金十数据6月24日讯，贝莱德认为，在中国的生物技术、自动化和自动驾驶领域可能会出现更多类似 DeepSeek的时刻，反映其对中国人工智能领域进一步发展的乐观态度。贝莱德大中华区投资策略师陆 文杰在周二的发布会上表示，很难给出确切的时间，但目前的环境适合这些科技公司实现非常强劲的创 新。 贝莱德：预计中国科技行业将出现更多DeepSeek时刻 ...

【文/观察者网 刘程辉】6月24日，夏季达沃斯论坛在中国天津开幕。中国国际经济交流中心资深专家 委员、国际货币基金组织原副总裁朱民表示，中国在人工智能（AI）发展方面的优势即将引发一波创 新浪潮，在未来18个月内将催生超过100个类似DeepSeek的突破。 据彭博社报道，朱民在论坛期间表示，这些新的软件产品"将从根本上改变整个中国经济的性质和技术 特性"。他认为，这一转变得益于中国庞大的工程师队伍、庞大的消费基础以及政府的支持性政策。 朱民 视觉中国 报道认为，朱民对中国AI未来的乐观看法表明，中美在尖端技术主导权上的竞争不会减缓。中美当前 正处于贸易冲突中，今年1月，DeepSeek的出世震惊全球科技行业，它以低成本实现了强大功能，自那 以来，美国将中国视为人工智能领域的关键竞争对手。 除了阻止中国获得先进的半导体制造设备外，美国政府还打着"国家安全"的幌子封锁中国企业获取英伟 达高端AI训练芯片的路径。中国则寄望本土科技巨头在先进芯片制造领域取得突破。 DeepSeek的出现曾引发中国科技股上涨，激发市场对中国科技竞争力的乐观情绪。在Deepseek推出后的 一个多月里，香港恒生科技指数一度大涨超过20 ...

Group 1 - The aerospace and defense sector experienced a significant rebound, with construction industrial stocks rising over 7% and companies like Inner Mongolia First Machinery Group increasing by over 6% [1] - The Tianhong Aerospace ETF (159241) opened low but quickly turned positive, driven by news of a military parade on September 3 showcasing domestically produced military equipment [2] - The Tianhong Aerospace ETF tracks the Guozheng Aerospace Index, focusing on low-altitude economy, large aircraft, commercial aerospace, and military informationization, with a 47.78% overlap with low-altitude economy and 52.18% with large aircraft themes [2] Group 2 - Analysts believe that Chinese military enterprises are demonstrating technological advantages in drones and fighter jets, with military trade expected to see significant growth, making the aerospace sector a core beneficiary [2] - The military sector is showing signs of performance recovery, with demand improving across various fields since the beginning of the year, and expectations for quarterly performance recovery as orders are fulfilled [2] - The Tianhong Aerospace ETF offers a concentrated investment in aerospace equipment, domestic large aircraft, and low-altitude economy stocks, with 99% of its index belonging to the defense and military sector, indicating higher investment value compared to other military-related indices [2]

Group 1 - The total market value of the 500 entrepreneurs or families on the list reached 13.7 trillion yuan, an increase of 11% year-on-year, with an average of 273.8 million yuan and a threshold of 66.2 million yuan for entry [3] - Zhang Yiming topped the list with a net worth of 481.57 billion yuan, marking a significant increase of over 141.37 billion yuan compared to last year, primarily due to his stake in ByteDance [3][4] - ByteDance's revenue reached 155 billion USD (approximately 1.13 trillion yuan) last year, growing by 29% year-on-year, surpassing Alibaba and Tencent [4] Group 2 - The AI sector has significantly influenced the wealth dynamics among tech entrepreneurs, with ByteDance's valuation being raised by various investment firms to between 400 billion and 450 billion USD [4][5] - DeepSeek, founded by Liang Wenfeng, has gained substantial attention in the AI field, with a user base exceeding 180 million, making it the leading AI application in China [7][8] - The TMT (Technology, Media, and Telecommunications) sector remains dominant, with 110 entrepreneurs listed, contributing to a total wealth of 3.34 trillion yuan, accounting for one-fourth of the total wealth of all listed individuals [14][15] Group 3 - The chip industry saw a significant presence on the list, with 36 entrepreneurs from various segments, including design and manufacturing, reflecting the growing importance of AI and semiconductor technology [15][16] - Companies like Xiaomi and Tencent have also benefited from AI advancements, with Xiaomi's stock price doubling in the past year due to its AI-driven products [12][13] - The emergence of new entrepreneurs in the AI and robotics sectors indicates a shift towards innovative technologies, with several startups making their mark on the wealth list [16]

