Core Insights - Huawei unveiled the complete development roadmap for its Ascend AI chips at the Global Connectivity Conference, establishing a self-controlled computing foundation for China's AI industry amid manufacturing constraints [2] - The domestic AI chip ecosystem is evolving with multiple players like Alibaba, Baidu, Tencent, and ByteDance adopting different strategies for market entry, creating a multi-path domestic substitution landscape [3][6] Huawei's Asymmetric Innovation Path - Huawei acknowledges that its single-chip computing power still lags behind Nvidia but opts for an asymmetric innovation path, focusing on system architecture and interconnection technology to compensate for performance gaps [3] - The key breakthrough is the Lingqu interconnection protocol, which addresses long-distance, high-reliability, and low-latency challenges, achieving significant improvements in reliability and bandwidth [3] Future Roadmap for Ascend Chips - Huawei's roadmap includes the launch of Ascend 950PR in Q1 2026, focusing on inference pre-fill scenarios, and Ascend 950DT in Q4 2026, which will shift to SIMD/SIMT architecture for general AI tasks [4] - The Ascend 960, set for Q4 2027, will double specifications, while the Ascend 970 in Q4 2028 will achieve significant increases in computing power and memory access bandwidth [4] Competitive Edge of Huawei's SuperNodes - Huawei's Atlas 950 SuperPoD and Atlas 960 SuperPoD support 8192 and 15488 Ascend cards respectively, leading in key metrics compared to Nvidia's upcoming NVL144S [4] - The Atlas 950 SuperCluster and Atlas 960 SuperCluster boast computing power exceeding 500,000 and 1 million cards respectively, marking a significant advancement in the industry [4] Software and Ecosystem Development - Huawei is enhancing its software and ecosystem by open-sourcing the CANN compiler and virtual instruction set interface, with plans to open-source the Mind series application enablement suite by the end of 2025 [5] - The company aims to build a competitive technology alliance against Nvidia's CUDA ecosystem through the open release of Lingqu 2.0 technology specifications [5] Other Players in the AI Chip Ecosystem - Alibaba is diversifying its AI chip strategy with self-developed inference chips and ARM architecture CPUs, while Baidu's Kunlun series has gained market recognition with significant contracts [8] - Tencent is optimizing software-hardware collaboration through cloud services and investments in AI chip companies, while ByteDance is engaging in supply chain partnerships to procure domestic AI chips [8] Policy and Patent Support - The Chinese government has implemented policies to support the chip industry, aiming for a 70% self-sufficiency rate by 2025, with various tax incentives for chip manufacturers [10] - Patent accumulation is crucial for technological breakthroughs, with Huawei holding over 150,000 global patents, including significant numbers in AI and communication fields [11][12] Conclusion - The advancements in Huawei's Ascend chips and the collaborative efforts of other domestic players are driving the growth of a self-controlled AI chip ecosystem in China, supported by robust government policies and patent strategies [12]

Core Viewpoint - Major Chinese tech companies, including Alibaba, Baidu, and Tencent, are accelerating the development and adaptation of domestic AI chips to reduce reliance on NVIDIA products amid tightening international restrictions on advanced AI chip exports [3][6][7]. Group 1: Alibaba - Alibaba has been actively developing its own chips since acquiring Zhongtian Micro in 2018, launching products like the Hanguang 800 and Xuantie processors, and recently testing a new AI inference chip that rivals NVIDIA's H20 [3][4]. - The company aims to create a complete closed-loop system encompassing chips, models, and applications, demonstrating its commitment to building a self-controlled computing power system [3][6]. Group 2: Baidu - Baidu introduced the Kunlun chip series in 2018, with the second generation now utilizing 7nm technology, significantly enhancing performance [3][4]. - The company has established a large-scale cluster based on the Kunlun P800 chip, achieving training efficiency and energy efficiency comparable to international standards, and is currently testing the new version of Wenxin Yiyan [3][4]. Group 3: Tencent - Tencent has announced full compatibility with mainstream domestic chips, building on previous developments in its cloud services [4][6]. - The company has created a comprehensive domestic software ecosystem and has integrated its proprietary cloud platform with various domestic hardware and software, enhancing its service offerings [4][6]. Group 4: ByteDance - ByteDance has not officially announced significant progress in adapting or developing domestic chips but is reportedly increasing its efforts in self-developed AI chips, with plans to collaborate with TSMC for large-scale production by 2026 [4][6]. - The company has ordered over 200,000 NVIDIA H20 chips, valued at over $2 billion, highlighting the high costs of computing power that are driving its chip development initiatives [4][6]. Group 5: Industry Implications - The competition among these tech giants in the domestic computing power sector is not only crucial for their individual growth but also for the future of China's AI industry [6][7]. - As these companies invest heavily in domestic chip development, there is potential for breaking the foreign chip monopoly and establishing a more autonomous and robust domestic computing ecosystem [6][7].