Musk: Tesla Revives Dojo3 for Orbital AI Computing - AI News Today Recency

# Musk: Tesla Revives Dojo3 for Orbital AI Computing

Elon Musk has announced that Tesla is restarting development of its Dojo3 supercomputer, marking a significant strategic shift in the company's artificial intelligence infrastructure. Unlike previous iterations focused on terrestrial AI training, the revived Dojo3 will be dedicated to space-based AI compute, positioning Tesla to expand its computational capabilities beyond Earth-bound data centers.

Tesla's AI Chip Roadmap Enables Dojo3 Restart

The decision to resurrect Dojo3 comes as Tesla's AI5 chip design has reached a stable development stage, freeing up engineering resources that were previously allocated elsewhere. According to Musk's announcement, the AI5 chip—designed by TSMC and built to power Tesla's automated driving features and Optimus humanoid robots—is now "in good shape," enabling the company to pivot resources back to the long-dormant supercomputer project.[1][2]

Tesla's AI roadmap is accelerating rapidly, with the company targeting a nine-month design cycle for its next-generation chips.[3] The AI5 chip delivers what Musk describes as Hopper-class performance on a single chip and Blackwell-class performance when two chips work together, while consuming significantly less power than competing solutions.[2] Following AI5, Tesla is developing AI6 and AI7 chips as part of this aggressive timeline, with AI7/Dojo3 specifically earmarked for space-based applications.[1][3]

From Terrestrial to Orbital: The New Vision for Dojo3

Musk's revelation that Dojo3 will focus on "space-based AI compute" represents a dramatic reimagining of the project's purpose.[1] Unlike Dojo2, which incorporated a mixture of Tesla's in-house chips alongside Nvidia AI GPUs, Dojo3 will be the first Tesla-built supercomputer to utilize purely in-house hardware, with no reliance on external partners like Nvidia.[2]

This shift marks Tesla's renewed ambition in large-scale AI training after the company had previously stepped back from the Dojo initiative in late 2025, citing resource constraints across multiple AI chip architectures.[3] The decision to revive the project signals confidence in Tesla's ability to develop competitive AI infrastructure independently. The company is now actively recruiting engineers to rebuild the team it had dismantled, with Musk posting a direct appeal on X for specialists interested in "what will be the highest volume chips in the world."[1]

Strategic Competition and Market Implications

The timing of Dojo3's revival carries strategic significance in the competitive landscape of autonomous driving technology. At CES 2026, Nvidia unveiled Alpamayo, an open-source AI model for autonomous driving that directly challenges Tesla's Full Self-Driving software.[1] Musk acknowledged the competitive pressure, noting that solving the "long tail of rare edge cases in driving is super hard," though he expressed hope that Nvidia would succeed in its efforts.[1]

Tesla's dual-track approach—advancing in-car inference through AI5 and AI6 chips while simultaneously building large-scale training capacity through Dojo3—positions the company to maintain control over its autonomous driving technology stack.[4] This closed-loop strategy combines in-house hardware, a camera-first software architecture, and data from Tesla's extensive vehicle fleet, creating what the company views as a competitive advantage against traditional competitors and tech companies entering the autonomous vehicle space.[4]

The success of Dojo3 will be critical for Tesla's future. Previous iterations, including Dojo1 and the cancelled Dojo2, failed to achieve their ambitious goals due to competition from Nvidia and other technical challenges.[2] However, with Tesla's improved chip designs and renewed commitment, Dojo3 has the potential to become the company's first truly successful supercomputer for large-scale AI training.[2]

Frequently Asked Questions

What is Dojo3 and why is Tesla reviving it?

Dojo3 is Tesla's third-generation supercomputer designed for large-scale AI training. Tesla abandoned the original Dojo initiative in late 2025 to consolidate resources, but the company is now reviving it with a new purpose: supporting space-based AI compute operations.[1][3] The restart became possible once Tesla's AI5 chip design reached a stable development stage.[1]

How is Dojo3 different from previous Dojo iterations?

Dojo3 will be Tesla's first supercomputer built entirely with in-house hardware, eliminating reliance on external partners like Nvidia.[2] Previous versions, such as Dojo2, used a mixture of Tesla's proprietary chips and Nvidia AI GPUs.[2] Additionally, Dojo3 is specifically designed for space-based applications rather than traditional Earth-bound data center operations.[1]

What does "space-based AI compute" mean?

While Musk has not provided extensive details, "space-based AI compute" indicates that Dojo3 will support artificial intelligence operations conducted from orbital platforms or satellites.[1][2] This represents an ambitious expansion of Tesla's computational infrastructure beyond terrestrial facilities, though the specific applications remain to be fully disclosed.[5]

How does Dojo3 fit into Tesla's broader AI strategy?

Tesla's AI strategy encompasses both in-car inference and large-scale training. AI5 and AI6 chips focus on running Full Self-Driving neural networks inside vehicles, while Dojo3 will handle the massive computational demands of training advanced AI models.[3][4] This integrated approach allows Tesla to maintain control over its autonomous driving technology from hardware design through deployment.[4]

What is Tesla's chip development timeline?

Tesla is targeting a nine-month design cycle for its next-generation AI chips, including AI7, AI8, and AI9.[3] The AI5 chip is nearly complete, AI6 is already in early development, and AI7 will power Dojo3.[1][3] This aggressive timeline suggests that Dojo3 deployment could occur sooner than traditional supercomputer development cycles would typically allow.[3]

Is Tesla's Dojo3 project likely to succeed?

Success is uncertain but possible. Previous Dojo iterations failed to achieve their ambitious goals due to Nvidia competition and technical challenges.[2] However, Tesla's improved AI5 chip design—which delivers competitive performance with significantly lower power consumption—suggests the company has made genuine technological progress.[2] Investors and industry observers will closely monitor whether Dojo3 produces measurable training capacity and whether it accelerates Tesla's real-world autonomy progress.[4]