编辑 | summer 回望过去12 个月，女性影响力的叙事逻辑发生了根本性的变化。 很难想象，就在年初，人们还在争论女性是否应该去"战斗"；而到了年末，郑钦文已经用她的网球拍证明了"力量"本身就是一种女性语言；在DeepSeek的 开源代码里，同样隐藏着无数女性工程师的力量；至于韩江，她则让世界意识到，有时候拒绝吃饭、拒绝说话，竟然可以爆发出比呐喊更震耳欲聋的回 响。 如果这些名字让你感到兴奋或复杂，那你是对的。2025年已过，我们回顾了这一年里不论是在硅谷的实验室、巴黎的红土赛场，还是在杭州的董事会里， 重塑了世界规则的女性人物。她们不再寻求"被赋权"，她们本身就是"权力"。 PART 1 The World Modeler：世界建模者 只要 AI 还在狂飙，就总有人在思考如何让它不仅仅是"聊天"，而是"看见"。 Fei-Fei Li（李飞飞）：World Labs创始人 / "空间智能"教母 在TOPHER看来，这不仅是技术的突破，更是女性科学家特有的长期主义胜利：不追逐短期热点，而是构建AI与物理世界交互的根本基石。 DeepSeek女性工程师们：开源大模型的幕后推手 2025年初，DeepSeek以 ...

【环球时报记者 倪浩 环球时报驻韩国特约记者 黎枳银 环球时报特约记者 任重】2025年，美国关税政策持续冲击多边贸易体系；人工智能（AI） 领域全球投资热情高涨，但泡沫风险引发警惕；经济不确定性和对美元信用风险的担忧推高国际金价。在此复杂背景下，多家外媒岁末刊发报道 认为，中国经济在2025年展现出韧性与活力，股市表现、AI大模型发展、软实力出海等多个领域亮点纷呈，正吸引国际企业与市场共同聚焦并期 待未来的"中国机遇"。 化解外部冲击，外贸韧性十足 2025年，美国挑起关税摩擦是贯穿全年的世界经济话题，众多国家面临高关税抑制需求的挑战。在这一背景下，今年2月至11月，中国货物贸易进 出口已连续10个月保持增长。高盛在近期的报告中预测，2025年全年中国出口同比增速有望达到8%，将进一步凸显中国产品在全球市场中的竞争 力。 燃市场做多热情。同时，中国在中美贸易对峙中展现出来的在稀土等领域的优势，进一步提振了市场情绪。贝莱德、富达国际等海外基金公司纷 纷表示，明年中国市场可能迎来更多资金流入，有望进一步推动实体经济增长。 彭博社在报道中说，面对美国的关税政策，中国通过积极拓深欧洲、拉美、非洲及其他海外市场，基本 ...

Core Insights - The article discusses the rapid development of AI in 2025, highlighting ten key terms that reflect how AI is reshaping industries and society. Group 1: AI Concepts - Vibe Coding redefines programming by allowing developers to express goals in natural language, with AI generating the necessary code [2] - Reasoning models have emerged as a core focus in AI discussions, enabling complex problem-solving through multi-step reasoning [3] - World Models aim to enhance AI's understanding of real-world causality and physical laws, moving beyond mere language processing [4] Group 2: Infrastructure and Investment - The demand for AI has led to the construction of super data centers, exemplified by OpenAI's $500 billion "Stargate" project, raising concerns about energy consumption and local impacts [5] - The AI sector is experiencing a capital influx, with companies like OpenAI and Anthropic seeing rising valuations, though many are still in the high-investment phase without stable profit models [6] Group 3: AI Challenges and Trends - The term "intelligent agents" is popular in AI marketing, but there is no consensus on what constitutes true intelligent behavior [7] - Distillation technology allows smaller models to learn from larger ones, achieving high performance at lower costs [8] - The concept of "AI garbage" reflects public concern over the quality and authenticity of AI-generated content [9] Group 4: AI in Real-World Applications - Physical intelligence remains a significant challenge for AI, as robots still require human intervention for complex tasks [10] - The shift from traditional SEO to Generative Engine Optimization (GEO) indicates a change in how brands and content creators engage with AI-driven information retrieval [11]

