AIPress.com.cn报道 为了规避供应链断裂的风险，字节跳动在策略上表现得极为老练：一方面通过在新加坡注册的子公司 Picoheart 负责高端芯片业务；另一方面，字节内部千人规模的芯片团队已取得突破，成功研发了一款性能对标英伟达 H20 但成本更低的自研处理器。 12月31日消息，字节跳动再次抛出震撼全球半导体行业的"军备计划"。据《南华早报》报道，字节跳动已初步 计划在 2026 年向英伟达（Nvidia）订购价值约 140 亿美元（约 1000 亿人民币） 的 AI 芯片，较 2025 年的 850 亿人民币预算有显著增长。 目前，这一庞大计划的关键变数在于美国政府是否准许英伟达向中国客户交付性能更强的 H200 GPU。 字节跳动对算力的"无底洞"需求主要源于其庞大的产品矩阵。旗下 AI 助手"豆包"的每日 token 处理量已从 2024 年底的 4 万亿暴增至目前的 50 万亿；而火山引擎作为春晚独家 AI 云合作伙伴，更是承载了数亿人次的瞬时并 发需求。 近期多方消息指出，字节也在与华为洽谈价值约400 亿人民币 的"昇腾"系列芯片订单。这种"英伟达+华为+自 研"的三位一体布局，反映了 ...

如果您希望可以时常见面，欢迎标星收藏哦~ 据路透社今日报道，英伟达公司已告知中国企业，希望在2月中旬之前向中国交付首批H200图形处 理器。 报告援引两位熟悉这家芯片制造商业务的人士的话称，首批出货量将达到5000至10000个芯片模 块，总计约4万至8万颗H200芯片。报告还援引第三位匿名消息人士的话称，英伟达计划提高H200 芯片的产能，以便在明年第二季度加快对中国的出货速度。 然而，任何出货都取决于中国政府是否允许国内企业购买英伟达的芯片。尽管阿里巴巴集团和字节 跳动等中国科技巨头已表达了购买H200芯片的意愿，但北京方面尚未批准任何采购，因为仍在权 衡任何决定对国内芯片制造产业的影响。 拟议的2月份出货计划将是自美国总统特朗普批准向中国出口H200 GPU以来，该系列GPU首次交 付中国市场，美国政府将从中获得25%的分成。据报道，白宫已启动一项跨部门审查，审查针对该 系列芯片的新授权申请，兑现了本月早些时候允许英伟达向中国出售其性能第二强的AI处理器的 承诺。 重大政策转变 据报道，中国官员正在权衡是否允许国内企业进口英伟达H200芯片，因为他们担心这样做会阻碍 中国自身的芯片制造进程。为应对美国的 ...

Core Insights - The approval of the first provincial UHV project in Zhejiang and accelerated progress in controllable nuclear fusion commercialization are significant developments in the power equipment sector [2][63] - The total investment for the Zhejiang UHV AC ring network project is 29.3 billion RMB, marking it as the highest investment and largest single project in China's UHV AC engineering history [63] - The report recommends companies such as Pinggao Electric, Shunhua Electric, and Huaming Equipment in the power equipment sector, while suggesting attention to Tebian Electric [2] - For controllable nuclear fusion, Xuch Electric is recommended, with additional focus on companies like New Wind Power, Saijing Technology, Guoguang Electric, Hailu Heavy Industry, and Yongding Co [2] Industry Developments - The global opening of the ITER organization's core simulation tool IMAS is expected to accelerate the commercialization of fusion energy [2] - Huadian Energy has released new regulations for wind and solar investment mergers, requiring a minimum internal rate of return of 6.5% for capital in domestic and foreign wind and solar projects [3] - The energy storage sector saw a significant year-on-year increase of over 80% in procurement capacity in November, with a total scale of 11.5 GW/33.5 GWh [3] - The establishment of a photovoltaic storage platform company aims to regulate the photovoltaic industry by storing approximately 1 million tons of outdated capacity [4] Market Trends - In November, the sales of new energy vehicles in ten major European countries increased by 38.8% month-on-month, with a total of 290,000 units sold [25] - The report highlights the stable pricing of polysilicon, silicon wafers, battery cells, and modules, indicating a steady market despite fluctuations in demand [10][11][14] - The report notes that the prices of lithium salts and ternary materials have shown mixed changes, with battery-grade lithium carbonate prices rising to 94,500 RMB per ton [47]

