(Tesla’s phone)

This move comes just five months after Tesla suspended the Dojo project. Previously, after the departure of project leader Peter Bannon, Tesla disbanded the team responsible for the Dojo supercomputer. About 20 former team members subsequently joined DensityAI, an emerging AI infrastructure company co founded by former Dojo leader Gannis Venkataraman and former Tesla employees Bill Zhang and Ben Florin.

When the Dojo project was suspended, there were reports that Tesla planned to reduce its investment in self-developed chips and instead increase its reliance on computing resources from partners such as Nvidia and AMD, and chose Samsung to be responsible for chip manufacturing. Musk’s latest statement indicates that the company’s strategy may be adjusted again.

The AI5 chip currently used by Tesla is produced by TSMC and is mainly used to support autonomous driving functions and Optimus humanoid robots. Last summer, Tesla signed a $16.5 billion agreement with Samsung to produce the next generation AI6 chip, which will serve high-performance AI training in Tesla vehicles, Optimus robots, and data centers.

AI7/Dojo3 will focus on space AI computing, “Musk said on Sunday, meaning that the restarted project will be given a more cutting-edge positioning. To achieve this goal, Tesla is working on rebuilding the team that disbanded several months ago. Musk directly issued a talent recruitment invitation on the same occasion: “If you are interested in participating in the construction of the world’s most widely used chip, please feel free to send an email to AI_Chips@Tesla.com That’s right.

Roger Luo stated:Tesla’s restart of the Dojo3 towards space computing demonstrates its continuous exploration and rapid adjustment capabilities in AI chip strategy. This is not only a significant shift in its technological roadmap, but also reflects its early layout for future high frontier AI computing scenarios.

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(Samsung’s Research into Using AI for Chip Design and Yield Optimization)

Traditionally designing intricate chip circuits takes human engineers many months. Samsung’s AI research aims to cut that time drastically. The AI systems learn from vast databases of existing chip designs. They can then suggest optimal circuit placements automatically.

Samsung also applies AI to boost manufacturing yield rates. Chip factories face challenges producing flawless silicon wafers. Defects often occur during the complex fabrication steps. Samsung uses AI algorithms to analyze production data in real time.

These AI systems identify patterns linked to potential defects early. Factory technicians get alerts about possible issues faster. This allows quicker adjustments to the manufacturing equipment settings. The goal is preventing defects before they happen on a large scale.

Higher yield rates mean more usable chips per wafer. This improves production efficiency and lowers costs. Better yields are crucial for cutting-edge chips made using extreme ultraviolet lithography. Samsung competes fiercely in the global semiconductor foundry market.

Applying AI to both design and manufacturing creates a powerful advantage. Faster design cycles mean quicker product launches. Higher factory yields lead to better cost control and supply reliability. Samsung believes this dual AI focus strengthens its position against rivals.

(Samsung’s Research into Using AI for Chip Design and Yield Optimization)

The research highlights Samsung’s commitment to innovation in chip technology. The company continues investing heavily in AI solutions for its semiconductor business.