Core Insights - Liang Wenfeng, founder of DeepSeek, has been recognized as one of the top ten scientific figures of 2025 by Nature, being labeled a "technology disruptor" for his contributions to AI [1][24] - DeepSeek's R1 model has demonstrated that the perceived gap in AI capabilities between the US and China may not be as significant as previously thought, challenging existing narratives in the AI landscape [5][7] Company Overview - DeepSeek, founded in 2023 by Liang Wenfeng in Hangzhou, has developed a powerful yet affordable AI model, R1, which excels in solving complex tasks by breaking them down into steps [5][13] - The R1 model is the first of its kind to be released with open weights, allowing researchers to download and adapt it for their own applications, significantly impacting the AI research community [7][8] - DeepSeek's commitment to transparency is evident as it was the first mainstream LLM to undergo peer review, with the company publicly sharing the technical details of R1's construction and training [8] Market Impact - The success of DeepSeek has inspired other companies in both China and the US to release their own open-source models, indicating a shift in the competitive landscape of AI development [7] - Despite R1's capabilities being comparable to leading US models, its training costs are significantly lower, with some estimates suggesting that training costs for models like Meta's Llama 3 are over ten times higher [9][15] Leadership and Vision - Liang Wenfeng's background as a former financial analyst who applied AI algorithms to the stock market has shaped his vision for DeepSeek, focusing on achieving general artificial intelligence [17][20] - The company prioritizes individual potential over experience in its hiring practices, fostering a flat organizational structure that empowers researchers to choose their research directions [20] Societal Integration - DeepSeek's models are becoming integral to daily life in China, with local governments utilizing them for chatbots and assisting citizens, reflecting a broader trend of AI integration into economic development [20] - The company is seen as a symbol of China's transformation from a follower to an innovator in the AI field, with expectations for the upcoming R2 model to further this narrative [21][23]

Group 1 - The core focus of the article is the recognition of Chinese AI company DeepSeek's founder Liang Wenfeng and geoscientist Du Mengran in the Nature magazine's annual "Nature 10" list, highlighting significant scientific figures for 2025 [1][2] - Liang Wenfeng's company DeepSeek launched the powerful and cost-effective R1 model in January, which has been noted to challenge the perceived dominance of the US in the AI field [1] - Du Mengran's groundbreaking exploration into the hadal zone, where she and her team discovered the deepest known animal ecosystem on Earth, is also highlighted [1] Group 2 - The "Nature 10" list is compiled by the editors of Nature magazine and is not a ranking or award, but rather a recognition of significant scientific advancements and the individuals involved [2] - The list aims to honor contributions to new fields, breakthroughs in medicine, commitment to scientific integrity, and the formulation of global policies that save lives [2] - The inclusion of these individuals reflects the collective efforts to understand and protect the natural world, which is a key reason for their recognition in this year's list [2]

