Core Viewpoint - Major tech companies, including Microsoft, are shifting towards self-developed chips to reduce reliance on traditional suppliers like NVIDIA and AMD, aiming for a more autonomous and controllable technology ecosystem [1][3]. Group 1: Strategic Shift to Self-Developed Chips - Microsoft plans to primarily use self-developed chips in its data centers, marking a significant strategic shift in its overall data center system design [3]. - The move is part of a broader trend among major cloud service providers seeking customized solutions to meet specific business needs, driven by the rapid development of artificial intelligence technology [3][4]. Group 2: Investment in AI and Chip Development - In 2023, Microsoft launched the Azure Maia AI accelerator and Cobalt CPU, specifically designed for AI workloads, which have been widely adopted in its data centers [3]. - Tech giants, including Meta, Amazon, Alphabet, and Microsoft, have committed over $300 billion in capital expenditures this year, with a significant portion allocated to artificial intelligence to meet the growing market demand [3]. Group 3: Industry Trends and Implications - The shift to self-developed chips is not only driven by cost and performance considerations but also by strategic concerns regarding supply chain security and business customization [4]. - This trend is expected to reshape the global semiconductor industry landscape as more companies follow suit [4].

Core Viewpoint - Microsoft aims to primarily use its own chips in data centers to reduce reliance on major companies like Nvidia and AMD [1][3][5] Group 1: Chip Strategy - Microsoft has been using Nvidia and AMD chips in its data centers, focusing on selecting the right silicon for optimal cost-effectiveness [3][5] - The company has launched AI-specific chips like the Azure Maia AI accelerator and Cobalt CPU, and is developing next-generation semiconductor products [5][6] - Microsoft is implementing a new cooling technology to address chip overheating issues [5] Group 2: Industry Context - Major cloud computing players, including Microsoft, Google, and Amazon, are designing their own chips to enhance efficiency and reduce dependence on Nvidia and AMD [6] - Tech giants, including Meta, Amazon, Alphabet, and Microsoft, have committed over $300 billion in capital expenditures this year, primarily focused on AI investments [6] Group 3: Capacity Challenges - There is a significant shortage of computing capacity, exacerbated since the launch of ChatGPT, with Microsoft struggling to build enough capacity to meet demand [7] - Despite ambitious forecasts, Microsoft has found its data center capacity deployments insufficient to satisfy the growing needs [7]

Core Viewpoint - Microsoft plans to primarily use self-developed chips in data centers to reduce reliance on Nvidia and AMD, focusing on optimizing AI workloads with a complete system design approach [1][4]. Group 1: Chip Development and Strategy - Microsoft has launched the Azure Maia AI accelerator and Cobalt CPU in 2023, continuing to develop next-generation chip products [1]. - The company aims to design a complete data center system to optimize AI workloads, indicating a shift towards self-sufficiency in chip design [4]. - Microsoft currently uses Nvidia and AMD chips in data centers, prioritizing cost-effectiveness, but is expanding the use of its own chips [4]. Group 2: Market Context and Competition - Nvidia dominates the market with its GPUs, while AMD holds a relatively small market share [3]. - Major tech companies, including Microsoft, Google, and Amazon, are designing their own chips for data centers to reduce dependence on Nvidia and AMD and to better meet specific needs [3]. Group 3: Capacity Challenges - There is a severe shortage of computing power since the launch of ChatGPT, making it difficult for Microsoft to quickly establish sufficient capacity [5]. - Tech giants, including Meta, Amazon, Alphabet, and Microsoft, have committed over $300 billion in capital expenditures this year to meet AI demands [5].