Group 1: SiC Substrate Market - The global N-type SiC substrate market is projected to experience a revenue decline of 9% in 2024, amounting to $1.04 billion, due to weakened demand in the automotive and industrial sectors, alongside intensified market competition and significant price drops [1] Group 2: Semiconductor Packaging and Testing Market - The combined revenue of the top ten semiconductor packaging and testing companies is expected to reach $41.56 billion in 2024, reflecting a year-on-year growth of 3% [4] - ASE Holdings and Amkor maintain their leading positions, while companies like JCET and Tianshui Huatian are experiencing double-digit growth, posing strong challenges to the existing market structure [4][5] Group 3: AI Chip Development - The demand for AI servers is accelerating the self-research of ASIC chips among major North American cloud service providers, with new versions expected to be released every 1-2 years [6] - The proportion of AI chips sourced from foreign suppliers like NVIDIA and AMD in the Chinese market is anticipated to decrease from approximately 63% in 2024 to about 42% in 2025, while local suppliers are expected to increase their share to 40% under government policy support [6]

Core Insights - The article discusses the accelerating trend of AI server demand driving major North American Cloud Service Providers (CSPs) to develop their own Application-Specific Integrated Circuits (ASICs) to reduce reliance on external suppliers like NVIDIA and AMD [1][2][3][4][5]. Group 1: North American CSP Developments - Google has launched the TPU v6 Trillium, focusing on energy efficiency and optimization for large AI models, with plans to significantly replace the TPU v5 by 2025 [2]. - AWS is collaborating with Marvell on the Trainium v2, which supports generative AI and large language model training, and is expected to see substantial growth in ASIC shipments by 2025 [2]. - Meta is developing the next-generation MTIA v2 in partnership with Broadcom, emphasizing energy efficiency and low-latency architecture for AI inference workloads [3]. - Microsoft is accelerating its ASIC development with the Maia series chips, optimizing for Azure cloud services, and is collaborating with Marvell for the Maia v2 design [3]. Group 2: Chinese AI Supply Chain Autonomy - Huawei is actively developing the Ascend chip series for domestic markets, targeting applications in LLM training and smart city infrastructure, which may challenge NVIDIA's market position in China [4]. - Cambricon's MLU AI chip series is aimed at cloud service providers for AI training and inference, with plans to advance its solutions to the cloud AI market by 2025 [4]. - Chinese CSPs like Alibaba, Baidu, and Tencent are rapidly developing their own AI ASICs, with Alibaba's T-head launching the Hanguang 800 AI inference chip and Baidu working on the Kunlun III chip [5].