在科技与产业交汇处，始终有一群推动时代进步、改变行业格局、启发未来方向的杰出人士。 他们是引领技术突破的科学家，是以技术与产品定义时代的创业者，是让科技真正走向产业的管理者， 也是以科技创新重塑商业逻辑的决策者。无论来自实验室、企业，还是开源社区，他们共同构成了科技 叙事中的创造力、行动力与影响力。 作为钛媒体T-EDGE最重要的年度评选，EDGE AWARDS始终以"价值"为核心，着眼于世界前沿，是具 有权威性、先锋性和敏锐挖掘力的全球创新榜单。12月8日至21日（北京时间），钛媒体集团携手 NextFin.AI、巴伦中国举办的2025 T-EDGE 全球对话正式开启。 陈天桥 盛大集团创始人、董事长兼CEO，天桥脑科学研究院创始人 2025年，陈天桥聚焦AI驱动科学，投入10亿美元算力以及PI孵化器等全面支持。他提出"发 现式智能"是真正意义的通用人工智能重磅理念，引发全球关注，旗下团队2025年围绕发现 式智能的关键能力，发布了预测大模型MiroMind ODR、开源记忆系统EverMemOS、数字人 框架Mio等，多次获得全球行业榜单第一，并成立尖峰智能实验室聚焦类脑大模型研究。 他 支持的脑虎科技和 ...

Core Insights - By 2025, the global focus of technological competition has shifted to language models, marking a transition from a "Spring and Autumn" period of "hundred models war" to a "Warring States" era where major companies prioritize "value realization" over mere parameter scale competition [1] - Language models are reshaping the underlying logic of the digital economy, with tech giants investing billions in R&D to transform these models from novelty tools into essential national-level utilities [1] Industry Overview - The AI industry is experiencing rapid expansion and deep technological iteration, driven by language models as the core engine [2] - Key trends include multi-modal integration, embodiment intelligence, and the practical application of intelligent agents, with language models serving as the indispensable "central nervous system" [2] Language Model Sub-industry - The language model sub-industry is generally positive but faces three core pain points in consumer applications: insufficient practicality, fragmented scenarios, and cost-ecosystem imbalance [3] - The recent launch of Alibaba's Qianwen APP has seen significant success, with over 10 million downloads within a week of public testing and monthly active users exceeding 30 million within 23 days [4] Qianwen APP's Strategic Approach - Qianwen APP's rise is attributed to its strategic adjustment addressing industry pain points through a "technology + scenario + ecosystem" framework, validating Alibaba's "user-first, AI-driven" strategy [6] - The app leverages Alibaba's Qwen series models, which are competitive with leading closed-source models, enhancing its capabilities in logical reasoning and long-text processing [6][8] Future Development Trends - The language model industry is expected to enter a new development cycle characterized by technological integration, ecological symbiosis, and value orientation [9] - Future models will focus on deep multi-modal integration and vertical precision, with open-source models driving innovation and reducing costs for small and medium enterprises [9] Conclusion - The language model industry is at a critical juncture, transitioning from technological explosion to industrial prosperity, with Qianwen representing a significant breakthrough in both domestic and global markets [10]

Core Insights - Alibaba's CTO and head of Tongyi Lab, Zhou Jingren, has recently become a partner in Alibaba, marking a significant recognition within the company's highest decision-making body [1][12] - The restructuring of research organizations at Alibaba has led to the formation of Tongyi Lab, which is now responsible for AI model development, particularly the Qwen series [3][14] - The company is facing increased competition from other Chinese AI startups that are adopting open-source strategies, putting pressure on Tongyi Lab to maintain its leading position in AI model performance and application [20][21] Company Developments - Zhou Jingren has been with Alibaba for ten years, having held various positions, including Chief Scientist at Alibaba Cloud and Vice President at DAMO Academy [3][14] - The restructuring process has seen the integration of multiple AI research teams into Tongyi Lab, which is now under the leadership of Zhou Jingren [3][14] - The Qwen series of models has gained significant traction, with over 80,000 derivative models expected by October 2024, surpassing earlier models like Meta's Llama series [4][15] Talent Management - Over 80% of the team working on the Qwen model are graduates trained within Alibaba, indicating a strong internal talent development strategy [5][16] - Recent departures of key technical leaders from Tongyi Lab, including Huang Fei and others, highlight the challenges in retaining talent amid competitive pressures [17][18] - The company has promoted younger team members to leadership positions, such as Lin Junyang, who now leads the Qwen model team [5][16] Strategic Goals - Tongyi Lab has set three primary objectives for the year: maintaining model ranking, expanding commercial applications, and significantly increasing daily model usage by 2025 [19] - The launch of the new Qianwen app, aimed at competing with ChatGPT, reflects Alibaba's strategic focus on AI-driven applications [20][21] - The restructuring of business units to form the Qianwen C-end business group indicates a commitment to enhancing user engagement through AI technologies [20][21]

