阿尔法工场研究院·2025-08-20 00:04Core Viewpoint - The closure of Tesla's Dojo supercomputer project, which had significant investment and was initially seen as a key to achieving full self-driving capabilities, reflects a shift in strategy towards leveraging existing industry solutions rather than pursuing vertical integration in AI technology [4][10][12]. Group 1: Project Closure and Financial Implications - Tesla's Dojo project was officially shut down after over $1 billion in investment, marking a significant pivot in its approach to AI technology [4][10][13]. - The company plans to spend tens of billions on NVIDIA AI chips, increasing its stock from 35,000 to 85,000 units by the end of 2025 [13][30]. Group 2: Challenges of Vertical Integration - The ambitious design of Dojo's chip architecture faced significant challenges, including heat dissipation, power consumption, and system stability, which hindered its performance [16][18]. - Tesla's attempt to create a new chip and software stack simultaneously proved to be an extremely difficult challenge, leading to the project's failure to meet performance targets [16][18]. Group 3: Industry Dynamics and Strategic Shift - The closure of Dojo highlights a broader trend in the AI industry where companies are recognizing the importance of platform ecosystems over isolated technological breakthroughs [21][28]. - NVIDIA's CUDA software ecosystem has become a dominant force in AI development, making it difficult for new entrants to compete without a similar platform [22][23][27]. - By outsourcing its computing infrastructure to NVIDIA, Tesla can refocus its engineering efforts on neural network algorithms and data processing, aligning with the industry's shift towards platform-based competition [27][28][30].