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Core Insights - The MEET2026 Smart Future Conference will focus on cutting-edge technologies and industry developments that have garnered significant attention throughout the year [1] - The theme "Symbiosis Without Boundaries, Intelligence to Ignite the Future" emphasizes how AI and smart technologies are penetrating various industries, disciplines, and scenarios, becoming a core driving force for societal evolution [2] Group 1: Conference Highlights - The conference will cover hot topics in the tech circle this year, including reinforcement learning, multimodal AI, chip computing power, AI in various industries, and AI going global [3] - The event will showcase the latest collisions between academic frontiers and commercial applications, featuring leading technological achievements from infrastructure, models, and product industries [4] - The conference will also feature the authoritative release of the annual AI rankings and the annual AI trend report [5][93] Group 2: Notable Speakers - Zhang Yaqin, President of Tsinghua University's Intelligent Industry Research Institute and an academician of the Chinese Academy of Engineering, has a notable background in AI and digital video technologies [11][12] - Sun Maosong, Executive Vice President of Tsinghua University's AI Research Institute, has led multiple national projects and has extensive experience in AI research [15] - Wang Zhongyuan, Director of the Beijing Academy of Artificial Intelligence, has a strong background in AI core technology development and has published over 100 papers [19] Group 3: AI Trends and Rankings - The "Artificial Intelligence Annual Rankings" initiated by Quantum Bit has become one of the most influential rankings in the AI industry, evaluating companies, products, and individuals across three dimensions [94] - The "2025 Annual AI Trend Report" will analyze ten major AI trends based on technological maturity, implementation status, and potential value, highlighting representative institutions and best cases [95] Group 4: Event Details - The MEET2026 Smart Future Conference is scheduled for December 10, 2025, at the Beijing Jinmao Renaissance Hotel, with registration now open [96] - The conference aims to attract thousands of tech professionals and millions of online viewers, establishing itself as an annual barometer for the smart technology industry [98]

Core Insights - Ilya Sutskever, co-founder of OpenAI and a key figure in deep learning, has shifted focus from scaling models to research-driven approaches in AI development [1][2][3] - The industry is moving away from "scale-driven" methods back to "research-driven" strategies, emphasizing the importance of asking the right questions and developing new methodologies [2][3] - Sutskever argues that while AI companies may experience stagnation, they can still generate significant revenue despite reduced innovation [2][3] - The potential for narrow AI models to excel in specific domains suggests that breakthroughs may come from improved learning methods rather than merely increasing model size [3][4] - The emergence of powerful AI could lead to transformative societal changes, including increased productivity and shifts in political and governance structures [3][4] - Sutskever emphasizes the importance of aesthetic principles in research, advocating for simplicity and elegance in AI design [4] Industry Trends - The scaling laws that dominated AI development are nearing their limits, prompting a return to foundational research and exploration [2][28] - The current phase of AI development is characterized by a shift from pre-training to reinforcement learning, which is more resource-intensive [29][30] - The distinction between effective resource utilization and mere computational waste is becoming increasingly blurred in AI research [30][31] - The scale of computational resources available today is substantial, but the focus should be on how effectively these resources are utilized for meaningful research [42][44] Company Insights - Safe Superintelligence (SSI) has raised $3 billion, positioning itself to focus on foundational research without the pressures of market competition [45][46] - SSI's approach to AI development may differ from other companies that prioritize immediate market applications, suggesting a long-term vision for advanced AI [45][46] - The company believes that the true value lies not in the sheer amount of computational power but in the strategic application of that power to drive research [43][44]

MEET组委会 发自 凹非寺 量子位｜公众号 QbitAI 2025年，我们正迈入一个由人工智能重塑一切的新时代。 12月10日，量子位MEET2026智能未来大会 将带你聚焦这一年里最受关注的前沿技术与产业落地进展。 我们将以 「共生无界，智启未来」 为主题，关注以AI为代表的智能科技如何穿透产业、学科与场景的边界，成为驱动社会演进的核心动能。 强化学习、多模态、芯片算力、AI+行业、AI出海 等等今 年科技圈最热议的话题，你都能够在这场大会上看到。 这里既有 学术前沿 与 商业落地 的最新碰撞，也有来自 Infra 、 模型 、 产品产业 的领先技术成果。 大会上还将权威发布 人工智能年度榜单 与 年度AI趋势报告 ，敬请期待。 话不多说，现在大会已经开启了 观众报名通道 ，点击链接线下参会 今年MEET智能未来大会依然盛况不减，最新嘉宾阵容在此， 一起来看还有哪些大咖嘉宾出席—— 张亚勤 清华大学智能产业研究院院长 中国工程院院士 张亚勤院士于2014年9月至2019年10月担任百度公司总裁。出任百度总裁前，张亚勤院士曾在微软公司工作16年，历任全球资深副总裁兼微软亚太研发集团主 席、微软亚洲研究院院长 ...

