Core Viewpoint - The article highlights the rapid development and commercialization of humanoid robots, marking 2023 as a pivotal year for the industry, with significant advancements in technology and market presence [9][39]. Group 1: Humanoid Robot Market Development - The Beijing Yizhuang Robot Half Marathon showcased the competitive capabilities of humanoid robots, drawing attention from both established companies and startups [4][6]. - Many professional institutions define 2023 as the year of mass production for humanoid robots, with 11 manufacturers initiating production plans, including notable names like UTree Technology and UBTECH [9]. - The global humanoid robot market was valued at $1.017 billion in 2022 and is projected to reach $15.1 billion by 2030, with a CAGR exceeding 56% from 2024 to 2030 [17]. Group 2: Company Insights - Baiwei Storage - Baiwei Storage has launched products suitable for the robotics sector, including eMMC, LPDDR4X/5/5X, UFS, and BGA SSDs, and is actively promoting these products in the market [30]. - The company has successfully mass-produced its first domestically developed eMMC controller, SP1800, which offers high performance and reliability [30]. - Baiwei's revenue for the previous year reached 6.7 billion yuan, a significant increase of 86.5% year-on-year, with a net profit of 160 million yuan, marking a turnaround from losses [33]. Group 3: Supply Chain and Product Applications - The UTree Go2 robot dog utilizes chips from multiple companies, including Baiwei Storage's LPDDR4X memory and eMMC storage, indicating the company's strong position in the supply chain [21][39]. - Baiwei's products are already integrated into the supply chains of major companies like Meta and Google, particularly in wearable devices, which have seen substantial growth [32]. - The company is constructing a wafer-level advanced packaging factory, expected to enhance its capabilities in providing comprehensive storage and advanced packaging solutions [36][37].

该工作由通用人工智能研究院 × 北京大学联手打造。第一作者郑欣悦为通用人工智能研究院研究员，共同一作为北京大学人工智能研究院博士生林昊苇， 通讯作者为北京大学助理教授梁一韬和通用人工智能研究院研究员郑子隆。 开发能在开放世界中完成多样任务的通用智能体，是 AI 领域的核心挑战。开放世界强调环境的动态性及任务的非预设性，智能体必须具备真正的泛化能力 才能稳健应对。然而，现有评测体系多受限于任务多样化不足、任务数量有限以及环境单一等因素，难以准确衡量智能体是否真正 「 理解 」 任务，或仅是 「 记住 」 了特定解法。 为此，我们构建了 Minecraft Universe （ MCU ） —— 一个面向通用智能体评测的生成式开放世界平台。 MCU 支持自动生成无限多样的任务配置，覆 盖丰富生态系统、复杂任务目标、天气变化等多种环境变量，旨在全面评估智能体的真实能力与泛化水平。该平台基于高效且功能全面的开发工具 MineStudio 构建，支持灵活定制环境设定，大规模数据集处理，并内置 VPTs 、 STEVE-1 等主流 Minecraft 智能体模型，显著简化评测流程，助力智 能体的快速迭代与发展。 开放世界 ...

每经记者｜张蕊 每经编辑｜陈旭 没有安全，数据流通就无从谈起；没有流通，数据就难以赋能千行百业。 5月10日，以"数智无界 安全共生"为主题的2025中国数谷·西湖论剑大会在杭州开幕。 中国计算机学会（CCF）原理事长、CCF计算机博物馆馆长梅宏在大会主论坛上提到，没有数据就不可能有智能，就像燃料和火箭的关系一样。现在业界经 常讲本轮AI革命的三要素：算法、数据、算力，实际上数据是关键。 推动AI（人工智能）向AGI（通用人工智能）演进，数据与AI的深度融合非常重要，但现在缺乏高质量的数据集致数据流通受限，这是不是一个关键的堵 点？ 对于《每日经济新闻》记者提出的这一问题，安恒信息技术股份有限公司（SH688023，股价49.18元，总市值50.30亿元，以下简称安恒信息）高级副总裁、 研究院院长王欣表示，数据的流通受限确实是一个关键问题。 私有数据是让模型落地到场景里发挥价值的关键因素 王欣对《每日经济新闻》记者表示，整个模型从构建到应用落地分为两个方面：一方面，现在"大厂"做一些基础的通用模型训练，更多用到的是互联网的网 页数据。这里存在一些具体数据层面的安全问题，主要是数据质量问题，这影响了模型本身的能 ...

