Core Viewpoint - Google is challenging Nvidia's dominance in the AI semiconductor market by supplying its Tensor Processing Units (TPUs) to external data centers, marking a significant shift in its strategy from solely using Nvidia GPUs to offering its own AI chips [2][3][5]. Group 1: Google's TPU Strategy - Google has begun to supply TPUs to external cloud computing companies, indicating a potential expansion of its customer base beyond its own data centers [2]. - The company has signed a contract with Floydstack to set up TPUs in a new data center in New York, which will be its first deployment outside its own facilities [2]. - Analysts interpret this move as either a response to increasing demand that outpaces Google's own data center expansion or as a strategic effort to compete directly with Nvidia [2]. Group 2: TPU Development and Market Growth - The TPU, launched in 2016, is designed specifically for AI computations, offering advantages in power efficiency and speed compared to traditional GPUs [3]. - Recent reports indicate a 96% increase in developer activity around Google Cloud TPUs over the past six months, reflecting growing interest in the technology [4]. - The upcoming release of the seventh-generation Ironwood TPU is expected to further drive demand, with significant enhancements in performance and memory capacity compared to the previous generation [8]. Group 3: Market Dynamics and Competition - Nvidia currently holds an 80-90% market share in the AI training GPU market, with a staggering 92% share in the data center market as of March this year [5]. - As Google begins to supply TPUs externally, the competitive landscape in the data center semiconductor market may shift, reducing reliance on Nvidia's products [5]. - DA Davidson analysts suggest that Google's TPU business could be valued at $900 billion, significantly higher than earlier estimates, indicating strong market potential [7]. Group 4: Technical Specifications of Ironwood TPU - The Ironwood TPU is expected to deliver 4,614 TFLOPS of computing power, with a memory capacity of 192GB, which is six times that of the previous generation [8]. - The chip will also feature a bandwidth of 7.2 Tbps, enhancing its ability to handle larger models and datasets [8]. - The efficiency of the Ironwood TPU is projected to be double that of the Trillium TPU, providing more computational power per watt for AI workloads [8].

Core Viewpoint - Google's A shares (GOOGL) experienced a significant increase of 9.14%, reaching a new intraday high since July 2022, reflecting investor optimism regarding the company's ongoing efforts in the technology sector, particularly in artificial intelligence and cloud computing [1] Group 1: Company Developments - Google is collaborating with several small cloud service providers to deploy its Tensor Processing Units (TPUs) in their data centers, indicating a strong push towards the proliferation of AI computing [1] - A recent ruling by a U.S. district court determined that Google does not need to divest its Chrome browser and Android system, allowing continued collaboration with Apple and maintaining Google's position as the default search engine on iPhones [1] Group 2: Market Reactions - Barclays has raised its target price for Google's A shares from $235 to $250, reflecting a positive outlook on the company's future financial performance [2]

Core Viewpoint - Samsung Electronics is set to supply 12-layer HBM3E to Broadcom, with plans for mass production starting as early as the second half of this year to next year, aiming to mitigate the impact of NVIDIA's HBM supply delays [1][3]. Group 1: Supply Agreements - Samsung has completed quality testing for HBM3E 12-layer with Broadcom and is negotiating supply volumes estimated between 12 billion to 14 billion Gb, with mass production expected soon [1]. - Samsung is also in active discussions to supply HBM3E 12-layer memory to Amazon Web Services (AWS), which plans to produce the next generation AI semiconductor "Trainium 3" using this memory [2]. Group 2: Market Dynamics - The surge in development of proprietary ASICs by major tech companies presents an opportunity for Samsung to offset the downturn in its HBM business [3]. - Samsung's initial plan to supply NVIDIA with HBM3E 12-layer was delayed due to performance issues, and the company is now adjusting its production rates for HBM3E lines [3]. Group 3: Production Goals - Samsung aims to double its total HBM supply to between 8 billion to 9 billion GB this year, compared to last year [1]. - The successful supply to NVIDIA and acquisition of more ASIC clients in the second half of this year is crucial for stabilizing Samsung's HBM business [3].

如果您希望可以时常见面，欢迎标星收藏哦~ 来源：内容来自digitimes ，谢谢 。 三星电子（Samsung Electronics）近来重兵部署在HBM先进制程，但供应链传出，三星HBM3E 认证进度再遭卡关，由于Google投入自行设计AI伺服器晶片，原打算搭配三星HBM3E，并送交台 积电进行CoWoS封装，但日前却突然通知三星HBM遭撤下。 据了解，事发源头是来自三星HBM3E未能通过NVIDIA认证，Google为求保险起见，可能改换美 光（Micron）产品递补供应，相关市场消息近日在业界传得沸沸扬扬。 对此，DIGITIMES向三星求证，三星回覆无法评论客户相关事宜，相关开发计画仍按照进度执 行。 相关供应链指出，根据规划，三星向NVIDIA送出的HBM3E认证确实进入开奖揭晓阶段，原本预 期最快在2025年第1季向NVIDIA放量供应HBM3E，而NVIDIA迟迟未明确对外公布最后的认证结 果，但Google改换供应商的动作，已被视为三星HBM3E认证不顺的重要指标。 客户改换供应传言间接证实三星HBM3E卡关 先前外电曾报导，联发科将打入Google新世代的AI供应链，双方将携手开发下一 ...