Group 1: Veo 3 Upgrade - The Google Veo 3 upgrade allows audio and video generation from a single image, maintaining high consistency across multiple angles [1] - The new feature is implemented through the Flow platform's "Frames to Video" option, enhancing camera movement capabilities, although the Gemini Veo3 entry is currently unavailable [1] - User tests indicate natural expressions and effective performances, marking a significant breakthrough in AI storytelling applicable in advertising and animation [1] Group 2: Hugging Face 3B Model - Hugging Face has released the open-source 3B parameter model SmolLM3, outperforming Llama-3.2-3B and Qwen2.5-3B, supporting a 128K context window and six languages [2] - The model features a dual-mode system allowing users to switch between deep thinking and non-thinking modes [2] - It employs a three-stage mixed training strategy, trained on 11.2 trillion tokens, with all technical details, including architecture and data mixing methods, made available [2] Group 3: Kunlun Wanwei Skywork-R1V 3.0 - Kunlun Wanwei has open-sourced the Skywork-R1V 3.0 multimodal model, achieving a score of 142 in high school mathematics and 76 in MMMU evaluation, surpassing some closed-source models [3] - The model utilizes a reinforcement learning strategy (GRPO) and key entropy-driven mechanisms, achieving high performance with only 12,000 supervised samples and 13,000 reinforcement learning samples [3] - It excels in physical reasoning, logical reasoning, and mathematical problem-solving, setting a new performance benchmark for open-source models and demonstrating cross-disciplinary generalization capabilities [3] Group 4: Vidu Q1 Video Creation - Vidu Q1's multi-reference video feature allows users to upload up to seven reference images, enabling strong character consistency and zero storyboard video generation [4] - Users can combine multiple subjects with simple prompts, with clarity upgraded to 1080P, and support for character material storage for repeated use [5] - Test results show it is suitable for creating multi-character animation trailers, supporting frame extraction and quality enhancement, reducing video production costs to less than 0.9 yuan per video [5] Group 5: VIVO BlueLM-2.5-3B Model - VIVO has launched the BlueLM-2.5-3B edge multimodal model, which excels in over 20 evaluations and supports GUI interface understanding [6] - The model allows flexible switching between long and short thinking modes, introducing a thinking budget control mechanism to optimize reasoning depth and computational cost [6] - It employs a sophisticated structure (ViT+Adapter+LLM) and a four-stage pre-training strategy, enhancing efficiency and mitigating the text capability forgetting issue in multimodal models [6] Group 6: DeepSeek-R1 System - The X-Masters system, developed by Shanghai Jiao Tong University and DeepMind Technology, has achieved a score of 32.1 in the "Human Last Exam" (HLE), surpassing OpenAI and Google [7] - The system is built on the DeepSeek-R1 model, enabling smooth transitions between internal reasoning and external tool usage, using code as an interactive language [7] - X-Masters employs a decentralized-stacked multi-agent workflow, enhancing reasoning breadth and depth through collaboration among solvers, critics, rewriters, and selectors, with the solution fully open-sourced [7] Group 7: Zhihui Jun's Acquisition - Zhihui Jun's Zhiyuan Robot has acquired control of the listed company Shuangwei New Materials for 2.1 billion yuan, aiming for a 63.62%-66.99% stake [8] - Following the acquisition, Shuangwei New Materials' stock resumed trading with a limit-up, reaching a market value of 3.77 billion yuan, with the actual controller changing to Zhiyuan CEO Deng Taihua and core team members including "Zhihui Jun" Peng Zhihui [8] - This acquisition, conducted through "agreement transfer + active invitation," is seen as a landmark case for new productivity enterprises in A-shares following the implementation of national policies [8] Group 8: AI Model Usage Trends - In the first half of 2025, the Gemini series models captured nearly half of the large model API market, with Google leading at 43.1%, followed by DeepSeek and Anthropic at 19.6% and 18.4% respectively [9] - DeepSeek V3 has maintained a high user retention rate since its launch, ranking among the top five in usage, while OpenAI's model usage has fluctuated significantly [9] - The competitive landscape shows differentiation: Claude-Sonnet-4 leads in programming (44.5%), Gemini-2.0-Flash excels in translation, GPT-4o leads in marketing (32.5%), and role-playing remains highly fragmented [9] Group 9: AI User Trends - A report by Menlo Ventures indicates that there are 1.8 billion AI users globally, with a low paid user rate of only 3%, and a high student usage rate of 85%, while parents are becoming heavy users [10] - AI is primarily used for email writing (19%), researching topics of interest (18%), and managing to-do lists (18%), with no single task dependency exceeding one-fifth [10] - The next 18-24 months are expected to see six major trends in AI: rise of vertical tools, complete process automation, multi-person collaboration, explosion of voice AI, physical AI in households, and diversification of business models [10]

Core Insights - The AI industry is experiencing unprecedented growth and rapid technological advancements, with significant shifts in market dynamics and application strategies [1][2]. Model Economics - The cost of training cutting-edge foundation models is skyrocketing, with the estimated training cost for Llama 4 in 2025 expected to exceed $300 million, a dramatic increase from $4.5 million for GPT-3 in 2020 [3][6]. - The lifespan of these models is decreasing rapidly, with high training costs facing the reality of quick obsolescence, as seen with GPT-4's performance being matched or surpassed by lower-cost open-source models within a year [6][8]. Application Trends - Successful AI applications are increasingly relying on multi-model collaboration rather than single-model dependency, enhancing performance through systematic approaches [4]. - The shift towards "data as a service" is anticipated as data collection costs decrease significantly, creating new opportunities for AI infrastructure [4]. Technological Breakthroughs - Two key breakthroughs are driving the current AI wave: self-supervised learning, which allows models to learn from vast amounts of unlabelled data, and attention architecture, which enhances computational efficiency and contextual understanding [24][25]. - The emergence of "emergent behavior" in models indicates that once a certain scale is reached, performance can dramatically improve, leading to a race for larger model sizes [26][27]. Market Dynamics - Venture capital investment in foundation model companies has surged, with approximately 10.5% of global venture capital directed towards this sector in 2024, amounting to $33 billion [112]. - The concentration of capital in AI is reshaping the competitive landscape, with over 50% of venture capital deployed to AI-related companies in 2025, marking a significant shift in investment focus [112].