Core Insights - The article discusses the evolution of AI models using games as a testing ground, highlighting the recent achievement of Google's AI model Gemini 2.5 Pro in independently completing the original Pokémon game, which has reignited interest in AI capabilities [4][30]. Group 1: AI Development and Gaming - AI has been tested through games for nearly a decade, with notable milestones including AlphaGo's victory over human players in Go and DeepMind's success in games like DOTA2 and StarCraft II [2][3]. - The use of games as a benchmark for AI intelligence remains prevalent, as demonstrated by Gemini's recent accomplishment, which was celebrated by Google's CEO and DeepMind's head [4][5]. Group 2: Challenges in AI Learning - The Moravec's paradox suggests that tasks perceived as easy for humans can be significantly more challenging for AI, which is exemplified by Gemini's achievement in Pokémon [6][7]. - The process of AI learning in games like Pokémon is complex, requiring the AI to develop its own understanding and strategies without predefined rules or guidance [16][17]. Group 3: Comparison of AI Models - Anthropic's Claude 3.7 struggled to progress in Pokémon, achieving only three badges after a year of iterations, while Gemini completed the game with approximately 106,000 actions, significantly fewer than Claude's 215,000 actions [11][30]. - The differences in performance between Claude and Gemini are attributed to their respective frameworks, with Gemini's agent harness providing better input processing and decision-making capabilities [34][35]. Group 4: Implications for AI Research - The ability of AI to navigate and complete games like Pokémon indicates its potential for independent learning and problem-solving in real-world scenarios [37][38]. - The choice of Pokémon as a training ground reflects the game's themes of growth, choice, and adventure, paralleling the journey of AI in understanding complex rules and environments [39][40].

Core Insights - The new fund, Creekstone Ventures, is focusing on AI investments and aims to connect closely with founders [1][2] - The fund plans to raise several tens of millions of dollars and has already identified two projects in the AI sector [2][3] - The investment strategy emphasizes vertical intelligence (ASI) and aims to support innovative projects in the AI space [9][15] Investment Focus - The fund will allocate approximately 60-70% of its capital to AI applications, particularly in consumer-oriented (ToC) sectors, and 15-20% to AI hardware [4][5] - The fund is particularly interested in projects that focus on vertical intelligence, aiming to develop super intelligence in specific fields [15][16] - There is a strong belief in the potential of Chinese AI applications to lead globally, as evidenced by the rapid growth of companies like DeepSeek [5][9] Project Examples - The fund has already committed to an AI coding company and an AI glasses company, with a focus on projects that simplify functionality rather than adding unnecessary features [2][3] - The investment in the AI coding project is seen as timely, given the founder's recent transition from a large tech company [2][3] Market Dynamics - The current market is experiencing rising valuations for projects, influenced by supply and demand dynamics and a reduction in the total capital available from traditional dollar funds [22][23] - The fund aims to differentiate itself by engaging deeply with founders and providing support that goes beyond traditional investment approaches [24][28] Entrepreneurial Support - Creekstone Ventures intends to offer emotional and strategic support to founders, leveraging their own experiences as entrepreneurs [6][7] - The fund emphasizes the importance of maintaining close relationships with portfolio companies, facilitating daily communication and collaboration [8][19] Future Outlook - The fund is optimistic about the potential for coding AI and believes that the Chinese market has significant opportunities in this area [16][17] - The focus will also be on identifying and investing in key components that support the development of future AI agents [15][16] Conclusion - Creekstone Ventures positions itself as a partner to entrepreneurs, aiming to foster innovation in the AI sector while navigating the evolving market landscape [28][30]

