作为技术共享的载体、推动全球技术创新的基础之一，技术"开源"不仅能减少基础且重复的投入，更降低企业间的技术壁垒，形成"群体智慧"。通过开放协 作、生态共建和资源复用，"开源"加速着技术从实验室到市场的转化。在2025中关村论坛年会开幕式上，"北京重大开源系列成果"正式发布，通过RISC- V、长安链、整车操作系统等一批开源项目，系统展示北京开源成果矩阵，彰显北京始终以开源开放为本色，全面建设全球"开源之都"。智能汽车作为新质 生产力的代表，技术开源将成为中国汽车领先国际的重要推动力。开幕式上，理想汽车发布理想星环OS，并宣布将对自研的汽车操作系统进行开源。 封闭放大系数，开源放大基数 理想汽车自研操作系统始于2021年，彼时全球芯片市场正处于短缺状态，同时闭源操作系统也给芯片适配与验证带来挑战，面对市场发展中的不可控风险， 销量正处爬坡期的理想汽车启动汽车操作系统自研项目。据理想汽车CEO李想介绍，理想汽车投入200多人的研发团队和超10亿元的研发费用，最终完成汽 车操作系统方案选型、架构设计和落地，并于2024年实现首个版本量产上车。 "理想星环OS实现了软硬解耦，具备适配灵活、支持硬件丰富的特点。"李想透 ...

Core Viewpoint - Google has decided to stop maintaining the public branch of the Android Open Source Project (AOSP), leading to a more closed development process that may eventually eliminate the open-source aspect of AOSP altogether [1][12][13]. Group 1: What Happened? - Google will no longer maintain the public branch of AOSP, and all Android development will occur solely within Google's internal branch starting next week [1][12]. - Only Google employees will have access to the internal branch or be able to submit code, resulting in a lack of transparency in the Android development process [2][12]. Group 2: Impacts - Mainstream smartphone brands and their users, such as Xiaomi, vivo, OPPO, and Samsung, are not expected to be affected as they have existing agreements with Google to access the latest Android source code and Google Mobile Services (GMS) [3][14]. - Consumers of non-certified Android devices may face impacts, as Google may compel these manufacturers to sign agreements to access the latest code, potentially increasing costs for consumers [4][28]. - Some manufacturers may resist Google's demands, leading to a reduction in market options for consumers [5][28]. - Third-party ROM developers will experience significant challenges, as they may only be able to modify and maintain the last available version of AOSP until it becomes obsolete [6][29]. - Android application developers may not see immediate effects, but the existing fragmentation in the Android ecosystem could worsen, increasing costs for smaller developers [8][29]. Group 3: Future Considerations - The decision to close AOSP may be driven by Google's desire to reduce costs and increase revenue, as maintaining multiple code branches and collaborations is resource-intensive [13][32]. - Google aims to regain control over the non-certified device market, which could lead to higher prices for consumers and reduced choices [27][28]. - The closure of AOSP may also hinder innovation and competition among developers, particularly affecting smaller players in the market [29][32].

Core Viewpoint - Lepton AI, founded by former Alibaba executives, is reportedly in talks to be acquired by NVIDIA for an estimated amount in the hundreds of millions of dollars, focusing on AI cloud services and GPU rental business [1][7]. Company Overview - Lepton AI was established in 2023 and raised $11 million in seed funding, aiming to provide an efficient and scalable AI application platform that allows developers with minimal AI knowledge to deploy AI models with just 2-3 lines of code [2]. - The founding team includes notable figures from Alibaba and Meta, such as former Alibaba VP Jia Yangqing and AI researchers Bai Junjie and Li Xiang [3][4]. Strategic Importance - NVIDIA is interested in Lepton AI primarily for its cloud service capabilities, which could help diversify its business and reduce reliance on major clients like Amazon and Google, who are developing their own chips [6][7]. - Lepton AI is the first company NVIDIA is directly acquiring, indicating a strategic move towards enhancing its cloud computing offerings [8]. Technological Contributions - Lepton AI has gained recognition for its open-source contributions, including a demonstration of a conversational search engine implemented with only 500 lines of code [11]. - The company has invested approximately $100 million in Coreweave for high-end GPU supply and participated in significant funding rounds for AI cloud providers, including $480 million in Lambda's Series D and $305 million in TogetherAI's Series B [12]. Business Model - Lepton AI does not own any GPUs but provides a machine learning platform for managing and monitoring GPU health, allowing users to rent GPUs from other suppliers or purchase support and platform access [18][19]. - By simplifying AI training and deployment, Lepton AI enables users to focus on product development rather than technical complexities [21].

