Core Insights - The article discusses the investment strategies of fund manager Jiang Na, who emphasizes the importance of financial data and performance metrics in selecting growth stocks, particularly in the AI sector [1][2][3] - Jiang Na believes that the market is transitioning from a value-driven approach to a growth-oriented one, with significant opportunities in AI, gaming, and consumer sectors [1][4] Investment Strategy - Jiang Na focuses on companies in the "performance explosion" phase, prioritizing strong financial reports, cash flow, and balance sheet quality [1][2] - The investment framework also includes precise judgment of industry cycle positions, favoring sectors transitioning from low penetration to growth phases [2][3] Key Selection Criteria - Jiang Na employs the "Three New" principle for stock selection: new cycle, new customers, and new products [3] - The AI-driven demand for computing power is identified as a clear new cycle, with extensive tracking of the sector over the past three years [3] Market Outlook - The AI sector is viewed as a long-term trend with ongoing opportunities, while the internet and gaming sectors are expected to enter new cycles due to favorable policies [4][5] - Companies expanding internationally are also highlighted, particularly those in culturally strong sectors with low trade friction risks [4][5] Additional Focus Areas - Jiang Na is monitoring sectors like chemicals, new energy, and consumer goods for potential bottom reversals, emphasizing the importance of independent judgment in a rapidly changing market [5]

9月6日，2025全球工业互联网大会在沈阳开幕。当前，人工智能发展从技术能力驱动转向需求应用驱 动。站在人工智能浪潮的关键转折点，2025全球工业互联网大会以"人工智能+"为核心命题，充分展示 我国工业互联网领域取得的重要发展成果。 工业互联网是新一代信息通信技术与工业经济深度融合的全新工业生态、关键基础设施和新型应用模 式，是推动产业数字化转型的关键支撑，也是促进实体经济和数字经济深度融合、科技创新和产业创新 深度融合的关键路径。近年来，我国工业互联网发展成效显著，政策体系持续健全，技术创新不断突 破，生态建设日益壮大，赋能效应持续显现。 当下，人工智能技术正助推工业互联网迈向智能新阶段。工业互联网与人工智能的双向赋能效应不断增 强。 一方面，工业互联网为人工智能提供了数据沉淀基础、场景数字化条件和算力等数字底座。特别是我国 庞大的工业场景和数据资源潜能，有力推动了人工智能技术不断取得新突破。另一方面，人工智能正深 刻影响着工业互联网发展，重塑工业互联网，推动企业实现数字化转型、智能化升级，助力企业和相应 产业打造更强大的生态系统。 面对人工智能浪潮，国家也出台政策给予大力支持。国务院日前印发的《关于深入实 ...

Core Viewpoint - The investment landscape in the AI sector is shifting, with a potential transition from value to growth style, highlighting significant long-term opportunities in AI and related industries [1][5]. Investment Style - Two distinct investment styles have emerged among fund managers entering the AI space: one focusing on long-term sector potential and the other emphasizing strict performance verification [1]. - The investment approach of the fund manager from Dongfanghong Asset Management, Jiang Na, is characterized by a high demand for financial data and a focus on companies in their "performance explosion" phase [2]. Financial Analysis - Jiang Na prioritizes companies with strong financial metrics, including cash flow and balance sheet quality, and regularly updates financial models for the companies in her portfolio [2]. - The investment strategy includes a keen assessment of industry cycles, particularly favoring sectors transitioning from low penetration to growth phases, which present richer investment opportunities [2]. Resource Integration - Jiang Na leverages her extensive experience and team collaboration to identify and capitalize on investment opportunities, emphasizing the importance of collective intelligence over individual efforts [3]. Stock Selection Criteria - The selection of stocks is guided by the "three new" principles: new cycle, new customers, and new products, with a focus on the AI-driven demand explosion in the PCB sector [4]. - The emphasis on customer perspective and management foresight in identifying strong companies is crucial for building competitive advantages [4]. Market Outlook - The outlook for the market suggests a favorable environment for equity assets, with a potential shift towards growth styles aligning with Jiang Na's investment focus [5][6]. - Key sectors to watch include AI, internet, gaming, and companies expanding internationally, particularly those with cultural attributes and lower trade friction risks [6]. - The chemical, new energy, and consumer sectors are also highlighted for potential bottom reversals, with a focus on maintaining independent judgment amid market consensus [6].