Core Insights - The event "How to Efficiently Utilize DeepSeek" was held by the Shenzhen Federation of Trade Unions, focusing on the application of AI tools in the workplace [1] - Liu Dian, a researcher from Fudan University, provided practical insights on the effective use of AI tools across various work scenarios [1] Group 1: AI Tools in Work Applications - AI tools can quickly generate frameworks and drafts in copywriting, providing inspiration and reference for creators [1] - In project management, AI assists with task allocation, progress tracking, and risk warning, leading to more organized project advancement [1] - For data analysis, AI tools can process vast amounts of data rapidly, uncovering valuable information and trends to support decision-making [1] - In market research, AI efficiently collects and analyzes market information, helping businesses accurately grasp market dynamics [1] Group 2: Employee Perspectives - Employees expressed excitement about the newfound understanding of AI tools' potential in copywriting, emphasizing the practical techniques shared by Liu Dian [4] - The event was seen as a timely opportunity for employees to learn essential skills that enhance workplace competitiveness in the digital age [4] Group 3: Future Initiatives - The Shenzhen Federation of Trade Unions plans to collaborate with various resources to deepen the series of lectures, inviting industry experts to share valuable knowledge with employees [4]

Core Insights - The domestic large model industry is rapidly consolidating after more than two years of rapid growth, with the emergence of DeepSeek altering the competitive landscape [1] - MiniMax has launched a series of new products, including the world's first open-source hybrid architecture inference model, MiniMax-M1, which utilizes a unique reinforcement learning method [2][12] - MiniMax aims to enhance its foundational model capabilities in response to the competitive pressure from DeepSeek and other major players in the industry [1][12] Group 1: MiniMax's Innovations - MiniMax-M1 is touted as the best open-source model for complex productivity scenarios, surpassing domestic closed-source models and approaching the leading overseas models while offering the highest cost-performance ratio [2] - The model supports an input context length of "1 million," which is equivalent to the input length of Google's Gemini 2.5 Pro and eight times that of DeepSeek R1, with an output capacity of 80,000 tokens [2][3] - MiniMax's unique Lightning Attention mechanism significantly enhances computational efficiency, requiring only 30% of the computing power used by DeepSeek R1 for deep reasoning with 80,000 tokens [4][12] Group 2: Competitive Landscape - The large model industry is witnessing a shift, with many domestic players adjusting strategies and abandoning model pre-training, while major internet companies leverage their resources to advance [10][11] - MiniMax has been a pioneer in the field, investing in MoE architecture and launching the first MoE large model in China, which has become a consensus for technological iteration in the industry [11][12] - The competition is intensifying, with major players like OpenAI and Google continuously releasing new models, indicating a fast-paced environment where MiniMax is striving to maintain its innovative edge [10][11] Group 3: Future Directions - MiniMax is preparing for the next wave of AI development focused on agent technology, with the MiniMax Agent designed to handle complex tasks and multi-modal content generation [15][16] - The company emphasizes reliability in its agent design, aiming to create a tool that can perform tasks with a high degree of accuracy and efficiency [16][17] - The successful launch of MiniMax-M1 and the MiniMax Agent positions the company to capitalize on emerging opportunities in the AI landscape, particularly in foundational models and video generation [17]

Core Insights - ByteDance's Volcano Engine showcased its strength in AI technology and commitment to AI cloud services during the Force Original Power Conference [2] - The company announced several product updates, including the Doubao Model 1.6 and the Seedance 1.0 pro video generation model, along with upgrades to its AI cloud-native services [2] Product Updates - The Doubao 1.6 model supports multimodal understanding and graphical interface operations, enabling it to handle real-world tasks such as hotel bookings and receipt organization [2] - The Seedance 1.0 pro model allows for text and image input to generate high-quality 1080P videos with seamless multi-angle transitions and stable motion [2] - Doubao 1.6 introduces a pricing model based on "input length" intervals, offering a cost that is only one-third of the previous Doubao 1.5 deep thinking model or DeepSeek R1 [2] Market Positioning - Volcano Engine does not engage in "loss-leading" strategies to gain market share, maintaining a focus on ensuring gross margins [3] - The company emphasizes that while initial low pricing can attract users, the key factors for user attraction now lie in model performance, stability, and throughput [3]

