作者丨律新社研究员 方佳柠 出品丨律新社研究中心 商业犯罪形态万千，唯变是存。 据公安部数据统计，2024年全国公安机关共破获各类刑事案件1.17万起，全国刑事案件同比下降25.7%，创本世纪以来最低。 然而据中国社会科学院法学研 究所《法治蓝皮书·中国法治发展报告（2025）》数据统计，2024年全国检察机关共起诉破坏社会主义市场经济秩序犯罪13.7万人，同比反升13%。在全国刑 事犯罪案件数量呈现持续下降趋势的背景下，涉企商业犯罪却呈现出上升趋势。理清商业犯罪的演变趋势，或将助力法律服务从业者明确专业化发展方向。 2025年5月，律新社研究中心正式启动《精品法律服务品牌指南（2025）：商业犯罪领域》调研。本文近距离对话5位深耕商业犯罪的刑辩律师，聚焦技术化 犯罪手段、结构性治理难题与系统性风险防控三大核心维度，进一步梳理新经济形态下商业犯罪的变化趋势： 犯罪领域多元化："动态演进"与"交叉跨境" 犯罪手段技术化："技术黑箱"与"证据蒸发" 上海市海华永泰律师事务所高级合伙人 谈及近年商业犯罪趋势，上海市海华永泰律师事务所高级合伙人李开胜认为，中央经济工作会议强调"民营企业家保护"，商业犯罪领域或将更加聚 ...

2025年6月24日至26日，世界经济论坛的第十六届新领军者年会（即"夏季达沃斯论坛"）在天津如期 举行。作为全球最受关注的新兴经济体商业盛会之一，本届论坛以"新时代企业家精神"为主题，汇 聚了1700多位来自政商界、国际组织、社会机构及学术界的思想者与变革者，共同探讨在全球格局 深度重构中寻找可持续增长的新路径。 麦肯锡中国区主席倪以理、麦肯锡中国医药医疗行业负责人王锦及麦肯锡全球金属及矿业行业联席 主席Karel Eloot（艾家瑞）等麦肯锡代表在论坛期间就全球经济解读、中国展望、产业重塑、气候投 资、新能源与材料及医疗卫生行业展望等话题，与参会的全球各界领袖展开了深入交流。 中国企业全球化3.0时代：从"世界工厂"到"全球企业公民"的蜕 变 在麦肯锡"2025中国企业全球新航程：战略转型与价值重构"的专题论坛上，麦肯锡代表对中国企业 的全球化进程进行了深入剖析。近年来，尽管中国企业在国内市场取得了巨大成功，但与全球许多 其他国家相比，其国际化进程仍较为滞后。事实上，目前全球前100大品牌中，仅有2个品牌起源于 中国，显示出中国企业在全球品牌认可度方面的差距。然而，随着全球化趋势的加速，中国企业对 于走向 ...

在刚刚过去的半年，生成式AI的发展节奏悄然切换了频道。我们从投资人对估值的口风变化里察觉了 这一点，从创业者对产品设计语言的更新里也发现了端倪。这并不是又一次"模型换代"的技术热潮，而 是一场更本质的跃迁——从拼工具到拼交付，从参数军备到闭环实战。 我们把这场结构性转向称为"Agentic AI的崛起"，也正是在这个时间节点上，非凡资本联合火星加速器 将于7月18日举办「2025年度生成式AI全球化高峰论坛暨Go Global AI 100年度评选」，同时非凡学堂 也特地为AI应用创始人准备了7月19日～7月20日的AI 应用创业增长实战课，邀请头部 AI 应用创始人与 资深出海顾问，从 PMF 打造、全球 GTM、流量闭环到资本路径四条战线拆解实战方法论。 一· 什么是真正的"Agentic AI时刻"？ Agent，从来不是一个新词。但"Agent-as-a-Service"的热度飙升，标志着AI正在进入一种全新的产业范 式： 这一变化背后的信号非常清晰： 从"工具"到"同事"，从"插件"到"分身"，Agentic时代不再停留在科研设想，而是正在成为商业现实。 二· 非凡视角：为什么我们要做这场双轨论坛？ ...

7 月 10 日，微软研究院 AI for Science 团队在《Science》杂志发表了题为「Scalable emulation of protein equilibrium ensembles with generative deep learning」的研究成果。 论文 ： https://www.science.org/doi/10.1126/science.adv9817 代码 ： github.com/microsoft/bioemu 该研究提出了一种名为 BioEmu 的生成式深度学习模型，能够以前所未有的效率和精度模拟蛋白质的 构象变化，为理解蛋白质功能机制和加速药物发现打开了新路径。 从结构预测到功能模拟：蛋白质研究的下一个前沿 近年来，AlphaFold 等模型在蛋白质结构预测方面取得了突破性进展，但这些方法通常只能预测单一静 态结构，难以捕捉蛋白质在功能过程中所经历的动态变化。蛋白质并非静止不动的分子，而是处于不断 变化的构象系综（conformational ensemble）中，其功能往往依赖于这些结构之间的转换。 BioEmu 正是为了解决这一挑战而生。它通过结合 Alpha ...

