当天早些时候，OpenAI发布了两个开放权重AI模型，分别是GPT-oss-120b和GPT-oss-20b。 微软首席执行官萨蒂亚·纳德拉当地时间8月5日发文称，很高兴将OpenAI的gpt-oss模型引入Azure"AI应 用和智能体工厂"AI Foundry，并通过Foundry Local将其带到Windows平台。纳德拉称，这是混合AI的实 际应用：用户可以灵活组合不同模型，优化性能与成本，并直接在数据所在的位置进行处理。 ...

来源：环球网 【环球网科技综合报道】7月23日消息，据外媒最新披露，苹果公司内部围绕人工智能（AI）技术开源 策略爆发激烈分歧。今年早些时候，其负责AI基础模型开发的团队曾提议将多个自研模型开源，以吸 引外部研究者协作优化并展示技术实力，但该计划最终被苹果软件工程高级副总裁克雷格·费德里吉 （Craig Federighi）以邮件形式直接否决。这一决策不仅暴露了苹果在AI战略上的深层矛盾，更成为其 核心团队人员流失的导火索之一。 然而，费德里吉在回复庞若明的邮件中明确反对这一计划。他认为开源将迫使苹果公开模型压缩算法细 节，使竞争对手得以复现其"以性能换体积"的端侧优化策略，进而削弱iPhone的AI差异化优势。 更关键的是，费德里吉担忧开源会暴露苹果模型的致命短板：为适配iPhone的A系列芯片，其模型需通 过量化剪枝等技术压缩至原有1/10大小，这导致在复杂任务（如多轮对话、长文本生成）中的准确率较 云端版本下降超20%。若外部研究者针对这一缺陷开发出更高效的压缩方案，苹果可能丧失端侧AI的领 先地位。 费德里吉的否决引发AI团队强烈不满。多位研究人员向媒体透露，苹果"设备优先"战略已严重束缚技术 发展。 ...

Market Overview - On July 16, the AI and robotics sectors experienced a pullback after an initial rise, with the Huaxia AI ETF (589010) closing up 0.59% after peaking over 2% during the day, indicating upward elasticity [1] - Notable performers included Cambricon Technologies, which rose by 4.9%, and Chipone Technology, which increased by 4.03%, while several other stocks saw gains exceeding 3% [1] - The Robotics ETF (562500) also closed up 0.58%, with Weichuang Electric surging by 13.97% and Xiangsha Precision rising by 6.18% [1] - The total trading volume for the day was 1.042 billion yuan, with stable liquidity, leading the same category of ETFs [1] - The Robotics ETF saw a net inflow of 57 million yuan, with four out of the last five trading days showing net inflows totaling 527 million yuan, ranking it first among comparable funds [1] Key News Highlights - As of July 16, 28 listed companies in the humanoid robot sector have disclosed their half-year performance forecasts for 2025, with 22 companies expecting positive results, driven by factors such as the penetration of new energy vehicles and the recovery of the consumer electronics market [2] - At the third China International Supply Chain Promotion Expo, NVIDIA's CEO Jensen Huang highlighted the miraculous nature of China's supply chain and predicted that factories will be driven by software and AI within the next decade, creating new opportunities for the supply chain ecosystem [2] - CoreWeave, a US AI cloud service provider, announced a $6 billion investment in an AI data center in Lancaster, Pennsylvania, with an initial capacity of 100 megawatts, potentially expanding to 300 megawatts to meet growing AI computing demands [2] Institutional Insights - Everbright Securities noted that hybrid AI can distribute AI computing workloads between edge AI and cloud AI, facilitating collaboration between the two [3] - The increasing complexity and usage of AI models will lead to high cloud inference costs, which may limit the scalability of generative AI [3] - Hybrid AI aims to shift some computational loads from the cloud to edge terminals, reducing infrastructure and transmission costs while saving energy [3] Popular ETFs - The Robotics ETF (562500) is the only fund in the market with a scale exceeding 10 billion yuan, offering the best liquidity and comprehensive coverage of the Chinese robotics industry [4] - The Huaxia AI ETF (589010) is described as the "brain" of robotics, with a 20% price fluctuation limit and small to mid-cap elasticity, aimed at capturing the "singularity moment" in the AI industry [4]

Group 1 - Garrett Group will establish its second innovation center in Wuhan, focusing on advanced technologies such as high-speed three-in-one electric drives, electric cooling compressors, and fuel cell electric air compressors for "zero emissions" [1] - This investment marks Garrett's third investment in Wuhan over the past 20 years, highlighting the city's rising position in the global new energy vehicle supply chain [1] - Garrett's production capacity has grown at an average annual rate of over 30% over the past decade, indicating the strategic importance of Wuhan as a key operational hub [2][3] Group 2 - Qualcomm's Chairman for China, Meng Pu, emphasized that technological innovation is the core driving force for urban development, aligning with Qualcomm's development philosophy [5] - Qualcomm is collaborating with Wuhan to accelerate the application of cutting-edge communication technologies like 5G-A in the industrial internet, showcasing the city's potential for technology validation [6] - The number of AI-enabled devices powered by Qualcomm has exceeded 2.5 billion, with significant growth expected in the AI smartphone and PC markets in China by 2025 [10]