6月18日上午，中国证监会主席吴清在2025陆家嘴论坛上宣布，将在科创板推出深化改革的"1+6"政策措 施，更加精准服务技术有较大突破、商业前景广阔、持续研发投入大的优质科技企业。 风险资本在我国过去数十年的科技产业发展中起到重要的作用。但在2023~2024年期间，由于美联储提 高利率以及全球经济衰退风险加剧，流入我国的美元风险资本减少。与此同时，国内IPO节奏阶段性收 紧，一些企业赴美上市定价过低，港股市场中小股票流动性不足，在一定程度上影响了部分创投机构通 过IPO退出与资金回流，国内风险投资活动有所减少。 但是，在我国当前经济发展阶段，以人工智能、生物科技、商业航天、低空经济等为代表的前沿技术与 新兴产业蓬勃发展，技术突破正向市场应用加快转化，这对加快构建与之相适配的金融服务体系提出了 新的更高要求。因此，及时重启第五套上市标准并扩大适用范围，积极吸引包括社保基金、保险资金、 产业资本等在内的各类社会资本参与私募股权投资，才能更好促进科技创新和产业创新融合发展，实现 科技、资本、产业良性循环。 我国诸多初创企业在互联网革命期间最终成长为巨头，比如高盛最近推出的中国十大民营上市公司中有 一半是互联网公司 ...

Core Insights - The emergence of DeepSeek in 2025 is revolutionizing the financial industry by enhancing market prediction models with its dynamic self-correction capabilities and advanced data mining abilities [1][10] - Traditional market prediction models often suffer from fixed weight configurations, leading to distorted judgment results, which DeepSeek aims to address [1][10] Group 1: Impact on Financial Industry - DeepSeek's dynamic self-correction ability optimizes weight based on historical data and current realities, improving prediction accuracy [1] - The model's data mining capabilities allow for the discovery of more relevant data, breaking linear thinking and avoiding "black box" issues [1] - DeepSeek enhances overall strategy intelligence through its powerful reasoning and complex decision-making capabilities [1] Group 2: Educational Initiatives - Guosen Securities has reported a 0.27% increase in annualized returns and a 1.08-fold increase in the Sharpe ratio after integrating DeepSeek into their simulation trading [3] - A masterclass titled "DeepSeek Restructures Strategy Investment Paradigm" has been launched to educate users on utilizing DeepSeek for investment [3][7] - The course, led by Wang Kai, covers various topics including asset allocation optimization, risk parity strategies, and understanding policy semantics [3][11] Group 3: Course Content and Structure - The masterclass is divided into eleven parts, focusing on practical techniques for asset allocation and investment strategies using DeepSeek [3][11] - Key topics include the application of AI in multi-asset frameworks, recreating classic investment portfolios, and understanding market timing and sector rotation [11][12] - The course aims to provide insights into the behavior logic behind key financial institution statements and the implications for investment strategies [11][12]

Core Viewpoint - MiniMax has launched its self-developed MiniMax M1 model, which competes directly with DeepSeek R1 and Google's Gemini 2.5 Pro in terms of key technical specifications, architecture design, context processing capabilities, and training costs [1][2]. Group 1: Model Specifications - MiniMax M1 supports a context length of 1 million tokens, which is 8 times larger than DeepSeek R1's 128,000 tokens and only slightly behind Google's Gemini 2.5 Pro [1]. - The total parameter count for MiniMax M1 is 456 billion, with 45.9 billion parameters activated per token, while DeepSeek R1 has a total of 671 billion parameters but activates only 37 billion per token [1]. Group 2: Cost Efficiency - MiniMax M1 consumes only 25% of the floating-point operations compared to DeepSeek R1 when generating 100,000 tokens, and requires less than half the computational power for inference tasks of 64,000 tokens [2]. - The training cost for MiniMax M1 was only $535,000, significantly lower than the initial expectations and much less than the $5-6 million GPU cost for training DeepSeek R1 [2]. Group 3: Pricing Strategy - MiniMax M1 has a tiered pricing model for its API services based on the number of input or output tokens, with the first tier charging 0.8 yuan per million input tokens and 8 yuan per million output tokens, which is lower than DeepSeek R1's pricing [3]. - The pricing for the first two tiers of MiniMax M1 is lower than that of DeepSeek R1, and the third tier for long text is currently not covered by DeepSeek [3]. Group 4: Technology Innovations - MiniMax M1's capabilities are supported by two core technologies: the linear attention mechanism (Lightning Attention) and the reinforcement learning algorithm CISPO, which enhances efficiency and stability in training [2].