公众号记得加星标⭐️，第一时间看推送不会错过。 来源：内容 编译自 notebookcheck 。 特斯拉在准备下一代AI5 FSD计算机以集成到车辆的同时，透露了一些AI6芯片的细节。AI5/HW5计算机将搭载一款内部 开发的AI芯片，该芯片专为特斯拉自动驾驶汽车的需求而量身定制，功能强大，不适合出口。 特斯拉将不得不限制其为下一代使用3nm工艺打造的HW5 计算机开发的"惊人"人工智能芯片的功率，该芯片将于 2026 年 底投入量产。这个发布时间已推迟整整一年，原定于"2025 年底/2026 年第一季度初发布。 特斯拉现在称之为AI5的硬件 5.0 FSD 计算机在人工智能计算方面将非常强大，它显然会与美国政府出于国家安全考虑对 人工智能芯片实施的出口管制相冲突。 埃隆·马斯克表示，特斯拉在将计算能力与自动驾驶汽车软件融合方面，拥有最佳的AI芯片设计。正因如此，该公司再次 内部开发HW5计算机，尽管其最新的HW4计算机也是几年前开发的， 但"目前还没有一款芯片是我们愿意用在汽车上 的"。 特斯拉 Model Y自动驾驶出租车目前搭载的 AI4 芯片 ，其无人驾驶全自动驾驶（FSD）功能显然比即将推出的 ...

特斯拉半年净利跌去3成！马斯克急于救市，连画"大饼"。 车东西7月24日消息，就在刚刚，特斯拉发布了其2025年第二季度业绩报告，路透社指出，这是特斯拉十多年来最严重的季度销售额下滑。而从今年上半 年来看，特斯拉营收、净利润更是双双下滑。 特斯拉2025年上半年总收入为418亿美元（约合人民币2995亿元），相比去年同期的468亿美元（约合人民币3351亿元），同比下滑11%。汽车业务收入为 306亿美元（约合人民币2193亿元），同比下滑18%。 特斯拉上半年净利润更是跌去30%，上半年其归母净利润（⾮GAAP）为23.27亿美元（约合人民币167亿元），去年同期为33.48亿美元（约合人民币240 亿元）。此外，特斯拉自由现金流仅为1亿美元（约合人民币7亿元）。 | FINANCIAL SUMMARY | | --- | | Unangicea) | | | | | | | | --- | --- | --- | --- | --- | --- | --- | | ($ in millions, except percentages and per share data) | Q2-2024 | Q3-2 ...

Core Insights - The automotive industry in China is entering the second half of intelligent transformation, with advanced driver-assistance systems (ADAS) becoming a key battleground [1] - The previous approach of maximizing features with minimal hardware has revealed limitations, leading to performance bottlenecks and user trust erosion [2][3] - A shift is needed from a focus on cost-effectiveness to prioritizing safety and system performance as the foundation for user experience [4][5] Group 1: Safety and Performance - Safety is now a prerequisite for ADAS, not just an added benefit, marking a new phase in the industry [4][5] - The introduction of national standards for ADAS safety requirements indicates a regulatory shift towards compliance rather than innovation [7][8] - High-performance computing and redundancy in models and decision-making are becoming industry consensus for ensuring safety and reliability [9][10][12] Group 2: System Integration and Cost - Achieving scalable deployment of ADAS requires a balance of safety, performance, and cost [15][16] - The industry is moving towards a "triangle" framework that integrates safety systems, high-performance support, and cost efficiency [16][17][18] - The need for high bandwidth and efficient data transmission is critical, as merely increasing computing power is insufficient to overcome system bottlenecks [23][24] Group 3: Advanced Models and Real-World Application - The integration of large models is essential for enhancing the system's ability to understand complex driving scenarios [24][25][28] - The evolution of ADAS is transitioning from a focus on functionality to a focus on safety, where the ability to handle extreme scenarios is paramount [29][30] - The ultimate goal is to create a trustworthy and continuously evolving ADAS platform that prioritizes user safety and experience [28][33]

大家好我是大鱼 今天的资讯 包括下面几个消息 1. 汽车市场的新闻 2. AI5晶片量产传闻 是真还是假？ 关注这些领域的朋友 不要错过 今天重要的内容 OK let's go 今天是美国的六月自由日 投资市场休市一天 第一部分 汽车市场的两个消息 加拿大政策方面 加拿大之前有个 iZEV补助计画 从2019年开始 给买电动车的朋友 最高5 000加元的补助 不过这计画在 2025年1月12日 因为钱花光了 直接喊停 没了补助 电动车销售 马上惨不忍睹 根据数据 2024年第四季 加拿大零排放车辆 （ZEVs）占新车销售 的18.9% 但到了2025年第一季 直接掉到9.7% 基本就是腰斩了 不过也别担心 最新的消息是 加拿大政府并没有 打算放弃电动车！ 加拿大的环境与气候 变化部长Julie Dabrusin 最近亲口说 新的消费者补助计画 正在紧锣密鼓地筹备中！ 虽然现在还不知道 这计画叫什么名字 也不知道什么时候公布 但对于有计划购买 电动车的加拿大朋友来说 这无疑是一个好消息 政府还说 他们正在跟各省 和产业大咖合作 确保这计画 不只帮消费者省钱 还能创造更多 加拿大本地的工作机会 不过Tesla在加 ...

