Core Viewpoint - Microsoft is adjusting its internal AI chip development strategy to focus on less aggressive designs by 2028, aiming to overcome delays in development while maintaining competitiveness against Nvidia [2][4]. Group 1: Development Delays and Strategic Adjustments - Microsoft has faced challenges in developing its second and third-generation AI chips, leading to a strategic shift towards more pragmatic and iterative designs [2][4]. - The Maia 200 chip's release has been postponed from 2025 to 2026, while the new Maia 280 chip is expected to provide a 20% to 30% performance advantage per watt over Nvidia's 2027 chip [2][4][5]. - The company acknowledges that designing a new high-performance chip from scratch each year is not feasible, prompting a reduction in design complexity and an extension of development timelines [2][5]. Group 2: Chip Development Timeline - The Braga chip's design was completed six months late, raising concerns about the competitiveness of future chips against Nvidia [5]. - A new intermediate chip, Maia 280, is being considered for release in 2027, which will be based on the Braga design and consist of multiple Braga chips working together [5][6]. - The Maia 400 chip, initially known as Braga-R, is now expected to enter mass production in 2028, featuring advanced integration technologies for improved performance [6][7]. Group 3: Impact on Partners - The revised roadmap has negatively impacted Marvell, a chip design company involved in the Braga-R project, leading to a decline in its stock price due to project delays and economic factors [9]. - Not all of Microsoft's chip projects are facing issues; CPU projects, which are less complex than AI chips, are progressing well [9][10]. - Microsoft's Cobalt CPU chip, released in 2024, is already generating revenue and is being used internally and by Azure cloud customers [10].

Core Insights - Microsoft is adjusting its ambitious AI chip development strategy due to delays, shifting towards a more pragmatic and iterative design approach to remain competitive with Nvidia in the coming years [1][4] - The release of the Maia 200 chip has been postponed from 2025 to 2026, with plans to launch less aggressive designs by 2028 [1][4] - Microsoft aims to reduce its dependency on Nvidia's chip procurement, which costs the company billions annually [1] Group 1: Strategic Adjustments - The delays in the development of Microsoft's second and third-generation AI chips have prompted a strategic overhaul [4] - The Braga chip's design was completed six months later than planned, raising concerns about the competitiveness of future chips against Nvidia [4] - Microsoft is considering an intermediate chip, Maia 280, to be released in 2027, which will be based on the Braga design [4][5] Group 2: Future Chip Plans - The chip initially known as Braga-R will now be called Maia 400, expected to enter mass production in 2028 with advanced integration technology [5] - The release of the third-generation AI chip, Clea, has been delayed until after 2028, with uncertain prospects [5] Group 3: Impact on Partners - The revised roadmap negatively affects Marvell, which was involved in the Braga-R project, leading to a decline in its stock price [6] - Marvell had anticipated earlier revenue from Microsoft, but delays and economic factors have impacted its performance [6] Group 4: Other Projects - Not all of Microsoft's chip projects are facing issues; the CPU project, Cobalt, is progressing well and has already generated revenue [8] - The next generation of Cobalt, Kingsgate, has completed its design and will utilize chiplet architecture and faster memory [8]

Expert Opinion: Chris: In the past quarter, there have been several media and press reports suggesting that Microsoft is withdrawing from certain data center commitments or contracts. However, during the earnings call, management indicated that AI demand is very strong, stating that demand is exceeding supply and that they do not have enough data center space for fiscal year 2025. Is there a shift occurring in Microsoft's data center plans, or could you help clarify this seemingly contradictory message? Exp ...

来源：内容编译自nextplatform，谢谢。 Nvidia 销售了 AI 训练所依赖的并行计算的大部分份额，并且它在 AI 推理领域占有非常大的份额 （甚至可能占据主导地位）。但这些会持续下去吗？ 我们看到超大规模计算公司和云构建商纷纷开发用于 AI 处理的自研 XPU，因此这个问题问得非常 合理。他们都处于开发自己的基于 Arm 的 CPU 和矢量/张量数学引擎的不同阶段，用于处理 AI 工 作负载，也许有一天，用于支持一些传统的 HPC 模拟和建模工作负载。 超大规模计算公司和云构建商可能会设计这些 CPU 和 GPU，但他们也会得到帮助，而 Broadcom 和 Marvell 拥有更多的经验，无论是直接还是通过收购，他们都是提供帮助的人。他们参与指导设 计并提供 IP 模块，如 SerDes 或 PCI-Express 或内存控制器。他们还通过台湾半导体制造公司的代 工厂获得定制芯片（如果英特尔幸运的话，也许有一天它的一个晶圆厂会使用 18A 或 14A 工 艺），以及实施各种尺寸的封装（2D、2.5D、3D 和 3.5D），从而获得报酬。 这项工作有助于实现这些定制的 CPU 和 XPU 计算引 ...