每经记者｜岳楚鹏 每经编辑｜兰素英 ｜2025年6月16日 星期一｜ NO.1 谷歌计划与Scale AI切断联系 近日，据外媒援引消息人士报道，谷歌原本计划今年向Scale AI支付2亿美元，用于购买训练AI模型的 人工标记数据。但在Meta收购Scale AI 49%股份消息传出后，谷歌开始与Scale AI的几家竞争对手进行 了对话，试图转移大部分工作量。谷歌是Scale AI最大的客户，Scale AI在2024年的收入为8.7亿美元， 谷歌贡献约1.5亿美元。除此之外，消息人士称，微软和xAI也计划放弃Scale AI，因为他们担心，与 Scale AI开展业务可能会将他们的研究重点和路线图暴露给Meta。 点评：该事件说明，AI数据服务供应商竞争加剧，企业需提升数据安全与隐私保护能力，以赢得客户 信任。 NO.2 亚马逊计划五年内向澳大利亚数据中心基础设施投资约130亿美元 近日，亚马逊表示，将在2025年至2029年期间投资200亿澳元（约合129.7亿美元）用于扩建、运营和维 护其在澳大利亚的数据中心基础设施。这项投资也是亚马逊在澳大利亚最大的一笔投资，资金将用于扩 建新的服务器容量和对生成性 ...

Core Viewpoint - The intelligent license plate recognition system is becoming an essential part of modern traffic management, significantly improving efficiency and accuracy in various applications such as highway tolls, urban traffic management, and security monitoring [1][14]. Industry Overview - The license plate recognition system utilizes advanced technology to monitor and identify vehicle license information in real-time, playing a crucial role in modern intelligent traffic management [3]. - The market size of China's license plate recognition system industry reached 1.556 billion yuan in 2023, with an expected growth to 2.398 billion yuan by 2029, reflecting a compound annual growth rate (CAGR) of 7.47% [1][14]. Industry Chain - The upstream of the license plate recognition system industry includes components such as chips, sensors, displays, power supplies, and enclosures, with chips being the core component for image processing [8]. - The downstream applications encompass traffic management, vehicle monitoring, and parking management, highlighting the system's versatility in various sectors [8]. Competitive Landscape - The license plate recognition system industry is characterized by low concentration, with numerous small-scale enterprises. Major players include Hikvision, Dahua Technology, and Jieshun Technology, each leveraging their strengths in video monitoring and parking management [16][17]. Development Trends - Multi-modal recognition is identified as a future trend, integrating various sensors and data sources for enhanced vehicle identification and monitoring [21]. - Product differentiation is crucial for competitive advantage, necessitating improvements in service quality, functionality, and customization to meet diverse customer needs [22]. - Increased emphasis on data security and privacy protection is anticipated, driven by regulations such as the Personal Information Protection Law in China, requiring companies to adopt advanced data management practices [24].

导读 当前，商业银行积极顺应数字化转型趋势，主动吸收应用金融科技成果，借助科技手段改进原有业务模 式和风控体系，重塑金融服务模式，进一步提升了银行服务实体经济的能力，对引导企业优化投资行为 能够产生重要影响。然而，银行和企业均存在行业之间的"数字鸿沟"，一是中小企业无法获得足够融资 支持自身发展，二是中小银行缺乏数字化转型的资源，且企业数字安全和隐私保护问题凸显。最后提出 政策建议，推动数字化普惠性建设，完善立法保护数据安全。 01 商业银行传统手段无法完全化解银企信息不对称问题 在经济实际运行过程中，银行受限于自身信息的获取能力和监督能力，无法完全化解信息不对称问题， 会产生信贷配给、信贷歧视等一系列问题。银行如何更好地为实体企业服务一直是学术界研究的热点。 大量研究以银行的业务模式和结构改革为切入点来探索缓解银企信息不对称问题。 早期研究认为，银行与借款人之间的信息不对称问题可以通过提供抵押物来解决。研究发现，抵押品对 逆向选择问题有一定的缓解作用，当银行向借款人提供有抵押和低利率、无抵押和高利率这两种贷款合 同时，低风险借款人倾向于选择前者，高风险借款人倾向于选择后者。而且当企业违约时，银行还可以 将抵 ...