01 数字浪潮，职场环境正在重塑 微软公司通过分析用户与AI工具的互动发现，知识密集型和沟通密集型岗位的工作内容与AI能力高度 重合，风险最高。 人工智能可能影响全球40% 的就业岗位，在发达经济体，这一比例甚至高达60%。这不是未来预言， 而是正在发生的现实。 国际货币基金组织（IMF）的评估显示，AI驱动的数字化转型正在重塑职场生态。面对这场变革，许多 非企业部门的员工——无论是事业单位、行政机关还是非营利组织的工作者——都感到前所未有的焦虑 和迷茫。 但真正的危险并非被AI取代，而是在这场变革中停滞不前。本文将为面临数字化转型的员工提供实用 建议，帮助你不只是生存，而是在变革中茁壮成长。 相反，需要体力劳动、机器操作或直接人际互动的岗位，与AI能力的重叠度最小。AI的影响是分层 的，它先自动化重复性任务，将人类价值推向需要创造力、战略性思维和情感联结的高阶功能。 在2025年，人工智能人才缺口预计达400万，掌握AI技能已成为保持职场竞争力的关键。 数字化转型不是一场是否到来的风暴，而是已经登陆的飓风。聪明的员工不会等待被冲击，而是提前准 备，顺势而为。 02 转变心态，从焦虑到拥抱 数字化转型中，员工 ...

从 AI 上下半场切换看后续产业投资机会 20250907 摘要 AI 技术正从深度学习转向大语言模型，核心在于智能涌现，包括理解、 生成、记忆和逻辑四大能力，推动从感知智能向认知智能转化，重塑用 户体验和生产效率。 AI 产业发展依赖算力、算法和数据三大要素，形成飞轮效应。上半场探 索模型智力极限，算力为王；下半场完善系统能力，应用为王，核心在 于 AI 系统构建与产品能力。 Transformer 框架的大规模应用引发质变，理解和逻辑推理能力涌现， 推动通往 AGI 的路径，并在文本、图像视频等领域产生新范式，模型治 理与工具水平提高。 短期内，大模型升级逐渐触及天花板，应用效果成为重点。发展路径包 括效率提升（数学及编程）、推理提升以及全模态模型，这些是后续重 点发展方向。 海外科技巨头如 Meta 持续加大资本开支，预计 2025 年同比 2024 年 有显著增长，积极投入以支持算力需求，推动技术与场景融合，加速 AI 发展。 Q&A AI 产业经历了哪些主要发展阶段？ AI 产业经历了三次主要浪潮。第一次浪潮发生在 20 世纪 50 年代到 70 年代， 是人工智能的起步阶段，首次提出 AI 概念， ...

1. AI Key作为一款定价89美元的iPhone外接AI助手硬件，上线7小时内几乎售罄，可通过USB接口连接后实现语音控 制手机应用功能； 2. 当今iPhone已自带强大芯片能访问各类AI模型，AI Key等外接硬件本质是给已足够智能的设备增加冗余功能； 生成式AI 一、 Anthropic禁止中国控股公司使用Claude，公司在哪都不行 1. Anthropic发布最新政策限制，停止向多数股权由中国资本持有的集团或子公司提供Claude服务，无论其运营地点 在哪里； 2. 该限制适用于直接或间接被中国公司持股超过50%的实体，官方声明这是出于法律、监管和安全风险考虑； 3. 政策同样适用于俄罗斯、伊朗、朝鲜等"对手国家"实体，高管称此举预计会对Anthropic全球收入造成"数亿美 元"范围的影响。 https://mp.weixin.qq.com/s/TsErlyz7xnm_iHhP1CGc8Q 二、 一个能让 iPhone 用上 AI 的配件，千万人围观但或大可不必 3. AI硬件创业潮(如Humane Ai Pin和Rabbit R1)多数是短期热度，未来真正有价值的是将AI作为系统"属性"而非 ...