2、模型阵营分明！aws不主推 openai gpt系列模型，不上Gemini系列模型室。google云上claude ，不上 gpt系列，微软云补主推 claude。 3、trainium2 目前能搭6万卡集群，后续推理需求，tainium2 推广很猛！inferentia好久没跌代了，后续估 计不会再推了。年底出trainium3。 最近抽空参加了一下现场。 说一下结论： 1、Claude 3.7 和4出来后，目前已经和openai O1 系列模型分庭抗礼了。 从单日token看，基本快持平 了。 4、亚马逊规模最大，基于CPU的计算 基础云，它受认可度最高。并在不断降本。 5、对应用开发递推有三层：基于gpu的 sagemaker！基础模型api调用一体化平台bedrock！针对 高阶用 户的Q！ ...

过去半年，科技股行情持续升温，中国科技产业的崛起已成为全球资本市场的焦点。DeepSeek 的突破性进展不仅提振了市场信心，更向世界展示了中国在AI领域的领先潜力。然而，对中国经 济的质疑声仍未消散——这种分歧恰恰印证了投资领域的经典规律：市场底部往往与怀疑相伴， 而市场顶部则由共识驱动。政策传导通常存在时滞，实施过程可能面临阶段性挑战，但政策制定 者始终秉持动态响应原则应对变化。因此，最重要的关注点应是政策制定者的战略决心和方向锚 定。 董晗：中国高科技产业的关键突破，有望惠及整个中国资产 导语："投资大家谈"是点拾投资的公益内容栏目，希望通过每周日不定期的推送，让更多人看到基金经 理对投资和市场的思考。"投资大家谈"栏目内容以公益类的分享为主，不带有基金产品的代码和信息， 也必须来自基金经理的内容创作。 下面，我们分享来自景顺长城基金科技军团的6月思考。一直以来，景顺长城科技军团通过持续 深耕产业链，不断取得前沿、深度的投资洞见。他们也是买方基金公司中，少数提供持续观点分 享的投研团队，相信这一期的6月观点，也能帮助大家理解景顺长城科技军团的投研思考。 最后，也欢迎大家持续给我们投稿！可以发送邮件到：az ...

每经编辑｜赵云 5月26日，通信ETF（515880）收涨0.83%，半导体设备ETF（159516）收涨1.1%。 近日，AI大厂继续发布新模型，加速AI应用落地。5月21日，谷歌I/O开发者大会发布多款AI模型、AI 应用、AI Agent等产品。语言模型方面，Gemini系列模型全面升级。AI应用方面，公司表示Gemini模型 将逐步登陆手机、手表、汽车、电视等多平台，持续赋能终端产品。5月22日，OpenAI宣布用于Agent 开发的Responses API支持MCP，随着A2A协议和MCP生态不断完善，AI Agent开发效率和交互能力有望 迎来快速提升，加速AI应用落地，催生AIDC产业链需求进一步释放。 一季度海外巨头资本开支保持良好趋势，根据民生证券，Meta25Q1 CAPEX为137亿美元（同比 +104%，环比-8%）。公司大幅上调25年全年CAPEX指引至640~720亿美元（同比+63~84%）。亚马逊 25Q1 CAPEX为263亿美元（同比+74%，环比-7%）。谷歌25Q1 CAPEX为172亿美元（同比+43%，环比 +20%）。 同时，国内大厂资本开支迎来明显加速。阿里2 ...

上周，被谷歌 I/O 发布会"刷屏"了。 各种重磅模型、产品更新、技术演示，还有关于"谷歌又领先了"的讨论，在朋友圈铺天盖地。这些内 容，大家已经看得不少，这里也不再多讲。 但如果只盯着功能细节和技术亮点，就很容易陷入局部，忽略背后更深层的动因。 这场发布会看似遥远，并不只是谷歌一家的技术秀场。它更像是一个信号，一面镜子，映照出全球 AI 竞争中一个重要玩家的战略方向。 所以，一周过去了，得用更理性的思维来追问一下：回顾谷歌I/O发布会，以及它的产品和技术路线， 到底给中国企业带来了哪些启示和挑战？ 还是先说一个词：AI原生（AI-Native）。什么意思呢？ 不是说你在产品上加个"AI按钮"就完事了，要从底层架构开始，用AI的思维重新设计整个产品逻辑。 就像盖房子。过去做法先把结构搭起来，再往里面装智能设备；而现在，谷歌已经从地基开始，把 AI 当作整栋建筑的核心支撑。它的产品，必须"长"在 AI 之上。 I/O 发布会核心战略也很清楚：让 AI 像空气一样无处不在；无论是搜索、语音助手、办公套件、安卓 系统，还是手机等终端设备，处处必须有 AI 的影子。 这释放了一个信号： AI 不再是某个模型或应用的事 ...