Manufacturing.
DensityAI, founded by former Dojo head Ganesh Venkataramanan along with ex-Tesla employees, is preparing to emerge from stealth mode.
The company aims to develop chips and infrastructure for AI data centres.