Group 1 - The core viewpoint of the article is that AI is expected to create a market space of up to $10 trillion by potentially replacing 20% of human labor and reducing costs by 20% [2][9] - Key industries that will benefit from the AI revolution include e-commerce, cloud computing, advertising, and financial analysis [2][10] - The company aims to adopt a startup mentality to enhance agility and responsiveness in a competitive e-commerce landscape [3][4] Group 2 - The company emphasizes the importance of empowering younger management team members to make decisions and learn from mistakes [5][7] - The AI strategy is closely linked to the company's cloud computing business, which will benefit from AI deployment across various use cases [10][11] - The pursuit of Artificial General Intelligence (AGI) is seen as a philosophical challenge, with implications for understanding human intelligence limits [12][19] Group 3 - The article discusses the diminishing value of developing the smartest AI in isolation, emphasizing the need for practical applications in real-world scenarios [20][21] - Open-source models are highlighted as a means to democratize AI capabilities, allowing a wider range of developers to innovate [20][21] - The company believes that AI will enhance rather than replace human jobs, improving the quality of work in fields like equity research and law [22]

以下文章来源于笔记侠 ，作者苏德超 笔记侠 . 点我关注，与260万读者一起看透新商业本质。笔记侠，中国新商业知识干货共享社区，8000多篇干货 笔记，宏观趋势、组织管理、商业模式等28个主题可精准搜索。 来 源丨笔记侠（ID：Notesman） 作者丨苏德超，武汉大学哲学院教授 图源丨midjourney DeepSeek的爆红，仿佛一夜之间让我们全民都进入了AI时代。 在享受AI带来的生活便利和工作效率提升的同时，我们也发现了一些问题：例如AI会编造不存在的案 例、名人名言和数据，或者对回答张冠李戴甚至"胡说八道"。 这说明AI在价值观、道德能力和真假辨别上，还有完备空间，而我们又必然面对这个类人意识与类人智 能进入我们的工作和生活。 那么，我们要怎样适应AI时代？ 如果苏格拉底来到今天，他会怎样看待AI？ 我们怎样通过用好AI，来做好企业管理？ 为什么说梁文锋等企业家身上体现出的"近代精神"是非常可贵的？ 带着这些问题，笔记侠团队于2月27日邀请了武汉大学哲学院教授，知名哲学学者苏德超与中国人工智能 学会心智计算专委会副主任委员，武汉大学计算机学院教授蔡恒进进行了一次题为"AI时代，如何用哲学 提问和范 ...

Investment Rating - The report rates the electronic industry as "Outperform" compared to the market [1]. Core Insights - The electronic industry experienced a decline of 4.9% in the past week, ranking 28th out of 31 sectors, while the SW electronic sub-sectors showed mixed performance with semiconductor materials up by 0.4% and others down [2][44]. - DeepSeek launched five open-source projects aimed at enhancing AI model efficiency, showcasing a competitive strategy against OpenAI's high-cost models [2][28]. - The report highlights significant advancements in AI hardware and software, indicating a potential surge in demand for domestic semiconductor chips [2][40]. Summary by Sections 1. DeepSeek Open Source Week Releases - DeepSeek announced the launch of five open-source projects to enhance AI capabilities, including FlashMLA for efficient model inference and DeepEP for improved GPU communication [5][9]. - FlashMLA achieved a data throughput of 3000 GB/s and 580 TFLOPS on the H800 platform, nearly doubling performance compared to previous models [6][8]. - DeepEP optimized GPU communication, achieving a bottleneck bandwidth of 153 GB/s for intra-node and 46 GB/s for inter-node communications [11][12]. 2. Global Industry Dynamics - NVIDIA reported a record revenue of $39.3 billion for Q4 2025, with significant growth in data center revenues [30][31]. - OpenAI launched its largest model, GPT-4.5, which is expected to enhance performance significantly but comes with a high API cost [33][34]. - Alibaba announced a massive investment of 380 billion yuan in cloud and AI hardware infrastructure over the next three years, marking a significant commitment to the sector [36]. 3. Market Review - The electronic industry saw a decline of 4.9% in the past week, with semiconductor materials showing slight gains while other sectors faced losses [2][44]. - The report lists top-performing stocks in the electronic sector, with notable gains from companies like Aojie Technology (+30.0%) and Chipone Technology (+27.4%) [48]. - The Philadelphia Semiconductor Index experienced a decline of 11.7%, reflecting broader market challenges [51].

