Core Viewpoint - Andrew Tulloch, co-founder and chief architect of Thinking Machines Lab, has left the company to join Meta, despite previously rejecting a $1.5 billion compensation package from Meta [1][18]. Group 1: Andrew Tulloch's Background and Career - Tulloch has a strong academic background, graduating with honors in mathematics and statistics from the University of Sydney and later earning a master's degree in mathematical statistics and machine learning from Cambridge University [8][11]. - He began his career at Goldman Sachs, developing financial products and trading strategies before moving to Facebook (now Meta) in 2012, where he worked for 11 years in machine learning [10][11][6]. - Tulloch's expertise in machine learning was further utilized at OpenAI, where he worked on training models like GPT-4.5 before co-founding Thinking Machines Lab [16][15]. Group 2: Transition to Meta - Tulloch's return to Meta is seen as a "homecoming," as he had previously spent a significant amount of time there [6]. - His departure from Thinking Machines Lab was described as a personal decision, and there was speculation about the reasons behind it, especially given the company's high valuation of $12 billion [4][21]. - The recruitment efforts by Meta included a direct approach from CEO Mark Zuckerberg, who initially sought to acquire Thinking Machines Lab before focusing on hiring Tulloch and other employees [19][20]. Group 3: Compensation and Market Dynamics - Tulloch had previously turned down a $1.5 billion offer from Meta, which included stock options, indicating a potential increase in compensation that may have influenced his decision to join [18][19]. - The article hints at the possibility that Tulloch's compensation package may have increased to $2 billion, reflecting the competitive nature of talent acquisition in the tech industry [21].

Core Insights - The collaboration between AMD and Sony Interactive Entertainment (SIE) has initiated the "Project Amethyst," aiming to integrate AI and machine learning into future gaming hardware and software [1][2] - The partnership will develop foundational AI systems for PC and PlayStation platforms, symbolizing a deep technological integration between AMD's red and PlayStation's blue, resulting in a purple crystal color [1] - The AI advancements will enhance not only image reconstruction but also explore neural frame generation and ray regeneration to improve real-time ray tracing and path tracing efficiency [2] AMD's Next-Generation GPU Technologies - AMD has revealed three core technologies for its next-generation GPU architecture, focusing on AI acceleration, ray tracing efficiency, and memory optimization [3] - The neural array technology is a key strategy for AMD to compete with NVIDIA's Tensor Core, indicating that AI is becoming a core part of the architecture [3] - The "Project Amethyst" will allow AMD and Sony to validate and promote these technologies on millions of gaming consoles, enhancing AMD's competitive edge in ray tracing performance and AI-driven features [3][4] Hardware Upgrades and Innovations - Sony has disclosed hardware upgrades for its next-generation console, with a focus on the collaboration project "Project Amethyst" [4] - Key innovations include Radiance Cores for efficient ray tracing and path tracing, neural arrays for AI rendering, and universal compression technology to reduce memory bandwidth requirements [4][6] - These advancements suggest that the next Sony gaming console, likely the PS6, will be capable of running ray tracing and path tracing games comparable to current PC graphics hardware [6][7] Future Implications - The technologies developed under "Project Amethyst" are expected to be implemented in future AMD GPUs and SoCs, with a timeline indicating these innovations will appear in upcoming gaming consoles in the coming years [7] - The collaboration signifies a strategic alignment between AMD and Sony, enhancing the gaming experience through AI and advanced graphics technologies [5][6]

为应对这一挑战，研究团队提出了一种结合物理模型与机器学习技术的新路径。该方法基于"自动微 分"技术——一种常用于深度学习中计算导数的算法，用于追踪输入变量微小变化对输出的影响。他们 利用这一机制，在分子动力学模拟框架下直接优化氨基酸序列，使其具备预定的物理或功能特性。与依 赖大量数据训练的典型人工智能模型不同，该方法依托已有且足够精确的物理模拟体系，通过梯度优化 高效搜索满足特定功能需求的蛋白质序列，如形成柔性连接结构或响应环境变化的能力。 团队强调，目标并非用数据驱动模型替代物理理解，而是将真实的分子行为规律嵌入设计过程，使生成 的蛋白质序列不仅具备功能性，而且其设计过程本身就根植于自然界真实的动力学原理。由此设计出的 蛋白质是"可微分的"，意味着每一步优化都建立在对系统物理状态连续、精确调控的基础上，而非依赖 黑箱式的预测。 （文章来源：科技日报） 美国哈佛大学与西北大学研究团队合作，开发出一种新型机器学习方法，能够从无序蛋白质中排序，设 计出具有特定性质的内在无序蛋白质（IDPs），从而突破了当前人工智能（AI）工具在解析约30%人类 蛋白质结构上的局限。该成果发表于最新一期《自然·计算科学》。 这类蛋 ...

