Core Insights - Protecting AI core technology assets has become a strategic priority for the United States amid the rapid global development of AI technology [1] - The protection of trade secrets is crucial in the context of increasing global AI competition, as AI is not just a new technology but a key infrastructure [2] - The U.S. faces significant challenges in its intellectual property system, particularly in patent protection for AI technologies, which has led to a reliance on trade secrets [4] Group 1: Trade Secrets and National Security - The value of trade secrets in AI has increased exponentially, and traditional protection methods like patents and copyrights are less effective for easily replicable AI innovations [2] - The U.S. has implemented laws like the Economic Espionage Act and the Defend Trade Secrets Act to criminalize trade secret theft, but enforcement remains limited to U.S. courts [3] - The National Security Commission on Artificial Intelligence (NSCAI) has called for prioritizing trade secrets and intellectual property as part of national security and economic strategy [3][4] Group 2: Legal Challenges and Litigation Trends - There has been a significant increase in trade secret litigation related to AI, with 36 cases reported in the first half of 2025, an 80% increase from the previous year [5] - High-profile cases, such as Tesla's lawsuit against Proception and OpenEvidence's lawsuits against competitors, highlight the growing importance of trade secrets in protecting AI technologies [6] - The "black box" nature of AI systems complicates the enforcement of trade secret rights, as plaintiffs must provide sufficient detail about algorithms to meet legal requirements [8] Group 3: Regulatory and Talent Development Issues - Overly broad AI reporting regulations could undermine U.S. leadership in AI by exposing proprietary information [9] - The U.S. government faces a talent deficit in AI, which is a significant barrier to deploying AI technologies effectively [10] - Concerns about the overreach of trade secret claims could hinder the mobility of talent within the AI ecosystem, impacting innovation [11] Group 4: Strategic Implications - The U.S. is engaged in a complex AI competition, balancing trade secret protection, technology openness, talent mobility, and national security [12] - A bipartisan consensus is forming around the necessity of protecting trade secrets as a strategic imperative for maintaining U.S. technological superiority in AI [12]

(活力中国调研行)广东超常规推进集成电路人才扩容 本硕博在校生破万人 中新网广州6月23日电(记者 郭军 程景伟)2025年"活力中国调研行"广东主题采访情况介绍会23日在广州 举行。广东省教育厅二级巡视员吴艳玲介绍称，"十四五"以来，广东超常规推进集成电路人才扩容，指 导中山大学等8所高校率先筹建省集成电路产教融合协同创新平台，集成电路本科专业点增至23个(2022 年同期为7个)，本硕博在校生破万人，较2022年翻两番，有力支撑广东打造全国集成电路"第三极"。 来源：中国新闻网 编辑：王永乐 广告等商务合作，请点击这里 本文为转载内容，授权事宜请联系原著作权人 中新经纬版权所有，未经书面授权，任何单位及个人不得转载、摘编或以其它方式使用。 关注中新经纬微信公众号(微信搜索"中新经纬"或"jwview")，看更多精彩财经资讯。 情况介绍会现场。中新网记者 郭军 摄 据悉，近年来，广东积极优化高等教育布局，提升科技创新人才供给。广东高起点新建香港科技大学 (广州)、深圳理工大学、香港城市大学(东莞)、大湾区大学等高水平研究型大学，推动设置深圳职业技 术大学、广东轻工职业技术大学等本科层次职业学校，全省高校数量 ...