Core Insights - The demand for computing power in the AI sector is experiencing explosive growth, with China's intelligent computing power exceeding tens of quadrillions of operations per second by 2025, and AI computing power doubling approximately every six months, significantly outpacing the hardware advancements driven by Moore's Law [2][4]. Industry Overview - The current landscape of computing chips shows a stark contrast between storage and computing chips, where storage chips have standardized interfaces while computing chips rely on a complete ecosystem of instruction sets, toolchains, and operating systems [2]. - The U.S. has long dominated the computing chip system, while China faces dual hardware constraints: the slowing of Moore's Law and the challenges posed by the ban on EUV lithography machines [2][4]. Technological Breakthroughs - The team led by Tang Jianshi has broken down chip computing power into three core elements: transistor integration density, chip area, and individual transistor computing power, and is exploring technologies to enhance each element [4][6]. - To achieve the goal of integrating over one trillion transistors, the team is focusing on chiplet technology, which allows for vertical stacking of multiple chips, expanding integration dimensions from "area density" to "volume density" [6][9]. Innovations in Memristor Technology - The team has made significant advancements in memristor technology, which features a simple structure that allows for multi-bit non-volatile storage and can perform matrix-vector multiplication, enhancing energy efficiency compared to traditional digital circuits [9][10]. - The integration of memristors with CMOS technology has reached a scale of over 100 million, with yield rates between 99.44% to 99.9999%, and products at 40nm and 28nm nodes have achieved mass production [10][12]. Industry Collaboration and Development - The team has established the "Beijing Chip Power Technology Innovation Center" to create a one-stop service platform for chiplet technology, which has already completed initial wiring and is capable of small-scale production [6][10]. - The team has incubated a startup, "Beijing Billion Technology," which has launched a hardware platform for computing and storage integration and is collaborating with various universities and companies like Migu and ByteDance to develop computing acceleration cards for content recommendation applications [15]. Future Directions - The team emphasizes the need for multi-level collaborative innovation to overcome the constraints of advanced manufacturing processes and achieve breakthroughs in high-performance chips [15]. - Future explorations will include integrating silicon photonics and optoelectronics to enhance data transmission and expand the technological pathways for efficient chip development [15].

Core Viewpoint - Tesla's AI5 chip is positioned as a groundbreaking product with significant advantages in cost and performance efficiency, while the upcoming AI6 chip is expected to be the best AI chip ever created [1][4][8]. Group 1: AI5 Chip Development - Elon Musk announced a successful design review for the AI5 chip, which is expected to excel in model inference applications with parameters below 250 billion [1][4]. - The AI5 chip boasts the lowest silicon cost and the highest performance-to-power ratio in its class, making it ideal for efficient and cost-effective AI applications [1][4][8]. - The chip is designed for specific scenarios, focusing on vehicle inference and autonomous driving computing clusters, with mass production expected by the end of 2026 [7]. Group 2: AI6 Chip Prospects - The AI6 chip is anticipated to be the core of Tesla's future AI ecosystem, with initial samples to be produced by Samsung Electronics [7]. - The first applications of the AI6 chip will be in Tesla's Cybercab robotaxi and the Optimus humanoid robot, with plans to expand into AI data centers to compete with leading products like NVIDIA's H200 GPU [7][8]. - The AI6 chip's mass production will begin at Samsung's new factory in Texas, set to open in 2025 [7]. Group 3: Strategic Shift in Chip Development - Tesla has made a strategic decision to consolidate its chip design efforts, shutting down the Dojo project and focusing all resources on a single architecture for the AI5 and AI6 chips [6][8]. - This shift is seen as a wise move to enhance chip performance and reduce reliance on external suppliers, thereby strengthening Tesla's integration of hardware and software [8].