Core Insights - Zhang Yiming's recent public appearance in China after four years has garnered significant attention, though it may not surpass the interest generated by Jack Ma's return [1][15] - The focus of Zhang's appearance was on talent development, emphasizing the importance of nurturing innovative and resilient individuals [3][4] Group 1: Talent Development and Innovation - Zhang Yiming highlighted the need for talent recruitment and development, noting that many individuals' potential remains untapped [3] - He compared the phenomenon of overfitting in machine learning to the challenges faced by talented individuals in innovation tasks, advocating for independent thinking and practical experience [3] - Zhang's talent philosophy evolved during the growth of ByteDance, where he prioritized curiosity and optimism over traditional experience [4] Group 2: Leadership Transition - In May 2021, Zhang Yiming stepped down as CEO of ByteDance, with co-founder Liang Rubo taking over, as Zhang aimed for greater innovation and creativity within the company [5][6] - Zhang expressed a desire to focus on long-term strategic matters, corporate culture, and social responsibility rather than daily management [6][8] Group 3: Market and Regulatory Environment - The external environment for tech companies is changing, with emerging fields like virtual reality and life sciences beginning to impact daily life [9] - ByteDance's potential IPO has faced delays due to regulatory uncertainties and the need for greater business transparency [12] - Zhang Yiming's movements are seen as a significant indicator of ByteDance's future direction, especially in light of the ongoing TikTok controversies [10][15] Group 4: Public Perception and Media Attention - Zhang Yiming's return to the public eye has sparked discussions about his citizenship status and ByteDance's IPO plans, with rumors circulating frequently [11][12] - The media narrative surrounding Zhang's public appearances often reflects broader themes of corporate leadership and innovation within the tech industry [15]

仪式上，西湖大学校长施一公院士现场发表题为《创新：一条不同寻常的路》的演讲，指出AI时代正在重构知识获取与创新方式；徐汇区区长王华表示 区政府将支持中心融入区域科创生态。 自2021年张一鸣卸任CEO后，字节跳动由联合创始人梁汝波接任，此次创新中心的成立凸显其持续关注AI技术人才培养与长期行业布局。 该机构由张一鸣与上海交通大学ACM班创始人俞勇教授共同发起，定位为民办非营利性组织，旨在培养泛计算机与人工智能领域的青年创新人才。 张一鸣在发言中以机器学习中的"过拟合"现象比喻人才培育痛点，指出部分人才虽具备专业技能，却难以应对创新任务。 他强调中心将聚焦思维活跃性、实践能力与长期主义视野，通过科技史串联多学科知识，在开放环境中培养拥抱不确定性的创新力量。该项目已招募首批 14名16-18岁的预备研究员，未来每年计划招聘30名16-18岁的青少年作为全职预备研究员。 10月9日，据知春创新中心公众号消息，字节跳动创始人张一鸣在卸任首席执行官后首次公开露面，现身上海徐汇知春创新中心开业仪式。 ...

知名机器人专家罗德尼・布鲁克斯（Rodney Brooks）是 iRobot 公司的联合创始人，曾在麻省理工学院 （MIT）深耕数十年。他对特斯拉、以及备受关注的 AI 机器人公司 Figure 等企业的技术路线尤为质疑 ——这些公司试图通过让机器人观看人类执行任务的视频，来教会它们掌握灵活操作的能力。在一篇新 文章中，他将这种方法称为"纯粹的空想"。 长期以来，布鲁克斯还认为，AI 并非像包括埃隆·马斯克（Elon Musk）在内的许多人所宣称的那样，是 一种"关乎人类生存的威胁"。早在 2017 年，TechCrunch 就曾在 MIT 与布鲁克斯探讨过这一话题——当 时的科技格局虽与如今不同，但也并非完全迥异。 当时布鲁克斯就表示，他已开始看到越来越多公司专注于为机器学习制作数据集——这一趋势此后一直 持续。与此相关的是，他还曾提出观点：尽管大型科技公司长期以来在数据掌控量上拥有看似不可逾越 的优势，但这并不意味着它们在机器人领域的胜利是"必然结果"。然而如今，领先的机器人公司仍未能 摆脱这些科技巨头的影响。 此外还有安全问题。全尺寸行走人形机器人需要消耗大量能量才能保持直立。一旦摔倒，它们会具有极 高 ...

