Tesla plans to revive its Dojo supercomputer project, but this time focusing on "space-based AI compute" rather than training self-driving models on Earth, according to a recent statement by Elon Musk on X. The move represents a significant shift in strategy for the electric vehicle company, which had effectively shut down its Dojo effort just five months prior.
The decision to restart Dojo3, Tesla's third-generation AI chip, is based on the progress of its in-house chip roadmap, specifically the AI5 chip design, Musk stated. "AI5 chip design is in good shape," he wrote on X, implying confidence in the company's ability to develop custom silicon for AI applications.
Tesla's initial Dojo program faced setbacks, including the departure of Dojo lead Peter Bannon and the subsequent disbanding of the team behind the supercomputer. Around 20 Dojo employees left to form DensityAI, an AI infrastructure startup founded by former Dojo head Ganesh Venkataramanan and ex-Tesla employees Bill Chang and Ben Floering.
Following the shutdown, reports indicated that Tesla intended to increase its reliance on Nvidia, AMD, and Samsung for compute and chip manufacturing. This suggested a move away from developing its own custom silicon, a strategy that now appears to be reversed, at least for space-based applications.
The specific applications of "space-based AI compute" remain unclear, but potential uses could include autonomous satellite operations, on-orbit data processing, and advanced image recognition for Earth observation. Such applications demand high performance and energy efficiency, potentially justifying the development of custom silicon optimized for these constraints.
The revival of Dojo raises questions about Tesla's overall AI strategy and its long-term vision for both terrestrial and extraterrestrial applications. While the company has not released detailed specifications for the AI5 chip, its performance will be critical in determining the success of the revived Dojo project. The industry will be watching closely to see how Tesla's renewed focus on in-house chip development impacts its competitive position in the rapidly evolving AI landscape.
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