来源：美通社 SDK二次开发模式 重构生态合作效率 率先在业内发布"标准化SDK二次开发框架"，彻底改变传统定制化交付模式，合作伙伴可基于统一 SDK自主适配驱动，自定义相关定制功能的配置，大幅降低硬件适配难度、提升适配灵活度、提升产品 改造效率、缩短产品上市时间。 多媒体能力升级 赋能实时交互与复杂场景 连接能力全面增强 打造多元无缝协同 流媒体支持：新增RTSP流媒体和webRTC功能，覆盖实时摄录、直播等场景 多路解码：多路编解码与循环播放，支持广告轮播、多路摄录高并发需求 多摄调控：多摄切换预览，自定义旋转/镜像/帧率参数，支持车载、安全摄录等硬件 北京2025年12月22日 /美通社/ -- 近日，软通动力在自主创新产品发布会上正式发布"软通天鸿操作系统 6"。该操作系统由软通动力子公司鸿湖万联基于OpenHarmony社区版深度定制而成，是一款高可用、高 稳定的商业发行版。本次升级率先推出标准化开发框架、深度融合"软通天鸿智能"百余种端侧视觉算 法与智能分析能力，同时在多媒体能力、连接能力、显示与交互、稳定与安全等多个维度，升级优化 300余项，进一步强化了"芯片适配‑操作系统‑开发套件‑智能终端 ...

开发者平台OpenRouter与美国风投公司安德森·霍洛维茨基金本月联合发布的一份报告显示，在全球范 围内，中国研发的开源模型的使用率已从2024年年末的1.2%飙升至今年8月的近30%。一位匿名的美国 企业家透露，相比使用专有模型，其企业通过采用阿里巴巴的通义千问人工智能模型，每年可节省40万 美元成本。法新社说，美国芯片巨头英伟达、AI公司Perplexity以及斯坦福大学，也在部分业务中使用 通义千问模型。 【环球时报报道 记者 陈子帅】"美中人工智能（AI）博弈正热，一些美国企业选择了中国（技 术）。"法新社22日报道称，尽管美国正在人工智能领域与中国展开竞争，但中国的相关技术却已悄然 进入美国市场，后者的开源人工智能模型赢得越来越多的程序员和美国公司的青睐。 据法新社报道，美国企业之所以选择中国AI技术，是因为包括阿里巴巴、深度求索（DeepSeek）在内 的多家中企推出的"开源"模型，允许程序员对软件部分内容进行定制，以满足自身需求。而OpenAI公 司开发的ChatGPT、谷歌开发的Gemini等，属于"闭源"的生成式人工智能模型，其内部运行机制严格保 密。 对外经济贸易大学国家安全与治理研究院 ...

Core Insights - The article discusses the significance of open-source in the AI era, emphasizing the need for sustainable business models while maintaining openness in the industry [1][3]. Group 1: Conference Overview - The GOBI 2025 Global Open-source Business Innovation Conference gathered over 500 leaders from various sectors to discuss the intersection of open-source, business, and AI [1]. - The conference theme, "Releasing Source Power, Creating the Future," aimed to explore how open-source innovation can translate into sustainable industrial value [1]. Group 2: AI and Open-source Development - Du Yingfen highlighted the necessity of a robust institutional environment for the sustainable development of open-source [4]. - The evolution of open-source from a software development model to a complex industrial ecosystem is driven by the rise of AI, which now encompasses data, algorithms, models, and computing power [6]. - China is transitioning from being a "user" to a significant contributor in the global open-source ecosystem, with projects like openEuler and openHarmony gaining traction [6][7]. Group 3: Entrepreneurial Opportunities - Wang Hua identified the current period as a "golden window" for entrepreneurship in AI and open-source, driven by favorable technological and market conditions [8]. - Entrepreneurs are encouraged to focus on global perspectives and rapid open-source implementation to seize emerging opportunities in AI [11]. Group 4: Commercialization of AI - Jiang Tao discussed the generational leap in the global open-source industry, moving from service-centric models to AI-driven commercial opportunities [12]. - The demand for AI is shifting from pilot projects to core business applications, with a growing preference for domestic models in China [12][14]. - The commercialization speed of AI startups is significantly faster than previous SaaS companies, with a 3-5 times increase noted in the U.S. market [12]. Group 5: Community and Collaboration - The importance of community engagement in open-source projects is emphasized, with contributors encouraged to actively participate and share knowledge [35][37]. - The challenges of maintaining code quality and project coherence in rapidly evolving open-source environments are acknowledged [35][36]. Group 6: Future Trends and Challenges - The article concludes with insights on the future of AI and open-source, highlighting the need for continuous adaptation and collaboration to harness the full potential of AI technologies [23][24].