Core Viewpoint - The article emphasizes the need for adaptability and continuous learning in the investment landscape, particularly in the context of emerging technologies like AI and biotechnology, highlighting the importance of maintaining a growth mindset amidst uncertainty [6][7][11]. Group 1: Investment Landscape - The current investment environment is characterized by collective anxiety within the Chinese venture capital community, questioning how to navigate a landscape devoid of simple innovation models [7]. - The transition from traditional investment strategies to hard technology sectors, such as biotechnology, poses significant challenges for seasoned investors who must adapt to new paradigms [9][10]. - The concept of "infinite games" is introduced, suggesting that successful companies focus on continuous evolution rather than short-term victories, which is crucial for long-term sustainability [24][25]. Group 2: Cultural Confidence - There is a deep-rooted cultural confidence in Chinese entrepreneurship, reflecting a historical resilience and a spirit of innovation that persists despite challenges [12][13]. - The belief in a new cycle of innovation, termed "Innovation 2.0," is gaining traction among investors and entrepreneurs, indicating a shift towards optimism in the market [12][16]. Group 3: AI and Future Trends - The emergence of AI is seen as a transformative force that will redefine productivity, enabling individuals and small teams to achieve significant market valuations [17]. - The article discusses the potential for AI to integrate into various industries, suggesting that its true impact will be realized when it becomes ubiquitous in decision-making processes [17][19]. Group 4: Narrative and Collaboration - The ability to create compelling narratives is highlighted as a unique human trait that drives collaboration and innovation, essential for achieving extraordinary outcomes [19][20]. - Successful companies are described as those that not only provide solutions but also construct an attractive vision for the future, fostering a shared sense of purpose among stakeholders [21][22]. Group 5: Learning and Growth - Continuous learning and iteration are emphasized as critical components of success in an ever-evolving business landscape, with failures viewed as valuable learning experiences [28][30]. - The article concludes with a call for entrepreneurs to embrace challenges and maintain a commitment to growth, underscoring that great companies thrive by remaining engaged in the market and evolving over time [30].

Core Insights - The article emphasizes the importance of maintaining an entrepreneurial mindset in AI research and development, focusing on rapid iteration and learning from failures [1][2][4] Group 1: Innovation and AI Development - Wu Yi's team developed the AReaL-lite framework, which significantly enhances AI training efficiency and reduces GPU waste [1] - The shift from traditional supervised learning to reinforcement learning is highlighted as crucial for developing intelligent AI capable of long-term task execution [6][33] - Wu Yi believes that the future of AI lies in creating intelligent agents that can understand vague human commands and perform complex tasks autonomously [12][13] Group 2: Entrepreneurial Spirit and Team Dynamics - Wu Yi stresses the need for innovation and resource creation within entrepreneurial teams, rejecting the notion of waiting for perfect conditions to act [25][26] - The article discusses the challenges faced by Wu Yi's early startup team, emphasizing the importance of having a committed and innovative mindset among team members [25][28] - Wu Yi's approach to team organization in the AI era involves creating a minimalistic structure that leverages AI to enhance productivity and efficiency [50][52] Group 3: Future of AI and Robotics - The concept of embodied intelligence is introduced, where intelligent agents can interact with the physical world and perform tasks based on minimal instructions [13][14] - Wu Yi envisions a future where multiple intelligent agents can collaborate to complete complex tasks, similar to a coordinated sports team [15][20] - The transition from digital to physical world applications of AI requires advancements in multi-modal data and training environments [21][22] Group 4: Learning and Adaptation - Wu Yi likens his career journey to a reinforcement learning process, emphasizing the value of learning through trial and error [29][30] - The article highlights the significance of prompt engineering in reinforcement learning, which is essential for effective AI training [35][36] - Wu Yi advocates for a layered approach in developing intelligent agents, combining low-level control with high-level reasoning capabilities [43][44]