2025年，人工智能将如何进一步突破认知的极限？又将怎样更深刻地助力千行百业，并塑造我们共同的 科技未来？ 7月27日，由世界人工智能大会组委会指导， 腾讯华东总部、腾讯优图实验室主办，腾讯研究院、腾讯 科技、腾讯云智能、腾讯Robotics X实验室、腾讯SSV为村发展实验室、腾讯游戏VISVISE、QQ浏览 器、ima及搜狗输入法 等共同支持的 2025世界人工智能大会腾讯论坛 将在 上海 举办。 当科技的浪潮奔涌向前，人工智能正以超乎想象的速度重塑世界。从早期的理论设想，到如今成为变革 世界的核心力量，AI 不再是高悬于科幻云端的概念，已然化作 生活中无处不在的贴心助手 ，驱动着产 业升级、革新用户体验、重构人机协同，在诸多领域展现出令人瞩目的突破性潜能。 2024 年，我们共同经历了生成式AI的深化融合与爆发式应用。以多模态大模型和具身智能为代表的科 技新范式不断涌现，不仅拓宽了AI能力的边界，更深层次地加速了智能与人类社会的共生进程，为人工 智能的发展书写激动人心的新篇章。 今年， 我们将以"智能涌现"为主题， 聚焦全球AI技术与产业深度融合趋势，围绕"大模型垂直落地、场 景创新突破、生态共建协同" ...

Core Viewpoint - Meta's aggressive recruitment strategy in the AI sector has raised questions about its sustainability and the potential impact on company culture and performance [2][24]. Group 1: Recruitment and Team Structure - Meta has made headlines by offering exorbitant salaries, reportedly up to $200 million for key talent, to attract AI experts from competitors like OpenAI and Apple [3][4]. - The newly formed Meta Superintelligence Labs (MSL), led by Alexandr Wang, is a focal point of interest regarding its operational structure and research direction [5]. - There is a significant internal restructuring, with high-level executives being allowed to recruit their own teams, which may lead to internal competition and integration challenges [21][22]. Group 2: Internal Dynamics and Culture - Concerns have been raised about the impact of these changes on Meta's corporate culture, with reports of a "fear culture" emerging due to performance evaluations and ongoing layoffs [24]. - A lack of clear vision and strategic confusion has been noted, particularly within the Llama team, where many employees are unclear about the company's goals [24]. - The retention rate of top talent recruited from other companies is low, indicating potential issues with employee satisfaction and organizational stability [24]. Group 3: Research Focus and Distinctions - The Fundamental AI Research (FAIR) division operates independently from the GenAI and MSL teams, focusing on long-term foundational research rather than product development [8][16]. - The Llama team, initially part of FAIR, has been transitioned to the GenAI product group following the success of Llama1, highlighting the distinction between exploratory research and product-oriented development [15][16]. - The controversy surrounding the Llama 4 model, including allegations of "ranking cheating," has raised questions about Meta's technical reputation and credibility in the AI field [24].

Core Viewpoint - The AI boom continues to reshape the global economic landscape, with Nvidia's market capitalization reaching $4 trillion, marking a historic milestone in the tech industry since the AI wave began in late 2022 with the launch of ChatGPT [1][3]. Company Performance - Nvidia's stock price rose by 2.5% to $163.9 per share at the opening on July 9, 2023, closing at $162.9, with a total market cap of $3.97 trillion, nearing the $4 trillion mark [3]. - Nvidia's revenue for Q1 of the 2026 fiscal year reached $44.06 billion, a 69% year-over-year increase, with net profit of $18.78 billion, up 26% [4]. - Nvidia's stock has seen a cumulative increase of over 1000% since the beginning of 2023, with a 20% rise since April 2025 [3][4]. Market Position - Nvidia remains the leading supplier of AI chips for AI servers, with its data center business generating $39.1 billion in revenue, accounting for 89% of total revenue, and growing 73% year-over-year [6]. - The global data center market was valued at $250 billion in the previous year, growing at an annual rate of 20% to 25%, supporting Nvidia's valuation [5]. Future Outlook - Analysts predict Nvidia's market cap could reach $6 trillion, with a target price increase from $175 to $250 per share, driven by the anticipated "golden wave" of generative AI adoption [4]. - Nvidia is entering a "decade-long AI infrastructure buildout period," with significant growth opportunities in AI and robotics, representing a multi-trillion dollar market [6]. Challenges - Nvidia faces competition from self-developed chips by major tech companies like Amazon, Microsoft, and Meta Platforms, which could reduce reliance on Nvidia's products [8]. - The company is also challenged by the rise of low-cost AI models and restrictions on sales to China, which previously accounted for 25% of its global sales [7][8]. - Concerns about quantum computing advancements pose a potential risk, with some experts suggesting breakthroughs could occur within 5 to 7 years, potentially surpassing Nvidia's current technology [8].