千问APP依托Qwen系列大模型打造。Qwen自2023年全面开源以来，性能超越Llama、Deepseek等国际开源模型，全球下载量突破6亿次。 Airbnb首席执行官布莱恩·切斯基（Brian Chesky）表示，公司业务大量依赖Qwen，认为其比OpenAI模型更快更高效。英伟达首席执行官黄仁 勋（Jensen Huang）也指出，Qwen在全球开源模型市场占据重要份额，并仍在扩张。 阿里巴巴今年早前宣布投入3800亿元用于AI基础设施建设，并计划追加更大投入。9月24日云栖大会上，阿里发布通义旗舰模型Qwen3-Max和 下一代基础模型架构Qwen3-Next，其中Qwen3-Max-Instruct预览版在LMArena文本排行榜上位列第三，超过GPT-5-Chat。同时，阿里宣布与英 伟达在PhysicalAI领域展开合作，为企业用户提供全链路平台服务。 阿里巴巴于1月17日宣布，个人AI助手千问APP正式开启公测，免费向用户开放。 千问App基于全球性能第一的开源模型Qwen3，定位为既能"对话"，又能"办事"的个人AI助手。阿里计划将地图、外卖、订票、办公、学习、 购物、健康等生活场景接入千问 ...

General-Reasoner团队 投稿 量子位 | 公众号 QbitAI 一项新的强化学习方法，直接让Qwen性能大增，GPT-4o被赶超！ 来自加拿大滑铁卢大学与TikTok新加坡，M-A-P的华人团队提出了一种全新训练框架： General- Reasoner 。 结果直接让Qwen系列大模型的跨领域推理准确率提升近10%，在多个基准测试中甚至超越GPT-4o。 上图显示出General-Reasoner在多项跨领域评测中显著提升基础模型推理能力。 当前，强化学习（RL）被视为提升模型推理能力的关键手段。其中，Zero-RL方法通过直接训练基础 模型，已在数学和编程等结构化任务上展现出强大效果。 问题是，这些方法往往局限于数据丰富、答案结构清晰的领域，在面对物理、金融或人文社科等更广 泛的领域时，模型难以有效泛化。 接下来看看研究团队是如何解决这些推理难题的？ 相较现有方法的关键革新 目前的Zero-RL框架如SimpleRL通常聚焦于单一领域数据，采用简单的规则式答案验证，存在以下不 足： 数据单一 多为数学竞赛或代码任务，泛化能力有限； 验证方式僵化 仅能识别明确结构化答案，无法灵活处理多样化的答 ...

Investment Rating - The investment rating for the communication industry is "Outperform the Market" [1]. Core Insights - The report highlights significant investments in AI infrastructure by leading companies, with Alibaba announcing a plan to invest 380 billion yuan (approximately 54.5 billion USD) over the next three years, which surpasses its total investment in the past decade [20][24]. - The AI computing power demand is rapidly increasing, with the domestic AI computing scale expected to reach 725.3 EFLOPS in 2024, a year-on-year growth of 74.1%, and projected to reach 2781.9 EFLOPS by 2028 [21][24]. - The report discusses the emergence of the Vision-Language-Action (VLA) model in the autonomous driving sector, which integrates visual input, language reasoning, and action output into a single framework, enhancing the performance of intelligent driving systems [26][30]. Summary by Sections 1. Market Review - From February 5 to February 28, 2025, the CSI 300 index rose by 1.91%, with the communication industry also increasing by 1.91%, while the computer industry surged by 16.31% [6][13]. - The communication sector experienced significant volatility, benefiting from operators' increased investment in computing power, leading to strong stock performance for companies like China Unicom and China Telecom [6][13]. 2. Communication Industry - Major companies are expanding their AI investments, with Tencent, Baidu, and Alibaba expected to increase their capital expenditures by 19.1% in 2025, reaching 15.42 billion USD [20][24]. - The report notes that the construction of intelligent computing centers is set to accelerate, with over 458 projects announced in the public bidding market for 2024 [24][25]. 3. Computer Industry - The VLA model represents a new direction in autonomous driving technology, improving the ability to process complex traffic scenarios and enhancing decision-making capabilities [26][30]. - The global autonomous driving market is projected to grow from 207.4 billion USD in 2024 to 273.8 billion USD in 2025, with the Chinese market expected to reach 399.3 billion yuan in 2024 [31][32].