Elon Musk, CEO of Tesla, recently published a lengthy post on a social platform, providing the first comprehensive overview of the company’s strategic layout in the field of artificial intelligence chips. He revealed that Tesla has assembled a chip R&D team with industry-leading capabilities and has deployed millions of self-developed AI chips in vehicle control systems and data centers. This technological accumulation has positioned the company as a benchmark for real-world AI applications globally.
According to the latest news, Tesla’s current in-vehicle chip version is AI4 (formerly HW4). Its iteration, AI5, has completed key design phases and is about to enter the tape-out stage, while R&D for the sixth-generation chip, AI6, has already commenced. The company plans to establish an annual chip update cycle, forming a complete technological iteration system. More notably, Musk claimed that Tesla’s future chip production capacity will surpass the total of all other global AI chip manufacturers combined, emphasizing that this goal is realistically achievable.
In terms of application scenarios, these specialized chips will primarily support two core businesses: the autonomous driving system and the Optimus humanoid robot. Musk specifically pointed out that autonomous driving technology, enhanced by increased chip computing power, could prevent millions of traffic accidents annually. Furthermore, medical robots equipped with advanced AI chips will expand access to high-quality medical services for a broader population. However, he did not disclose specific technical parameters or mass production timelines, only emphasizing that the chip strategy is the cornerstone of Tesla’s AI ecosystem.
To support this ambitious plan, Tesla has simultaneously initiated large-scale talent recruitment. Musk publicly invited top global chip engineers to join, requiring applicants to submit three case studies demonstrating their professional capabilities. The company is particularly focused on innovative talent capable of integrating cutting-edge AI technology into chip design. Industry analysts suggest that this move by Tesla aims to build end-to-end R&D capabilities from algorithms to hardware, consolidating its leading position in the fields of smart mobility and robotics.