Group 1 - The global macro environment has changed frequently over the past 12 months, challenging traditional market rules and prompting investors to seek long-term opportunities [1] - In the first half of 2025, international stocks represented by the MSCI All Country World Index (excluding the US) outperformed US large-cap stocks represented by the S&P 500, reversing the long-standing dominance of US equities [1] - Despite the strong performance of international growth stocks, their valuations remain relatively low compared to the significantly expanded valuations of US tech stocks, which have been supported by strong earnings and returns [1] Group 2 - The MSCI All Country World Index (excluding the US) is heavily weighted towards value sectors, with financials, energy, materials, and industrials making up 61%, while structural growth sectors like technology have a lower weight [2] - Historical data indicates that high-growth companies tend to outperform their slower-growing peers, suggesting that passive strategies tracking broad indices may miss opportunities for excess returns [2] Group 3 - Growth stocks encompass a diverse range of companies with varying characteristics, and their growth drivers can change over time [3] - Growth companies can be categorized into emerging growth companies, which are often disruptors in developing industries with significant upside potential, and stable compounding growth companies, which have established profitability and clear growth drivers [3] Group 4 - Understanding structural trends is crucial in an increasingly uncertain global macroeconomic environment, as these trends can help well-managed companies seize opportunities and enhance growth potential [4] - Artificial intelligence (AI) is a prominent global trend, with new generative AI models emerging, such as DeepSeek's R1 model, which offers competitive performance at lower costs, facilitating broader access to AI technology [4][5] - The luxury goods sector is benefiting from direct-to-consumer sales models, allowing brands to control distribution, pricing, and customer experience, thus enhancing brand value and profit margins [5] Group 5 - The transportation sector is undergoing significant transformation driven by electrification, autonomous driving technology, and evolving usage patterns, creating long-term growth opportunities for innovative companies [5] - In emerging markets, the rapid development of fintech and e-commerce presents attractive structural growth opportunities, as digital financial services and online consumption are accelerating due to increased smartphone penetration and an underserved banking user base [5] Group 6 - Investors in international growth stocks have reasons to reassess their investment strategies due to heightened geopolitical instability and rapid technological advancements reshaping the global economic landscape [6] - Historical experience shows that well-managed and innovative international companies can provide substantial long-term returns, suggesting that current market uncertainties may present growth opportunities for investors with analytical capabilities and long-term perspectives [6]

Core Viewpoint - The Trump administration has launched the "Genesis Project," aimed at consolidating resources from the federal government, tech companies, universities, and national laboratories to create a unified AI digital platform for accelerating scientific breakthroughs across various fields [1][3][6]. Group 1: Project Overview - The "Genesis Project" is described as the largest mobilization of federal scientific resources since the Apollo program, with the goal of transforming the way scientific research is conducted and significantly speeding up scientific discoveries [1][6]. - The initiative will prioritize areas such as biotechnology, critical materials, nuclear fission and fusion, quantum information science, and semiconductors [3][7]. - The project mandates specific timelines for the Department of Energy to complete tasks related to cataloging resources and demonstrating initial capabilities within nine months [4][7]. Group 2: Industry Implications - The project signals a shift towards a "federalized, automated, and closed-loop" AI infrastructure, which may raise concerns about potential subsidies for large tech companies [1][3][12]. - Major partnerships have been formed with influential AI and computing firms, including OpenAI, Google, Microsoft, and NVIDIA, indicating a strong collaboration between the government and private sector [4][6]. - The initiative is seen as a response to the competitive landscape of AI development, particularly in light of advancements made by countries like China [6][12]. Group 3: Challenges and Concerns - There are significant concerns regarding the project's funding sources, intellectual property rights, and the lack of clarity on how it will support smaller AI labs facing high operational costs [12][13]. - The energy requirements for the AI industry are projected to be substantial, with estimates suggesting a need for at least 50 gigawatts of power by 2028, raising questions about the adequacy of the U.S. energy infrastructure [8][12]. - Critics argue that the project may inadvertently serve as a "backdoor subsidy" for large tech firms, potentially undermining smaller players in the AI space [12][13].

Core Points - The U.S. government has launched the "Genesis Project," an AI research initiative aimed at uniting large tech companies, academia, and government to ensure the U.S. maintains its lead in the AI race [1][2] - The initiative is compared to the Apollo program, marking it as the largest mobilization of U.S. scientific resources since then [3] Group 1: Objectives and Structure - The Genesis Project aims to transform scientific research and accelerate discoveries by integrating AI into various fields such as healthcare, energy, and manufacturing [2][3] - The initiative will establish a digital platform to centralize national scientific data, computational resources, and AI tools [2] Group 2: Funding and Political Context - It remains unclear how the Genesis Project will be funded, with indications that Congress may need to provide additional support [4] - The initiative reflects President Trump's emphasis on AI during his second term, following previous announcements of significant investments in AI infrastructure [5] Group 3: Industry Response and Challenges - Major tech companies like NVIDIA and Dell have shown interest in the project, indicating a strong private sector response [2] - The project faces political backlash, with concerns about over-regulation at the state level potentially hindering AI investment [6]