Core Viewpoint - The article highlights significant developments in the AI sector, particularly focusing on Shenzhen's action plan to accelerate the growth of the AI terminal industry, aiming for a market size of over 800 billion yuan by 2026, with a target of 1 trillion yuan [1][4]. Group 1: Shenzhen's Action Plan - Shenzhen's action plan includes the introduction of innovative smartphone products, transitioning from "smart tools" to "smart assistants" [1][5]. - The plan aims to enhance the core competitiveness of the AI terminal industry, with a target of producing over 1.5 billion AI terminal products and launching more than 50 popular AI terminal products across various categories by 2026 [4][5]. - The initiative emphasizes the development of AI smartphones, computers, and wearable devices, focusing on specific applications in smart finance, smart healthcare, and smart cities [5][6]. Group 2: Market Reactions - Following the announcement of the action plan, local stocks such as Deep Konka A and Shenzhen Saige experienced significant price increases, with some reaching their daily limit [1]. - The stock market response indicates strong investor confidence in the potential growth of the AI sector in Shenzhen [1]. Group 3: Strategic Financing in AI - On the same day, Zhiyu AI announced a new round of strategic financing exceeding 1 billion yuan, aimed at advancing the development of its GLM large model technology [2][8]. - This financing will support the company's efforts to enhance its AI capabilities and contribute to the digital transformation of industries in the Zhejiang province and the Yangtze River Delta region [8][10]. - Zhiyu AI's previous financing round of 3 billion yuan just two months prior highlights the growing interest and investment in AI technologies [8][9].

Core Viewpoint - RISC-V has transformed from an emerging force to a core player in the semiconductor industry, with significant contributions from major companies and a growing presence in various markets, including AI and embedded systems [1][2][4]. Group 1: RISC-V Market Development - Qualcomm has shipped 650 million RISC-V cores by the end of 2023, while Intel has produced approximately 3 billion RISC-V-based chips [1]. - RISC-V has made substantial inroads into the AI chip market, attracting interest from both startups and established companies like Meta [1]. - The RISC-V architecture is expanding into consumer electronics, automotive, industrial, PC, and server markets [1]. Group 2: Alibaba's Contribution - Alibaba's Damo Academy, with its early investment in RISC-V, is actively developing high-performance processors, including the C930, which is expected to set new performance benchmarks [2][6]. - The C930 processor features advanced design elements such as a 15-stage out-of-order superscalar pipeline and is designed to compete with Arm's Neoverse series [7]. Group 3: Product Line and Ecosystem - The Damo Academy's XuanTie series includes a range of processors (C, E, R series) catering to various performance needs, with over 4 billion units shipped [5]. - The upcoming C930 processor is anticipated to meet the demands of high-performance computing applications, including PC and edge servers [6][8]. - The ecosystem around RISC-V is being strengthened through collaborations with various partners to enhance software and hardware integration [12][13]. Group 4: AI and Future Directions - The C930 processor will also incorporate AI capabilities, featuring an 8 TOPS Matrix engine, marking a significant leap in AI processing power [21]. - The development of the C908X processor aims to support AI acceleration and automotive applications, showcasing RISC-V's versatility [8][21]. - The RISC-V architecture is positioned to leverage open-source advantages, potentially reshaping the future of computing and AI [18][19][22]. Group 5: Collaborative Initiatives - The establishment of the "Wujian Alliance" aims to foster collaboration among leading companies to optimize RISC-V development and reduce costs [15][16]. - New members, including Siemens EDA and Cadence, have joined the alliance to enhance the ecosystem and support RISC-V's integration into various applications [16]. - The alliance has already produced the first RISC-V video transcoding card, demonstrating practical applications of the technology [15].