Core Viewpoint - Tesla has officially launched its "TeslaAI" Weibo account, showcasing its humanoid robot, Optimus, indicating a strategic shift towards artificial intelligence and robotics [2][6][7] Group 1: Humanoid Robot Development - Tesla released images of its humanoid robot, which features a bionic design with realistic hand details, marking significant improvements over previous versions [6] - Elon Musk has stated that the third version of the Optimus humanoid robot prototype is expected to be unveiled by the end of this year, with mass production starting in 2026, aiming for an annual output of 1 million units within five years [6][7] Group 2: Strategic Shift and Future Plans - The recent "Master Plan Part IV" indicates a major strategic pivot for Tesla, moving from a focus on electric vehicles and energy products to prioritizing artificial intelligence and robotics [7] - Musk emphasized that autonomous driving and the Optimus robot will be the company's most critical initiatives, projecting that approximately 80% of Tesla's future value will derive from the Optimus robot [7]

特斯拉最新。 9月7日，特斯拉开通"TeslaAI"的官方微博，认证为"特斯拉官方账号"，并发布首条微博展示其人形机器人。 特斯拉发布了两张人形机器人的照片，并配文："我一直在努力改善自己的身材"。 参考图片，该机器人身上印有特斯拉Logo，整体采用浅金色/黑色配色，应当是先前曝光的"Optimus 3 人形机器人"。 此前消息显示，这台机器人还拥有仿生设计的手部，带有真人手部的褶皱、指甲轮廓、关节痕迹等，细节较为逼真，相比前两代Optimus的手部有较为明显的进 步。 根据宏图计划4.0的介绍，特斯拉在过去的近二十年里，通过开发电动汽车、能源产品和仿生机器人，进行不懈的技术积累。而随着人工智能技术的影响力与日 俱增，特斯拉故事的"下一章"将是"打造将人工智能融入现实世界的产品与服务"，这将会创造一个"可持续的富足的未来"。对于如何实现宏图计划4.0，马斯克在 社交平台上表示，自动驾驶和机器人Optimus将是公司最重要的事项，且未来特斯拉约80%的价值将来自Optimus机器人。 责编：叶舒筠 校对： 李凌锋 版权声明 证券时报各平台所有原创内容，未经书面授权，任何单位及个人不得转载。我社保留追 究相关 行 ...

文 ： 华创证券研究所副所长 、首席宏观分析师 张瑜（执业证号：S0360518090001） 联系人： 李星宇（18810112501） 2、法国与意大利10年期国债利差收窄至0附近 。法国与意大利10年期国债利差近期收窄至接近零，反映市场对两国财政和政治风险评估的趋同。法国10年期国债 利差上行主要因总统马克龙提前选举失败导致"悬浮议会"，阻碍新总理贝鲁推动438亿欧元财政紧缩预算案，而意大利则因梅洛尼的稳健政策，国债收益率相对稳 定，法意利差收窄表明投资者对两国风险预期的重新平衡。 3、美股周期性行业/防御性行业与ISM制造业PMI出现分化 。2023年6月以来，美股周期性行业/防御性行业与ISM制造业PMI出现分化。美股周期股相对于防御股 的表现持续走强，而衡量制造业景气度的ISM制造业PMI却持续疲软，或说明当前的资本支出繁荣可能高度集中于少数与人工智能相关行业，未能广泛传导至整体 经济，因此并未带来全面的制造业复兴。 4、全球基金经理环比增加在新兴市场以及股票上的配置 。根据2025年8月的美国银行全球基金经理调查，全球基金经理环比增加了在新兴市场、股票、公用事 业、日本以及能源上的仓位，同时降低 ...

Core Viewpoint - The article discusses the launch of China's first AI computing open architecture by Zhongke Shuguang, aimed at addressing the increasing demand for AI computing power and fostering collaboration among industry players to overcome existing challenges in the AI computing sector [1][6]. Group 1: AI Computing Open Architecture - Zhongke Shuguang, in collaboration with over 20 industry chain enterprises, has introduced an AI computing open architecture to promote open collaboration and innovation in the AI computing field [1][6]. - The AI computing open architecture focuses on large-scale intelligent computing scenarios, utilizing GPU-centric designs to enhance system efficiency and collaboration across the AI industry chain [1][3]. Group 2: AI Super Cluster System - The newly launched Shuguang AI Super Cluster System supports multiple brands of accelerator cards and is designed to provide a robust computing foundation for trillion-parameter model training and various AI applications [3][5]. - The system features capabilities such as supporting 96 accelerator cards per cabinet, achieving over 100 petaflops of AI computing power, and allowing for large-scale expansion up to one million cards [5]. Group 3: Technical Innovations and Collaborations - The Shuguang AI Super Cluster has achieved significant performance improvements, including a 2.3 times increase in model training efficiency and a 55% increase in GPU computing efficiency compared to industry standards [5]. - Zhongke Shuguang has announced the opening of key technical capabilities, including AI storage optimization and liquid cooling infrastructure design, to reduce development barriers for small and medium enterprises [5][6].