Tesla(US:TSLA) 3 6 Ke·2026-01-21 07:45Core Insights - Tesla's CEO Elon Musk announced the revival of the previously shelved supercomputer project Dojo 3, marking a significant shift in Tesla's chip strategy [1][2] - The new mission of Dojo 3 will expand beyond training autonomous driving models on Earth to include "space artificial intelligence (AI) computing" [1][6] Group 1: Dojo 3 Project Overview - Dojo 3 was initially designed as a supercomputer for machine learning training, first introduced during Tesla's AI Day in 2021 [4] - The project aims to restructure its architecture and optimize costs, moving away from the complex paths of previous generations that relied on in-house D1 chips [4] - Musk hinted that the future of Dojo will involve a cluster architecture integrating numerous AI6 chips rather than developing dedicated training systems [4] Group 2: Strategic Shifts and Partnerships - Five months prior, Tesla halted the Dojo 3 project, disbanded its core team, and shifted focus to AI5, AI6, and subsequent chips, which can handle both efficient inference and core training tasks [2] - Tesla plans to increase reliance on Nvidia and other partners like AMD for computing, as well as on Samsung for chip manufacturing, rather than continuing to develop custom chips [2][5] - The AI5 chip is manufactured by TSMC and is intended to power Tesla's autonomous driving features and the Optimus humanoid robot [5] Group 3: Space AI Vision - Musk's latest statements indicate a vision for deploying AI computing centers in space, which he believes will be more cost-effective than terrestrial systems within four to five years [6][7] - The rationale includes the availability of "free" solar energy and relatively easier cooling technologies in space [6] - Musk's involvement in xAI, SpaceX, and Tesla creates a synergistic potential for these ventures, positioning Tesla as a major beneficiary if successful [6] Group 4: Challenges Ahead - Despite the ambitious goals, significant obstacles remain for establishing space-based AI data centers, including orbital debris, regulatory approvals, and international space policies [9] - Cooling high-power computing devices in a vacuum presents challenges, as temperature fluctuations in space can be extreme [9][10] - Constructing large AI data centers in geostationary orbit will require massive heat dissipation structures, which pose logistical and cost challenges [10]