"真正的大模型开源，应该把数据集也开源。" 文丨贺乾明 编辑丨宋玮 过去两个月，DeepSeek 重塑全球大模型格局，也扭转了整个行业对开源的理解。 OpenAI 反思走向闭源是 "站在历史错误的一边"，百度、MiniMax、阶跃星辰等原本闭源的公司转向开源。 "如果在以前，一个拿几亿美金融资的公司说自己要开源，估计投资人会吐血。" 一位科技投资人说。 DeepSeek 还在加大开源力度。这周，DeepSeek 计划开源 5 个训练、推理大模型相关的代码库——而大多数开源模型的公司还停留 在开放模型权重层面。 到底该怎么看待 DeepSeek 的开源？它对大模型开源社区意味着什么？为什么不同公司选择不同的开源策略？选择开源对一家商业 公司到底意味着什么？ 近期，我们访谈了中国开源先驱章文嵩。他 1995 年读硕士期间接触到开源，那时中国刚通互联网不久，不少 DeepSeek 的研究者还 没有出生。 1998 年，章文嵩在国防科大读博期间开源了 LVS（Linux 虚拟服务器）软件，这个均衡服务器访问流量、避免宕机的系统，是中国 最早在全球科技行业扩散的开源项目，如今是互联网基础设施的组件。 "几乎所有的互联网 ...

Core Viewpoint - The emergence of DeepSeek challenges traditional beliefs about AI model development, demonstrating that a financial startup from China can innovate in AI, contrary to the notion that only large tech companies or research institutions can do so [1][4][5]. Group 1: AI Economics: Scaling Laws vs. Scale Effects - DeepSeek's success indicates a shift in understanding the barriers to AI model development, particularly reducing the constraints of computational power through algorithm optimization [8][9]. - Scaling laws suggest that increasing model parameters, training data, and computational resources leads to diminishing returns in AI performance, while scale effects highlight that larger scales can reduce unit costs and improve efficiency [10][11]. - The interplay between scaling laws and scale effects is crucial for understanding DeepSeek's breakthrough, as algorithmic advancements can enhance the marginal returns of computational investments [12][14]. Group 2: Latecomer Advantage vs. First-Mover Advantage - The distinction between scaling laws and scale effects provides insights into the competitive landscape of AI, where latecomers like China can potentially catch up due to higher marginal returns on resource investments [16][22]. - The AI development index shows that the U.S. and China dominate the global AI landscape, with both countries possessing significant scale advantages, albeit in different areas [18][22]. - The competition between the U.S. and China in AI is characterized by differing strengths, with the U.S. focusing on computational resources and China leveraging its talent pool and application scenarios [19][22]. Group 3: Open Source Promoting External Scale Economies - DeepSeek's open-source model reduces commercial barriers, facilitating broader adoption and innovation in AI applications, which can accelerate the "AI+" process [24][26]. - The open-source approach allows for greater external scale economies, benefiting a wider range of participants compared to closed-source models, which tend to concentrate profits among fewer entities [25][28]. - The potential market size for AI applications is estimated to be about twice that of the computational and model layers combined, indicating significant growth opportunities [27]. Group 4: Innovation Development: From Supply and Assets to Demand and Talent - The success of DeepSeek raises questions about the role of traditional research institutions in innovation, suggesting that market-driven demands may lead to more successful outcomes in technology development [30][31]. - The integration of technological and industrial innovation is essential for sustainable growth, emphasizing the need for a shift from a supply-side focus to a demand-side approach that values talent and market needs [32][33]. - The importance of talent incentives and a diverse innovation ecosystem is highlighted, as smaller firms may be more agile in pursuing disruptive innovations compared to larger corporations [34][36]. Group 5: From Fintech to Tech Finance - The relationship between finance and technology is re-evaluated, with the success of DeepSeek illustrating how financial firms can leverage technological advancements to enhance their competitive edge [36][39]. - The role of capital markets in fostering innovation ecosystems is emphasized, suggesting that a diverse range of participants is necessary for achieving external scale economies [38][39].