MEET组委会 发自 凹非寺 量子位｜公众号 QbitAI 大会上还将权威发布 人工智能年度榜单 与 年度AI趋势报告 ，敬请期待。 话不多说，现在大会已经开启了 观众报名通道 ，点击链接线下参会 今年MEET智能未来大会依然盛况不减，最新嘉宾阵容在此， 一起来看还有哪些大咖嘉宾出席—— 首波嘉宾阵容 2025年，我们正迈入一个由人工智能重塑一切的新时代。 12月10日，量子位MEET2026智能未来大会 将带你聚焦这一年里最受关注的前沿技术与产业落地进展。 我们将以 「共生无界，智启未来」 为主题，关注以AI为代表的智能科技如何穿透产业、学科与场景的边界，成为驱动社会演进的核心动能。 强化学习、多模态、芯片算力、AI+行业、AI出海 等等今 年科技圈最热议的话题，你都能够在这场大会上看到。 这里既有 学术前沿 与 商业落地 的最新碰撞，也有来自 Infra 、 模型 、 产品产业 的领先技术成果。 张亚勤 清华大学智能产业研究院院长 中国工程院院士 张亚勤院士于2014年9月至2019年10月担任百度公司总裁。出任百度总裁前，张亚勤院士曾在微软公司工作16年，历任全球资深副总裁兼微软亚太研发集团主 席、微软 ...

点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 端到端作为这两年的量产关键词，是各家车企核心的招聘岗位。但市面上真正的量产人才少之又少，从模型优化、场景优化、数据优化，再到下游的规划兜底，端 到端其实是一个全栈的岗位，所以就出现一个神奇的现象：一方面求职者哀鸿遍野，另一方面企业招不到人。。。 从技术的成熟度和工业界的需求来看，端到端需要攻克的难题还有很多。导航信息的引入、强化学习调优、轨迹的建模及优化都有很多门道，目前也是量产第一 线。 为此我们花了三个月的时间设计了端到端量产进阶课程，从实战到落地层层展开。 该课程涉及的核心算法包括：一段式端到端、两段式端到端、导航信息的量产应用、开闭环强化学习、扩散模型+强化学习、自回归+强化学习、时空联合规划等 等，最后分享一些实际的量产经验。很多想进阶或者跳槽的同学苦于没有专家辅导，想转行但实际工作中无法接触到实际的量产优化，简历上往往不够亮眼，遇到 问题连个请教的人都没有。 这门课程是自动驾驶之心联合工业界算法专家开设的《面向量产的端到端实战小班课》！课程只有一个重点：聚焦量产。从一段式、两段式、强化学习、导航应 ...

理想的世界模型包含自车和其他车的轨迹，这是理想首次提出的。 做这件事目的是为了能够让理想VLA在仿真环境里进行强化学习，同一个场景可以不断测试更优的轨迹路线，这是真实数据完全无法实现的。 可视化见下面这个视频： 理想VLA训练过程： 预训练阶段是在云端训一个32B的VL基座模型，包含3D视觉、比开源模型清晰度提升3-5倍的高清2D视觉、驾驶相关的language的语料，关键的 VL联合语料（如导航信息与人类判断的同步记录），为适配车端算力并保证推理速度，云端大模型蒸馏成3.2B的MoE模型。 后训练阶段是将action引入模型，使其转化为VLA，参数量接近4B，采用短链条CoT，限制在2-3步以内，再用difusion，对未来4-8秒的轨迹和 环境进行预测。 强化学习阶段为两部分，一是人类反馈强化学习，二是不依赖人类反馈，利用世界模型模型生成数据进行纯强化学习训练，基于舒适性（G值）、 无碰撞、遵守交规三大指标自我进化，目标是驾驶水平超越人类。 2025年3月12日理想发布 Other Vehicle Trajectories Are Also Needed: A Driving World Model Un ...

11月23日，雷军发文总结小米端到端辅助驾驶HAD增强版的升级点。纵向加减速更舒适，旁车加塞时 可提前预判减速，及时跟车提速，行车更舒适安全。横向变道更丝滑，在变道并线、借道绕行时表现更 自然流畅。路况理解能力提升，在多车道复杂大路口能提前看懂导航信息，优化走对路、选对道的能 力。 此外，雷军还强调，辅助驾驶不是自动驾驶，驾驶时仍需时刻保持专注。此前在11月21日2025广州车展 开幕日，小米汽车端到端辅助驾驶"Xiaomi HAD增强版"正式发布，其在1000万Clips版本基础上引入"强 化学习"与"世界模型"，AEB防碰撞辅助升级，新增紧急转向辅助。 ...