尽管利润遭受重创，联想的营收表现却超出预期。营收达到169.8亿美元，同比增长23%，这得益于包括个人电脑、智能手机和平板电脑在内的智能设 备部门营收增长13%。然而，这种增长可能并不完全是积极信号。 受到关税逆风的影响，联想Q4净利润在经历了五个季度的增长后首次出现下滑，净利润暴跌64%，远低于市场预期。公司将下滑归因于非现金的认股 权证公允价值损失。 尽管利润遭受重创，但联想的营收却超出预期，包括个人电脑、智能手机和平板电脑在内的智能设备部门营收增长13%。但也有分析指出，这一定程度 上是由于供应商和终端用户都在为应对美国关税的影响而提前下单。 22日，联想集团公布2024全年及Q4业绩： | | FY 24/25 | FY 23/24 | Change | Q4 24/25 | Q4 23/24 | Change | | --- | --- | --- | --- | --- | --- | --- | | | US$ millions | US$ millions | | US$ millions | US$ millions | | | Group Revenue | 69,077 | 56,864 ...

Investment Rating - The report does not explicitly state an investment rating for the semiconductor industry Core Insights - AI computing chips are considered the "engine of the AI era," with significant growth in global computing demand driven by the ChatGPT trend and the acceleration of AI model iterations [6][12] - The global computing scale is expected to grow from 1397 EFLOPS in 2023 to 16 ZFLOPS by 2030, with a compound annual growth rate (CAGR) of 50% from 2023 to 2030 [25][28] - The AI computing chip market is dominated by GPUs, with a rapid growth in the custom ASIC chip market anticipated due to the increasing demand for AI computing [6][42] Summary by Sections 1. AI Computing Chips as the "Engine of the AI Era" - The ChatGPT trend has led to a surge in global tech companies accelerating their AI model development, with major players like Google, Meta, and Alibaba launching and iterating on AI models [6][12] - The demand for AI servers, which are essential for generative AI applications, is expected to drive significant growth in the AI server market, projected to reach $158.7 billion by 2025 [29] 2. Dominance of GPUs and Growth of Custom ASIC Market - AI computing chips are primarily used in cloud, edge, and terminal applications, with GPUs currently being the mainstream choice [6][42] - NVIDIA holds a dominant position in the global GPU market, with over 95% market share in AI server acceleration chips [42] - The custom ASIC chip market is expected to grow rapidly, with a projected CAGR of 45% from 2023 to 2028, driven by the need for diversified supply chains and enhanced bargaining power among cloud vendors [6][42] 3. DeepSeek's Role in Accelerating Domestic AI Computing Chip Development - DeepSeek's technological innovations are expected to enhance the efficiency of domestic AI computing chips, facilitating their rapid development and increasing market share [6][7] 4. Development of AI Computing Chip Industry in Henan Province - Henan Province is focusing on building a robust AI computing chip industry, establishing a core hub for computing resource scheduling and attracting upstream chip enterprises [9][10]

Core Viewpoint - The article discusses the significant impact of DeepSeek on the AI industry, particularly in the consumer electronics and automotive sectors, highlighting the shift towards edge AI and the emergence of new applications and models [1][5][25]. Group 1: DeepSeek's Influence - DeepSeek has been rapidly integrated by major consumer electronics brands such as Honor, OPPO, and Xiaomi, showcasing its widespread adoption [2][4]. - Over 20 automotive companies, including Geely and BYD, have announced their integration with DeepSeek, indicating a strong trend of AI and automotive convergence [3][4]. - The article emphasizes that AI is entering a new era of reasoning innovation, with DeepSeek acting as a catalyst for this transformation [5][7]. Group 2: AI Model Evolution - High-quality, small-scale AI models are becoming feasible, with DeepSeek-R1 providing innovative solutions to long-standing cost issues in edge AI [12][14]. - The article outlines four key trends in AI model development, including rapid evolution of AI models, shrinking model parameters, and the increasing availability of high-quality models for developers [15][17][20]. - Techniques such as quantization, pruning, and distillation are enabling the transfer of performance from large models to smaller ones, enhancing their applicability [18][20]. Group 3: Qualcomm's Role - Qualcomm is positioned as a leader in the edge AI space, having anticipated the shift of AI processing from cloud to edge, as outlined in their white paper on hybrid AI [28][29]. - The company has developed high-performance, energy-efficient chips that support advanced AI capabilities across various devices, including smartphones and automotive systems [32][33]. - Qualcomm's comprehensive ecosystem strategy facilitates developers in deploying AI models across multiple platforms efficiently [41][42]. Group 4: Future Implications - The transition of large models from cloud to edge presents significant opportunities for widespread application and user engagement [43]. - The article concludes that the ongoing innovations in edge AI are just beginning to emerge, with the potential for transformative impacts across industries [45][47].