公众号记得加星标⭐️，第一时间看推送不会错过。 面对全球AI热潮推升的半导体需求，科技巨头正加速摆脱对英伟达的依赖。最新消息指出，微软正与 博通洽谈共同研发客制化AI芯片的计划，为数据中心打造更具成本效益与掌控度的运算核心。这个动 向不仅是微软自身策略转变的一环，也与Google、亚马逊、OpenAI等巨头全面启动的自研芯片战略 相呼应。 根据《The Information》12月6日报导，微软正与博通商谈开发新一代客制化AI芯片的合作案。原本 微软采用迈威尔科技（Marvell）技术打造部分AI芯片，但随着生成式AI模型规模急速膨胀，现有供 应链已难以满足需求。 如 果 你 仍 然 不 明 白 Jensen 在 这 里 的 意 思 ， 他 指 的 是 最 近 Anthropic 达 成 的 协 议 ， 其 中 包 括 围 绕 Blackwell和Rubin系统构建的基础设施。与此同时，Anthropic还签署了谷歌最新Ironwood TPU的 协议，这引发了人们对ASIC芯片能否真正与NVIDIA竞争的新疑问。詹森就分析师的这一推断发表 了评论，他指出，当公司开发定制芯片时，真正的竞争并非来自NVIDI ...

Group 1 - OpenAI CEO Sam Altman visited Taiwan to discuss key projects with Foxconn and TSMC, focusing on the "Star Gate" initiative and the production details of its self-developed AI chips (ASIC) [1][2][3] - The "Star Gate" project aims to build five new data centers in the U.S., representing one of the largest investments in computing power in the country, with Foxconn being the largest AI server supplier for this initiative [2] - OpenAI is developing custom AI chips to reduce reliance on external suppliers like NVIDIA, with plans to have TSMC manufacture these chips, targeting mass production by 2026 [3] Group 2 - The collaboration with Foxconn is crucial for ensuring the production and delivery capabilities of AI servers needed for the "Star Gate" project's infrastructure [2] - OpenAI's initial chip versions are expected to focus on inference rather than training, marking a significant test for the viability of self-developed chips in the tech industry [3]

Core Viewpoint - Alibaba and Baidu have begun using internally designed chips to train their AI models, replacing some NVIDIA chips, indicating a shift towards self-sufficiency in AI infrastructure [1] Group 1: Company Developments - Alibaba's stock rose by 5.86% to HKD 151.7, while Baidu's stock increased by 3.76% to HKD 110.5 [1] - Alibaba has been applying its self-developed chips for lightweight AI model training since the beginning of this year [1] - Baidu is experimenting with its Kunlun P800 chip to train the new version of its Wenxin AI model [1] Group 2: Industry Trends - The trend of self-developed AI chips is emerging, as evidenced by OpenAI's collaboration with Broadcom to design its first self-developed AI chip [1] - Google is accelerating its self-developed TPU to compete directly with NVIDIA in third-party data centers [1] - According to招商证券, the shift towards self-developed AI chips signifies a transition in the AI infrastructure industry from a "single GPU supply constraint" to "diversified custom chip solutions," altering the investment logic from hardware monopoly to ecosystem competition [1]

Core Viewpoint - Alibaba and Baidu have begun using internally designed chips to train their AI models, replacing some NVIDIA chips, which has led to significant stock price increases for both companies [1][1][1] Group 1: Company Developments - Alibaba's stock rose by 5.86% to HKD 151.7, while Baidu's stock increased by 3.76% to HKD 110.5 following the news [1][1][1] - Since the beginning of this year, Alibaba has been applying its self-developed chips for training lightweight AI models [1][1][1] - Baidu is experimenting with its Kunlun P800 chip to train the new version of its Wenxin AI model [1][1][1] Group 2: Industry Trends - The trend of self-developed AI chips is emerging, indicating a shift in the AI infrastructure industry from a "single GPU supply constraint" to "diversified custom chip solutions" [1][1][1] - This shift in investment logic is moving from hardware monopoly to ecological competition [1][1][1] - OpenAI has announced a partnership with Broadcom to design its first self-developed AI chip, while Google is accelerating its self-developed TPU into third-party data centers to compete directly with NVIDIA [1][1][1]