Group 1: Founder Psychology and Roles - Eric Schmidt emphasizes the difference between founders and professional managers, stating that founders are visionaries while professional managers are "amplifiers" who help scale ideas [4][10] - Schmidt reflects on his experience at Google, noting that he was not a typical entrepreneur but rather a professional manager who contributed during the company's scaling phase [3][4] - He discusses the challenges of attracting talent, highlighting that many talented individuals often choose to start their own companies instead of joining established firms [3][5] Group 2: Market Dynamics and Startup Ecosystem - Schmidt points out that many startups are often acquired for their talent rather than their products, indicating a market structure that can be inefficient [6][7] - He notes that the majority of startups fail, with traditional venture capital experiences suggesting that 4 out of 10 will fail completely, and 5 will become "zombies" with no growth potential [7] - The conversation highlights the importance of competition for startups, suggesting that true leadership is demonstrated when facing challenges from larger companies [11][12] Group 3: AI and Future Trends - Schmidt believes that AI is currently underestimated rather than overhyped, citing the scaling laws that drive AI advancements [33][34] - He discusses the potential of AI to transform business processes and scientific breakthroughs, emphasizing the importance of understanding how humans will coexist with advanced AI systems [35][39] - The conversation touches on the competitive landscape between the U.S. and China in AI development, with China investing heavily in AI as a national strategy [41][42] Group 4: Talent Acquisition and Management - Schmidt stresses the importance of attracting top talent by creating an environment where individuals feel they are solving significant problems [18][20] - He differentiates between "rockstar" employees who drive change and "mediocre" employees who are self-serving, advocating for the retention of the former [21][22] - The discussion includes insights on how to identify and nurture high-potential talent within organizations [24][25] Group 5: Challenges in AI Development - Schmidt highlights the challenges of defining reward functions in reinforcement learning, which is crucial for AI's self-learning capabilities [51] - He warns about the potential pitfalls of over-investing in AI infrastructure without a clear path to profitability, suggesting that many companies may face economic traps [47][48] - The conversation concludes with a call for companies to focus on the most challenging problems in AI, as solving these will yield the most significant rewards [52][53]

Core Viewpoint - China's foreign trade has shown resilience and growth despite the challenges posed by the US tariff war, with significant increases in both exports and imports in the first four months of the year [1][19]. Group 1: Trade Data Overview - In April, China's total goods trade reached 3.84 trillion yuan, growing by 5.6%, with exports at 2.27 trillion yuan (up 9.3%) and imports at 1.57 trillion yuan (up 0.8%) [1]. - The overall foreign trade growth for the first four months was 2.4%, marking the second-highest level for the same period historically [1]. Group 2: Factors Driving Growth - High-tech products have been a significant driver of export growth, with exports of high-tech products reaching 1.52 trillion yuan, an increase of 7.4%, accounting for 18.1% of total exports [9][20]. - The diversification of markets has helped mitigate the impact of tariffs, with exports to the US dropping below 15% of total exports, while emerging markets contributed over 60% of the growth [19][20]. Group 3: Industry Innovations and Developments - Companies are leveraging advanced technologies, such as smart home products and automation, to enhance production efficiency and open new markets [3][12]. - The marine engineering and shipbuilding sectors have seen substantial growth, with exports from Shandong province exceeding 16 billion yuan, reflecting a shift towards a more integrated industrial ecosystem [11]. Group 4: Role of Private Enterprises - Private enterprises have emerged as a crucial force in sustaining foreign trade growth, with their exports accounting for 56.9% of total trade, growing by 6.8% in the first four months [18][20]. - The innovation capabilities of these enterprises have been bolstered by high tariffs, prompting accelerated research and development efforts [20].

