#黄金白银反弹
Tesla's chip layout expansion is not a direct challenge to Nvidia; the two are not in the same race. The core misconception of the issue lies in assuming that Tesla develops chips for commercial competition and chip sales, which is not the case. Tesla has been developing its own FSD, Dojo, and other AI chips for many years, and their computing power serves internal workloads, primarily for autonomous driving and robotics training. Chip design is merely a production tool for the company, not a route to commercialize computing power in the market. Tesla's insistence on in-house development stems from three practical constraints: highly customized computing power demands, training rhythms dictated by product iterations, and uncontrollable long-term computing costs. General-purpose GPUs can only address some of these issues. Nvidia's GPUs, on the other hand, are a general computing power platform aimed at cloud vendors, and the chip R&D positioning and application scenarios of the two are entirely different, with no direct market competition relationship. $BNB