Core Viewpoint - The rise of non-GPU chip forces is unstoppable, indicating a significant shift in the global computing power industry, traditionally dominated by NVIDIA GPUs [1][6]. Group 1: Recent Developments in the Computing Power Industry - Shanghai's leading GPU company, Muxi Co., recently listed on the STAR Market, with its stock price surging by 687.79% to a market cap of 329.88 billion yuan [1]. - Google’s TPU has secured orders worth over 100 billion yuan, breaking the GPU monopoly in the computing power market, while Broadcom's CEO revealed a total order of 21 billion USD (approximately 148.6 billion yuan) from Anthropic [2]. - In China, the computing power industry is also heating up, with AI chip company Qingwei Intelligence securing over 2 billion yuan in financing, supported by a rare investment lineup [2]. Group 2: Market Trends and Dynamics - The global computing power market is experiencing a transformation, with the long-standing NVIDIA GPU monopoly beginning to loosen [2][6]. - The demand for general computing power has led to NVIDIA GPUs dominating the market, but alternatives like Google’s TPU and Amazon’s Trainium3 are starting to replace GPUs in specific scenarios [2][8]. - By the first half of 2025, non-GPU computing cards are expected to account for 30% of the domestic market [2]. Group 3: Investment Movements - Intel is reportedly planning to acquire AI chip unicorn SambaNova for 1.6 billion USD (approximately 11.29 billion yuan) to regain competitiveness in the AI era [3]. - Non-GPU unicorn Groq has raised over 3 billion USD (approximately 21.3 billion yuan) in funding over the past two years [3]. Group 4: Industry Structure and Future Directions - The computing power industry is expected to face path differentiation, driven by demand, technology, and ecosystem development [8][10]. - The need for efficient computing solutions is pushing companies to seek alternatives to the traditional GPU-centric model, especially as AI applications diversify across various industries [8][9]. - The traditional von Neumann architecture is facing challenges, necessitating architectural innovations to overcome performance limitations [9]. Group 5: Non-GPU Market Growth - Gartner predicts that by 2027, the demand for AI inference applications will lead to AI accelerators (typically non-GPU AI-specific chips) surpassing GPU shipments [16]. - In the first half of this year, China's non-GPU chip market has shown significant growth, with projections indicating a market share of nearly 50% by 2028 [16]. Group 6: Domestic Chip Companies and Their Strategies - Key players in the domestic non-GPU sector include Kunlun Chip, Cambricon, and Qingwei Intelligence, each representing different technological routes [25][29]. - Cambricon and Kunlun Chip focus on ASIC routes, while Qingwei Intelligence emphasizes reconfigurable computing architectures [29][30]. - The ASIC architecture, exemplified by Google’s TPU, offers high performance and efficiency, but requires significant time and resources for customization [30][31]. Group 7: Reconfigurable Computing Advantages - Reconfigurable computing is gaining momentum, addressing the inefficiencies of GPUs and the rigidity of ASICs, thus balancing performance and cost [32][37]. - Qingwei Intelligence's reconfigurable chips have achieved over 30 million units shipped, with significant orders expected in the coming years [32]. - The technology supports efficient inter-chip communication, avoiding bandwidth bottlenecks and communication delays inherent in traditional architectures [33]. Group 8: Conclusion - The AI computing power landscape is evolving towards a diversified and heterogeneous integration, with GPUs maintaining dominance in general-purpose applications while non-GPU routes rapidly rise in AI inference and specialized computing needs [39][41].

Core Insights - Lingchuan Technology, an AI chip company, has completed a multi-hundred million yuan Series A financing round led by Beijing AI Industry Investment Fund and Kuaishou Group, with plans to use the funds for next-generation chip development, mass production of existing products, and overseas market expansion [1] Company Overview - Lingchuan Technology was established in March 2024, originating from Kuaishou Group's heterogeneous computing and chip division, and became independent after successfully deploying thousands of SL200 chips, which significantly reduced costs [1][4] - The CEO, Liu Lingzhi, emphasized that the company's internet background allows it to reverse-engineer chip design based on application needs, a competitive advantage over traditional chip companies [1] Product Details - The SL200 chip is the first domestic ASIC chip to integrate video encoding, AI inference, and multi-core CPU functionalities, achieving a fault rate of 0.0001 and nearly 100% coverage among top clients [2] - The chip's video compression performance surpassed Intel and NVIDIA in competitions, with a 40% reduction in single-stream processing costs [2] - The next-generation chip is designed for large model training and inference scenarios, supporting high computational demands for applications like LLM and generative video models [2] Technology and Architecture - The Transtreams Advanced Compute Unified Architecture combines CPU and NPU for efficient task collaboration and performance optimization, allowing seamless code switching between CPU and NPU [3] - The TC programming language simplifies complex data layouts and parallel computing, enhancing programming efficiency and reducing errors [3] Market Applications and Expansion - The SL200 chip is deployed in various sectors, including internet data centers for Kuaishou, Alibaba, and Baidu, and has over 20 collaborative cases in broadcasting, smart cities, and intelligent inspection [4] - The company is expanding into Southeast Asian markets like Singapore and Brazil through Kuaishou's overseas business [4] - Future plans include adapting the next-generation chip for autonomous driving robots and edge computing scenarios [4] Team Composition - The team has tripled in size since the company's split, with over 80% of staff in R&D, and more than 70% holding master's degrees, while over 20% have PhDs [4] - The team has filed over 100 patents in key technologies and has participated in international competitions, contributing to significant technology projects in Beijing and Shanghai [4]