Core Insights - The article discusses the challenges of maintaining open-source projects, emphasizing that while initiating a project is easy, sustaining it requires significant effort and dedication [1][2] - The GOBI 2025 Global Open-source Business Innovation Conference aims to address these challenges by bringing together successful open-source contributors to share their experiences and strategies [2][14] Group 1: Conference Overview - The GOBI 2025 conference will feature prominent figures from the open-source community, including contributors from projects with over 60,000 stars on GitHub [2][14] - The event will take place on December 21, from 10:00 to 17:15, at the Renaissance Beijing Dongsheng Hotel [5][19] - The conference will include various panels discussing the evolution of open-source communities and the intersection of AI and business [6][19] Group 2: Key Themes and Discussions - The conference will explore how to transition from individual contributions to community-driven projects, focusing on leveraging community power for personal and project growth [3][14] - Discussions will include strategies for converting observers into co-creators, igniting project momentum, and fostering a sense of community among members [3][14] - The event will feature keynote speeches and roundtable discussions on sustainable open-source development and the commercialization of open-source in the AI era [20][21]

罗福莉加入小米后的首次公开演讲，来了！ 智东西12月17日北京现场报道，刚刚，小米举办了年度"人车家全生态"合作伙伴大会，现场人头攒动座无虚席，展区不少展台都已被围观人群 挤满，讨论热度颇高。 ·相比生物演化的稳固根基，AI的发展是"空中楼阁"； ·AI进化的下个起点，一定是有一个能跟物理世界交互的模型； 小米创始人兼CEO雷军此次并未来到现场，小米集团合伙人、集团总裁卢伟冰率先登台演讲，今天第三位演讲的是当前备受关注的原 DeepSeek核心成员、被业内称为"天才少女"的罗福莉，她现在的职位是小米MiMo大模型负责人。 罗福莉在演讲过程中虽然稍显紧张，但她抛出的海量金句却句句令人印象深刻： ·AI正以非线性的方式重演人类大脑6亿年的进化史； ·语言是人类思维和物理世界在符号空间的"投影"； ·下一代智能体系统不是一个"语言模拟器"，而是一个真正理解我们世界、并与之共存的"智能体"； ·算力和数据也并非最终的护城河，真正的护城河，是科学的研究文化与方法，是将未知问题结合模型优化转化为可用产品的能力； ·开源的价值本质上是一种分布式的技术加速主义； ·开源是实现AGI的普惠化，是确保所有人类的智慧共同进化的唯一 ...

Core Viewpoint - NVIDIA's acquisition of SchedMD is seen as a strategic move to expand its competitive edge in the HPC and AI sectors by integrating SchedMD's Slurm system into its ecosystem, thereby enhancing its influence beyond hardware to resource scheduling [1][11][15]. Group 1: SchedMD Overview - SchedMD, founded in 2010, specializes in large-scale computing task scheduling technology [5]. - The core asset of SchedMD is the open-source workload management system Slurm, which efficiently allocates computing resources across numerous devices for tasks such as AI model training and scientific research [6][8]. - Slurm is utilized by over half of the TOP500 supercomputers globally, as well as by major tech companies like Meta and various AI startups [3][9][10]. Group 2: Strategic Importance of the Acquisition - The acquisition allows for low integration costs due to a decade-long collaboration between NVIDIA and SchedMD, facilitating a smooth transition of technology and team integration [12][13]. - The strategic value of the acquisition lies in extending NVIDIA's influence from hardware to scheduling, ensuring that even clients using AMD or Intel chips will rely on NVIDIA's ecosystem through Slurm [14][15]. - This move further solidifies NVIDIA's position among key customer groups, including supercomputing centers, cloud providers, and AI enterprises [16]. Group 3: Future Considerations - NVIDIA has committed to maintaining Slurm's open-source and vendor-neutral attributes, ensuring continued access for global users [18]. - However, there are concerns regarding NVIDIA's ongoing investment in critical projects like Slinky, which supports Slurm-on-Kubernetes services, raising questions about the future stability of related businesses [19][21].