活动现场，字节跳动创始人张一鸣久违露面并发言。张一鸣称，自己长期关注人才的招聘与培养，注意到许多人才的潜力尚未被充分挖掘。他以机器学习 中的"过拟合"现象作比，指出有些人专业技能很强，但在创新任务面前却难以发挥。他强调，创新中心希望培养的是思维活跃、富有热情与韧性的青年人 才，鼓励他们独立思考、重视实践，保持长期主义视角，在探索中成长，并学会以平常心拥抱不确定性。 【免责声明】本文仅代表作者本人观点，与和讯网无关。和讯网站对文中陈述、观点判断保持中立，不对所包含内容的准确性、可靠性或完整性提供任何 明示或暗示的保证。请读者仅作参考，并请自行承担全部责任。邮箱：news_center@staff.hexun.com 蓝鲸新闻10月10日讯（记者 武静静）据知春创新中心公众号，10月9日，上海徐汇知春创新中心正式开业，该中心由字节跳动创始人张一鸣、上海交通大 学ACM班创始人俞勇教授共同发起。定位为民办非营利性机构，将面向对泛计算机与人工智能感兴趣的年轻人开放招聘。 本文首发于微信公众号：蓝鲸新闻。文章内容属作者个人观点，不代表和讯网立场。投资者据此操作，风险请自担。 ...

Core Viewpoint - The controlling shareholder and actual controller of Jingbeifang (002987.SZ) have reduced their shareholding, triggering a change in equity that touches the 1% integer multiple threshold [1][2]. Group 1: Shareholding Changes - The controlling shareholder, Yuandao Investment, plans to reduce its holdings by up to 26 million shares, representing 3% of the total share capital, within three months from the announcement date [1]. - From September 8 to October 9, 2025, Yuandao Investment has cumulatively reduced its holdings by 8,808,316 shares, accounting for 1.02% of the total share capital [2]. - The shareholding ratio of the controlling shareholder and actual controller has decreased from 58.00% to 56.98% following this reduction [2]. Group 2: Financial Impact - Based on an average price of 21.97 yuan per share, Yuandao Investment has realized approximately 194 million yuan from this reduction [3]. - The company was listed on the Shenzhen Stock Exchange on May 7, 2020, with an initial offering price of 23.04 yuan per share and a total issuance of 40.17 million shares [3]. - The total funds raised during the IPO amounted to 925.52 million yuan, with a net amount of 865.55 million yuan after deducting issuance costs [3][4].

Core Insights - A research team from MIT has developed a new type of 3D printed aluminum alloy that exhibits five times the strength of traditional cast aluminum alloys and is 50% stronger than alloys designed without machine learning assistance [1] Group 1: Material Development - The new alloy is a composite of aluminum and other elements, with the research team utilizing simulation and machine learning to significantly narrow down candidate materials, evaluating only 40 compositions compared to millions in traditional methods [1] - The microstructure of the new alloy contains more fine precipitates, allowing it to maintain stability even at extreme temperatures of 400°C [1] Group 2: Applications and Benefits - This 3D printed aluminum alloy is expected to be used in manufacturing components such as jet engine fan blades, offering lighter, stronger, and more heat-resistant products compared to current materials like titanium alloys, which are over 50% heavier and cost ten times more than aluminum [1] - The use of lighter and stronger materials for fan blades could significantly reduce energy consumption in the transportation sector [2] - The advantages of 3D printing technology, including complex shapes, material savings, and design freedom, make this alloy suitable for high-end vacuum pumps, automotive cooling systems, and data center cooling equipment [2]

Group 1 - The core viewpoint of the report indicates that global market behavior and pricing show signs similar to past bubbles, but with key differences such as the tech sector's growth being driven by fundamental growth rather than irrational speculation [1] - The strongest leading companies have exceptionally robust balance sheets, contrasting with typical bubble scenarios where competition and investor enthusiasm are rampant [1] - The dominance of a few existing giants in the artificial intelligence sector is noted, which differs from the competitive frenzy often seen in bubble periods [1] Group 2 - The report suggests that the fate of leading tech stocks increasingly relies on their underlying physical infrastructure, with rising electricity demand necessitating real investments in power generation and distribution [2] - This shift is expected to create broader growth and return prospects for industries such as energy, resources, real estate, and transportation [2] - The leading tech giants of the 2020s are likely to continue dominating their fields, while rapid innovation, particularly in machine learning and AI, may give rise to a new wave of tech star companies [2]