.@ARKInvest has been wondering how much of a sleeper #Tesla’s Dojo is. Interesting perspective here.RimRunner (@samwose):@StockSavvyShay 1. Breaking Free from NvidiaTesla currently relies on Nvidia’s A100 and H100 GPUs for training its massive video-based neural networks. While powerful, these chips are general-purpose and optimized for broader markets like LLMs and gaming.Dojo 2, by contrast, is Tesla’s ...

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证券研究报告|专题研究 25年05月05日 华福证券 AI浪潮中，谁将盈利突围？ 证券分析师： 研究助理： 周浦寒 S0210524040007 杨逸帆 S0210124110046 请务必阅读报告末页的重要声明 华福证券 投资要点 风险提示：历史经验不代表未来;行业不确定性风险;国内经济复苏速度不及预期;海外降息节奏不及预 期;地缘政治风险。 2 华福证券 华福证券 "宏观叙事→股价驱动→财务筛选"方法论：我们认为，技术革命中主要受益的是三类"风口"公司 。对应股价，第一波行情驱动是估值，走出第二波行情多需要盈利验证。财务视角下，我们寻找到3 个领先盈利的信号。最终，希望筛选出：AI浪潮中，或将率先盈利、走出第二波行情的核心标的。 宏观叙事中，技术革命中3类"风口"上的公司或受益腾飞：1）上游"卖铲子"，2）技术新需求， 3）赋能全行业。而且，我们可以通过普及率、渗透率，观察产业的整体进展。 公司股价中，行情驱动或从估值转向盈利。第一波行情的股价多由估值驱动，而股价走出第二波行情 ，就需要得到公司业绩的验证。2次技术革命、3类"风口"公司，都验证了这一股价驱动因素的转变 。映射当下，多数AI公司或已上涨"估 ...

Group 1 - The core focus of the 2025 Shanghai International Auto Show is on automotive intelligence, with AI technology driving the shift from high-end to mainstream markets for intelligent driving assistance [1] - The competition in the automotive market has shifted from price to intelligence, with high-level intelligent driving features like NOA expected to penetrate the mainstream price range of 100,000 to 200,000 yuan by the end of 2025, reaching a penetration rate of 20% for passenger cars [1] - The competition surrounding intelligent driving assistance is testing automakers' algorithm innovation capabilities and the completeness of their computing infrastructure [1][2] Group 2 - The development of intelligent driving assistance faces challenges in complex urban scenarios, necessitating significant cloud computing power and data training costs for training visual language models [2] - Tesla has emerged as a global leader in intelligent driving assistance due to its substantial investments in computing power, with its Texas Gigafactory deploying a supercomputing cluster with 50,000 GPUs, expected to expand to 100,000 [2] - Some Chinese automakers, like Geely and BYD, are following Tesla's lead by building their own computing platforms, while others are partnering with cloud computing firms [2] Group 3 - The safety of intelligent driving assistance is paramount, requiring automakers to ensure data security and continuously enhance the safety of their features [3] - The development process for intelligent driving includes data collection, filtering, labeling, model training, and simulation testing, with a reliable computing platform directly impacting safety improvements [3] - The efficiency of training and iteration in intelligent driving technology is crucial for market success, necessitating high technical requirements for computing platforms [3] Group 4 - Consumer-grade GPUs, while appearing cost-effective, are not suitable for large-scale AI projects, as they are designed for gaming and may lead to higher failure rates in deployment [4] - High-performance GPUs like A100 and H100 are specifically designed for data centers and large-scale computing, making them more suitable for enterprise-level applications [4] Group 5 - The automotive industry's intelligent development is expected to continue vigorously in 2025, presenting both opportunities and intensified competition [5] - Core competitive advantages will include data accumulation, processing capabilities, and algorithm optimization, ultimately revolving around the effectiveness of computing platforms [5] - Preparing for computing challenges is essential for success in the future of intelligent driving [5]