Core Insights - Feishu's ambition is to redefine enterprise collaboration through AI, aiming for practical applications rather than mere concepts [2][8][21] - The monthly active users of Feishu's multi-dimensional table are approaching 10 million, marking it as a significant player in enterprise software [2][11][12] - Despite impressive commercialization results, profitability remains a challenge for Feishu, DingTalk, and WeChat Work [3][20] Company Developments - Feishu has launched a suite of AI products, including knowledge Q&A, AI meetings, Aily, and Feishu Miaodai, targeting real enterprise pain points [2][8] - The multi-dimensional table has seen significant updates, including a single table capacity increase to 10 million rows and improved loading speeds [9][10] - Feishu's enterprise-level agent development platform, Aily, allows users to create customized agents for various business needs [14] Market Position - Feishu is competing with DingTalk and WeChat Work, forming a triad in the collaborative software market [17] - In the new energy vehicle sector, 60% of the top 30 brands are using Feishu, showcasing its strong market presence [19] - In the consumer sector, Feishu has captured significant market share, with 5 out of 6 listed tea brands and 7 out of 10 listed domestic beauty brands using its platform [20] Industry Trends - The B-end market is accelerating the commercialization of generative AI, with enterprises expected to invest $4.6 billion in 2024, an increase of nearly 8 times [16] - The competitive landscape for enterprise software is shifting from single-function products to ecosystem building, driven by AI advancements [15]

Core Viewpoint - Manus, an AI Agent company, has faced significant challenges following a large-scale layoff and a shift of its headquarters to Singapore, indicating a strategic pivot in response to market pressures and operational efficiency [1][3][10]. Group 1: Company Developments - Manus confirmed a layoff of non-core technical staff, reducing its workforce from 120 to around 40 core technical personnel, as part of a strategy to enhance operational efficiency [1][3]. - The company has rapidly expanded its global presence, moving its headquarters to Singapore and establishing offices in California and Tokyo, reflecting a trend of "de-Chinaization" in its operations [3][4]. - Manus has completed two rounds of financing within a year, with a notable $75 million Series B funding led by Benchmark, raising its valuation to $500 million [4][6]. Group 2: Market Challenges - The AI Agent market is highly competitive, with the need for strong user retention and data accumulation to create a sustainable business model [2][10]. - Manus faces internal challenges related to the complexity of coordinating multiple AI models as tasks grow in scale and complexity [14]. - External competition is intensifying, particularly from newer entrants like GenSpark, which has demonstrated rapid growth and user acquisition, posing a threat to Manus's market position [15][16]. Group 3: Strategic Considerations - Manus has a significant user base of 200,000 potential paying customers, which could be monetized if user engagement and retention strategies are effectively implemented [17][20]. - The company must focus on creating a product that is not only functional but also engaging to retain users, as evidenced by successful strategies employed by other AI startups [18][19]. - There is a potential path for Manus to pivot towards niche markets or vertical applications, which could provide a more secure competitive position in the evolving AI landscape [20][22].

Core Viewpoint - The demand for AI is driving significant growth for DISCO, a leading manufacturer of wafer cutting machines in Japan, leading to upward revisions in their financial forecasts for the first quarter of 2025, with net profit expected to reach a historical high [1][2]. Group 1: Financial Forecast Revisions - DISCO revised its consolidated revenue forecast for Q1 2025 from 75 billion JPY (a 9% year-over-year decrease) to 89.914 billion JPY (a 9% year-over-year increase) [1]. - The consolidated operating profit was adjusted from 23.8 billion JPY (a 29% year-over-year decrease) to 34.48 billion JPY (a 3% year-over-year increase) [1]. - The consolidated net profit forecast was raised from 16.7 billion JPY (a 30% year-over-year decrease) to 23.767 billion JPY (a 0.2% year-over-year increase), marking a historical high for the same period [1]. Group 2: Market Dynamics and Demand Drivers - The upward revision in DISCO's financial outlook is attributed to strong demand for high-performance semiconductors driven by generative AI, which has boosted sales of manufacturing equipment [1]. - The depreciation of the Japanese yen against the dollar also contributed to the improved financial outlook, with the average exchange rate during the period being 144.5 JPY per USD, compared to the previously set benchmark of 135 JPY per USD [1]. - DISCO's individual shipment value for Q1 2025 reached 93 billion JPY, an 8.5% increase year-over-year, marking the fifth consecutive quarter of growth and surpassing the previous record of 90.8 billion JPY set in Q3 2024 [2]. Group 3: Industry Trends - The Japan Semiconductor Equipment Association (SEAJ) reported an upward revision in the sales forecast for semiconductor manufacturing equipment in Japan for the fiscal year 2025, increasing from 4.659 trillion JPY to 4.8634 trillion JPY, representing a 2% increase compared to the previous year [2]. - This growth is driven by increased investments in advanced semiconductor technologies, including the production of 2nm chips by TSMC and rising investments in DRAM and HBM by South Korean manufacturers [2].