4月25日，习近平总书记在主持二十届中共中央政治局第二十次集体学习时强调："面对新一代人工智能 技术快速演进的新形势，要充分发挥新型举国体制优势，坚持自立自强，突出应用导向，推动我国人工 智能朝着有益、安全、公平方向健康有序发展。"人工智能是引领这一轮科技革命和产业变革的战略性 技术。加快发展新一代人工智能，是我们赢得全球科技竞争主动权的重要战略抓手。习近平总书记高度 重视我国新一代人工智能发展，《习近平经济文选》第一卷中不少著作都对此作出深刻论述。比如， 《贯彻新发展理念，建设现代化经济体系》指出："推动互联网、大数据、人工智能和实体经济深度融 合"；《发展数字经济，抢占未来发展制高点》指出："要推动互联网、大数据、人工智能同产业深度融 合，加快培育一批'专精特新'企业和制造业单项冠军企业"；《加快构建新发展格局，着力推动高质量 发展》指出："推动战略性新兴产业融合集群发展，构建新一代信息技术、人工智能、生物技术、新能 源、新材料、高端装备、绿色环保等一批新的增长引擎"；等等。 人工智能大模型是通过深度学习技术在海量数据上训练出来的、拥有大规模参数和复杂计算结构的机器 学习模型，能够理解和生成多模态内容，具 ...

孙正义的职业生涯，处处 彰 显出他勇于豪赌、出手不凡的特质。图片来源：Haruyoshi Yamaguchi—Bloomberg/Getty Images 在唐纳德·特朗普的第二任期之初，这位新任美国总统迎来了一次与部分核心盟友共同亮相的机会。在出席活动的领导人里，有些是意料 之中的，例如内阁提名人选、国会领导人、超级捐赠者埃隆·马斯克，不过，至少有一位嘉宾的现身令人颇感意外：日本亿万富翁、科技 领域投资者孙正义（Masayoshi Son）。 今年1月21日，孙正义在白宫罗斯福厅（White House Roosevelt Room）成为焦点，他宣布软银集团（SoftBank Group，孙正义旗下总部位 于日本东京的大型企业集团）将为"星际之门"（Stargate）项目提供大部分资金。该项目是软银携手OpenAI和甲骨文（Oracle）达成的一 项雄心勃勃的合作项目，旨在全力助推美国巩固在人工智能领域里的领先地位。孙正义为了可以在讲台上被众人看见，特意站在一个箱 子上，他的身旁是甲骨文的董事长拉里·埃里森和OpenAI的首席执行官萨姆·奥尔特曼。孙正义向特朗普承诺，"星际之门"项目将投入高 达5,000亿 ...

Core Viewpoint - The current period is a golden window for the development of the robotics industry, driven by technological paradigm shifts that reshape product logic and market dynamics [3][12][15]. Group 1: Industry Development Stages - The robotics industry is in a "Spring and Autumn" era, characterized by diverse technological routes and business viewpoints, with significant innovation and exploration occurring [16][18][19]. - The transition from the "Spring and Autumn" era to a "Warring States" era is anticipated, where industry dynamics will become clearer and competitive outcomes will emerge [18][19]. Group 2: Key Conditions for Industry Maturity - The maturity of the robotics industry relies on several core capabilities: advancements in computing power, energy density of batteries, and continuous optimization of AI models [10][14]. - The demand side is also evolving, with an aging population and increasing service consumption among younger demographics, creating a significant market opportunity for robotics [11][12]. Group 3: Defining Revolutionary "Big Terminals" - A revolutionary "big terminal" must meet two criteria: a product price above 10,000 yuan and an annual shipment volume in the tens of millions to drive industry maturity [7][8]. Group 4: Product-Centric Approach - The essence of the industry lies in delivering tangible products rather than mere concepts, emphasizing the importance of a product-driven approach to business development [24][25]. - A successful product strategy involves prioritizing vertical applications, leveraging mature technologies, and obtaining diverse and sustained data from real-world environments [45][49]. Group 5: Path to General Robotics - The path to achieving general robotics involves starting from vertical scenarios, iterating with platform technologies, and gradually transitioning from specialized to general-purpose products [41][42]. - The ultimate goal is to create robots that provide high-quality services in various environments, emphasizing intelligent mobility and breakthrough interaction capabilities [47][49].