Core Insights - The narrative of artificial intelligence (AI) development is undergoing a fundamental shift, moving from algorithm breakthroughs to being constrained by physical world limitations, including energy supply and geopolitical factors [2][10][12] - The competition in AI is increasingly focused on reasoning capabilities, with a shift from simple language generation to complex problem-solving through multi-step logic [3][4] - The AI landscape is expanding with three main camps: closed-source models led by OpenAI, Google, and Anthropic, and emerging open-source models from China, particularly DeepSeek [4][9] Group 1: Reasoning Competition and Economic Dynamics - The core of the AI research battlefield has shifted to reasoning, with models like OpenAI's o1 demonstrating advanced problem-solving abilities through a "Chain of Thought" approach [3] - Leading AI labs are competing not only for higher intelligence levels but also for lower costs, with the Intelligence to Price Ratio doubling every 3 to 6 months for flagship models from Google and OpenAI [5] - Despite high training costs for "super intelligence," inference costs are rapidly decreasing, leading to a "Cambrian explosion" of AI applications across various industries [5] Group 2: Geopolitical Context and Open Source Movement - The geopolitical landscape, particularly the competition between the US and China, shapes the AI race, with the US adopting an "America First" strategy to maintain its leadership in global AI [7][8] - China's AI community is rapidly developing an open-source ecosystem, with models like Qwen gaining significant traction, surpassing US models in download rates [8][9] - By September 2025, Chinese models are projected to account for 63% of global regional model adoption, while US models will only represent 31% [8] Group 3: Physical World Constraints and Energy Challenges - The pursuit of "super intelligence" is leading to unprecedented infrastructure investments, with AI leaders planning trillions of dollars in capital for energy and computational needs [10][11] - Energy supply is becoming a critical bottleneck for AI development, with predictions of a significant increase in power outages in the US due to rising AI demands [10] - AI companies are increasingly collaborating with the energy sector to address these challenges, although short-term needs may lead to a delay in transitioning away from fossil fuels [11] Group 4: Future Outlook and Challenges - The report highlights that AI's exponential growth is constrained by linear limitations from the physical world, including capital, energy, and geopolitical tensions [12] - The future AI competition will not only focus on algorithms but will also encompass power, energy, capital, and global influence [12] - Balancing speed with safety, openness with control, and virtual intelligence with physical reality will be critical challenges for all participants in the AI landscape [12]

Core Insights - The global competition among tech giants in AI infrastructure investment has intensified, with Alibaba announcing a plan to invest 380 billion yuan in AI infrastructure and Nvidia committing up to 100 billion USD to OpenAI for building AI data centers [1][2] - The focus of competition has shifted from model innovation to computing power, driven by the increasing demand for AI applications across various industries [2][3] - Tech giants are adopting differentiated strategies to build diverse ecosystems, with unique technological advantages allowing them to attract specific partners and enhance their competitive edge [3][4] Investment Trends - Alibaba's significant investment in AI infrastructure signals a broader trend among tech giants to enhance their capabilities in AI [1] - Nvidia's investment in OpenAI highlights the growing importance of partnerships in the AI infrastructure space [1][2] Competitive Landscape - The competition is evolving from a focus on algorithm breakthroughs to large-scale expansion of AI infrastructure, reflecting both technological and market dynamics [2][3] - Companies like OpenAI, Nvidia, and Oracle are forming strategic alliances to create closed-loop ecosystems, while Alibaba aims to build a comprehensive stack from chips to platforms [3][4] Ecosystem Development - The construction of ecosystems by tech giants is becoming more complex and diverse, with different players choosing various technological paths [3][4] - A thriving ecosystem can provide resources, application scenarios, and user feedback, fostering continuous innovation and reinforcing competitive advantages [3][4] Industry Evolution - The AI infrastructure competition is driving a shift from "closed innovation" to "open co-creation," with companies integrating AI into various business sectors [5][6] - The future competitiveness will depend not only on computing power or model parameters but also on the ability to deeply integrate industries [5][6]