Group 1 - The next-generation FSD chip AI5/HW5 from Tesla has entered mass production, with TSMC as the primary foundry [1] - The AI5/HW5 chip boasts a computing performance of 2,000 to 2,500 TOPS, which is five times that of the current HW4 chip at approximately 500 TOPS [1] - The AI5/HW5 chip will utilize a 3nm N3P process, with Samsung as a backup foundry, and is expected to be used in mass production vehicles by 2026 [1] Group 2 - Tesla plans to enhance the FSD hardware suite with upgraded lenses, including weather-resistant lenses from Samsung that can melt ice and snow in one minute [2] - A pilot program for Robotaxi was launched in Austin, with the first 12 Model Y vehicles equipped with HW4 hardware for testing autonomous driving [2]

Core Insights - Xiaopeng Motors has introduced the G7 SUV, which features the self-developed Turing AI chip, boasting an effective computing power of over 2200 Tops, significantly surpassing competitors' offerings [1][2] - The G7 is positioned as the first AI vehicle with L3-level computing power, with a starting price of 235,800 yuan [1][2] - The Turing chip aims to secure a five-year safety period for computing power, essential for future advancements in autonomous driving [1][2] Summary by Sections Product Launch and Features - The G7 SUV was unveiled on June 10, featuring three Turing AI chips, which collectively provide computing power equivalent to nine Orin-X chips [1] - The G7 is designed to meet the increasing demands for higher computing power in autonomous driving, with a pre-sale price starting at 235,800 yuan [1][2] Technology and Innovation - The Turing AI chip's effective computing power is claimed to be 3-28 times that of other industry chips, with current mainstream solutions offering around 508 Tops [1][2] - Xiaopeng's strategy includes local deployment of VLA-OL and VLM models, enhancing the vehicle's capabilities in both driving assistance and smart cockpit features [3][4] Market Position and Competition - The G7 is expected to fill the price gap between the G6 and G9 models, targeting the 200,000-250,000 yuan electric SUV market, where it will face competition from models like Xiaomi's YU7 and Li Auto's i6 [6] - The industry is witnessing a shift towards high-computing power solutions, with competitors like Tesla also advancing their hardware capabilities [5][6] Future Outlook - Xiaopeng aims to enhance the Turing chip's performance through ongoing optimizations, with expectations of significant feature updates via OTA in the coming months [8][9] - The company acknowledges the challenges of keeping pace with rapid technological changes in the autonomous driving sector, emphasizing the need for continuous innovation [6][14]

Investment Rating - The report suggests to pay attention to the industry and its developments [4] Core Insights - The high-level intelligent driving technology is becoming more accessible by 2025, with an upward trend in the industry chain's prosperity driven by mature supply-side technologies and demand-side strategies [3][9] - The new paradigm of computing power in vehicles includes DSA heterogeneous integration, cockpit fusion, and RISC-V architecture, which enhances algorithm optimization and cost efficiency [3][10][17] - Domestic alternatives are emerging with quality supply, and there is potential for technology to go abroad, especially in the mid-to-high-end NOA segment [3][24][26] - The trend of integrated hardware and software is leading to competitive intersections among various players, with traditional manufacturers and new forces both investing in self-research and collaboration [3][27] - The economic analysis of self-research in intelligent driving indicates an annual cost of approximately 2 billion RMB, with significant investments in SoC and algorithms [3][28] Summary by Sections 1. New Paradigm of Computing Power - The supply side is seeing advancements in intelligent driving hardware and software, with improved cost-performance ratios [3][9] - The demand side is influenced by traditional manufacturers promoting lower price points for intelligent driving features [3][9] - The architecture is evolving towards a more integrated approach, moving from multi-box systems to single-chip solutions [3][14] 2. Domestic Alternatives and Technology Export - The domestic market is seeing a growing presence of local suppliers in the mid-to-high-end NOA segment, with companies like Horizon Robotics and Black Sesame emerging as key players [3][26] - The low-end segment remains dominated by foreign companies, but domestic technologies are expected to expand internationally [3][26] 3. Competitive Landscape and Self-Research - Leading companies are enhancing their capabilities by integrating computing power, toolchains, and algorithms [3][28] - The competition is intensifying as companies like Huawei and Tesla are investing heavily in self-research and development of their own chips and algorithms [3][27] - The report highlights the importance of a comprehensive approach to self-research, with significant financial commitments required to maintain competitiveness [3][28] 4. Company Analysis - Companies like NVIDIA and Huawei are leading in hardware performance and ecosystem development, while also seeking to strengthen their algorithm capabilities [3][32][39] - Horizon Robotics is positioned as a leader in providing integrated intelligent driving solutions, with a focus on software and service revenue [3][51]