Core Insights - The forum emphasized the importance of green electricity as a fundamental requirement for AI capabilities, highlighting that the future of AI is closely tied to environmental sustainability [1][5] - The discussion pointed out that the end goal of AI is aligned with ESG (Environmental, Social, and Governance) principles, indicating a shift towards zero-carbon initiatives in various sectors [3][7] Group 1: AI and Energy - AI's computational power is fundamentally dependent on electricity, which in turn must transition to green energy sources to meet ESG goals [3][7] - The evolution of data centers from water cooling to liquid cooling is a significant advancement in reducing energy consumption and resource use [3][7] Group 2: Open Source and CVC - The concept of CVC (Corporate Venture Capital) is introduced as a means to invest in startups using open-source platforms, allowing for minimal initial costs for entrepreneurs [4][8] - The marginal cost of development approaches zero when utilizing open-source resources, enabling widespread access and innovation [4][8] - The potential for innovation costs to be nearly zero is highlighted, suggesting a transformative impact on the entrepreneurial landscape in the AI era [4][8]

Core Insights - The report emphasizes that open source is a factual standard and a significant driver of technological innovation in the industry [2] Group 1 - The importance of open source in driving technological advancements is highlighted by ZTE's Li Xiang during the 2026 China Academy of Information and Communications Technology deep observation report meeting [2]

Core Viewpoint - Meta is shifting from an open-source strategy to a closed-source model, marking a significant strategic pivot for the company [11][12][28]. Group 1: New Model Development - Bloomberg reports that Meta is set to release a new model codenamed "Avocado" in spring 2025, which is expected to be closed-source [2][10]. - The closed-source model "Avocado" will utilize AI training from Alibaba's Qwen, indicating a collaboration with third-party models [4][5][10]. Group 2: Market Reaction - Following the news of the collaboration with Alibaba, Alibaba's stock saw a pre-market increase of 4% and closed with a 2.53% gain [6]. Group 3: Strategic Shift - Meta's transition to a closed-source model represents a 180-degree turn from its previous commitment to open-source, which was once considered a core narrative for the company [11][12]. - The shift is seen as a response to the competitive landscape, particularly acknowledging China's advancements in the open-source domain [15]. Group 4: Internal Changes and Leadership - Meta's leadership has undergone significant changes, with the new Chief AI Officer, Alexander Wang, being a strong proponent of closed-source models [21]. - Following the failure of the Llama 4 model, there has been a restructuring within Meta, leading to the marginalization of open-source advocates and a focus on closed-source initiatives [28][30]. Group 5: Talent Acquisition - Meta has invested heavily in acquiring top talent for its AI initiatives, with reports of salaries reaching up to hundreds of millions and personal outreach from CEO Mark Zuckerberg to recruit key researchers [23][25][27]. - The newly formed TBD Lab, which is central to Meta's AI strategy, has been closely monitored by Zuckerberg, indicating a hands-on approach to the new direction [32][33].

Core Insights - Meta is accelerating its adjustment of AI strategy, with the next-generation model "Avocado" being postponed from late 2025 to Q1 2026 and likely to be released in a closed-source format, indicating a shift from its previously open-source approach [2] - The company is increasing its capital expenditure for 2025 to $70-72 billion, focusing on training clusters and data center expansions, which is seen as a foundational investment for its AI initiatives [3] Group 1: Organizational Changes - The delay of Avocado reflects deeper organizational changes, with a significant turnover in AI leadership as the company shifts from an academic-oriented research system to one that emphasizes product implementation and speed [6] - The introduction of external high-end talent, including Alexandr Wang from Scale AI, has accelerated this restructuring, leading to a more closed and startup-like environment within the Meta Superintelligence Labs [6][8] - The AI-related teams have undergone multiple rounds of restructuring and layoffs, with over 600 personnel in foundational research being cut, indicating a move towards a more engineering-focused and commercially driven approach [8] Group 2: Hardware Strategy Shift - Meta's AI strategy overhaul has impacted its hardware roadmap, with a comprehensive review of the Reality Labs hardware department and a slowdown in the development of augmented reality (XR) projects [11] - The company plans to reduce its metaverse budget over the next two years, reallocating resources towards AI models and related technologies such as smart glasses and voice assistants [11] - Meta is transitioning from a primarily self-built infrastructure to a more pragmatic mixed model, expanding partnerships with CoreWeave, Oracle, and Blue Owl Capital to support the high computational demands of closed-source models [11] Group 3: Strategic Direction - The postponement of Avocado signifies a clear strategic pivot for Meta, driven by competitive pressures and the need to deliver investment returns more rapidly [12] - This shift represents Meta's third major strategic migration in over a decade, moving from a focus on mobile internet and the metaverse to a more concentrated effort on closed-source AI models [12] - The current environment reflects a transition from visionary discussions to a focus on ensuring competitive positioning, with all resources being mobilized to avoid being left behind in the evolving landscape [12]