Core Viewpoint - Xingtai City has been approved as a provincial-level data labeling base pilot, which will enhance the local industry cluster's intelligent upgrade in the field of artificial intelligence from January 2026 to January 2028 [1] Group 1: Data Labeling Importance - Data labeling is a critical step for the effective operation of artificial intelligence algorithms, transforming raw data such as images, text, audio, and video into machine-readable information [1] - High-quality training data is essential for intelligent models, emphasizing the significance of data labeling in AI development [1] Group 2: Pilot Implementation Focus - The pilot will focus on technological innovation, industry clustering, and talent cultivation, aiming to build intelligent labeling platforms and integrated labeling service platforms [1] - The initiative seeks to enhance labeling technology and platform capabilities, creating a comprehensive industrial ecosystem that includes computing power, data, labeling, and applications [1] Group 3: Talent Development and Industry Growth - The project aims to attract high-quality enterprises and cultivate local innovative entities, fostering a regionally influential labeling industry cluster [1] - There will be a focus on practical and skilled labeling talent through industry-academia-research collaboration and order-based talent supply [1] - The goal is to explore replicable and scalable data labeling industry development models, injecting new momentum into the city's digital transformation and accelerating the establishment of the Central and Southern Hebei digital industry base [1]

（来源：新华日报） □ 本报记者 周娴 实习生 任馨怡 上午9点，徐州市泉山区的江苏淮海科技城园区，江苏京数智能科技有限公司的办公区里，键盘敲击声 如潮水般准时响起。近50名年轻人端坐在电脑前，指尖重复着点击、拖拽、分类的动作——他们正通过 专业标注工具，为一张张商品图像打上精准"标签"。从商品标题、主图，到SKU（库存量单位）属性， 每一个细节都经由他们的双手，被逐一转化为机器能够理解的"语言"。他们，教会机器"读懂"世界。 数据标注行业驶入"快车道" "目前，江苏淮海科技城内已聚集20多家数据标注相关企业，规模小的不足50人，规模大的则超过200 人。"据江苏淮海科技城相关负责人介绍，这些企业的标注业务主要围绕三类通用模型展开：一类服务 于车企的自动驾驶系统，一类面向豆包、千问等大语言模型进行文本与图像标注，还有一类则专注于京 东、淘宝等电商平台的商品信息标注。 市场调研机构艾瑞咨询的数据显示，到2025年，中国人工智能数据采集与标注服务市场规模预计将突破 120亿元。在江苏，数据标注相关岗位的招聘信息遍布各地：南京某研究院招募标注工程师，月薪可达 万元，提供双休与五险一金；徐州有企业面向实习生开放岗位， ...

Group 1 - The core data labeling base in Ledou District, Haidong City, officially commenced operations on January 15, with a total area of 2,528.34 square meters and 400 labeling workstations [1] - The data labeling industry layout includes three operational bases in Haidong City, with a total of 10 registered labeling companies and 1,130 workstations, creating 324 jobs [1] - The base aims to support the creation of a national-level data labeling pilot city, with an expected annual labeling volume exceeding 30 million entries [1] Group 2 - During the 14th Five-Year Plan period, Haidong City will leverage the industrial agglomeration effect of the Ledou core base to promote the digital economy's quality upgrade [2] - The focus will be on data resource management ecology and the assetization of data resources, laying a solid foundation for the successful establishment of a national-level data labeling pilot city [2]

转自：贵州日报 流光溢彩的太平路。 文昌阁路边音乐会。 云岩区数据标注产业基地 俯瞰云岩城区。 连续入选全国高质量发展百强区、全国投资潜力百强区、全国科技创新百强区等；地区生产总值跨越三 个台阶，成为贵州面积最小的"千亿之区"；居民人均可支配收入突破5万元大关，连续四年领跑全省、 全市……这是云岩区发展速度与质量并进、颜值与内涵齐升的五年，是产业能级持续跃升、城乡面貌日 新月异的五年，更是民生福祉不断增进、群众幸福感节节攀升的五年。 面向"十五五"，云岩区将充分利用区位优势、成本优势和产业基础，因地制宜捕捉新机遇、抢滩新赛 道，奋力推动全区高质量发展、现代化建设取得新突破。 A 生产总值实现千亿级跨越 在云岩数据产业园，不仅有杭州景联文科技、北京热热文化科技、上海本原智数科技等全国数据标注类 头部企业，还有承接过《仙剑奇侠传3》动画等知名项目的贵州数谷智云信息科技产业有限公司。 近年来，云岩区以"大抓产业、大抓项目、大抓招商、大抓经营主体"的鲜明导向和实干劲头，将数据产 业特别是作为人工智能基础关键环节的数据标注产业，确立为引领区域产业升级、实现战略突围、产业 突围与经济突围的核心引擎与主导产业。目前，全区已 ...

正在工作的数据标注师 本报（chinatimes.net.cn）记者李氏琼 王晓慧 沈阳报道 发展人工智能产业，既需要顶层设计型的战略人才，也需要扎根实践型的技能人才。 数据标注工作需要工作人员坐下来，不断在现有数据基础上"打标签"的耐心、细心和责任心，这恰好与 残疾人"重脑力专注、轻肢体强度"的工作需求契合。正因如此，越来越多的残疾人也参与到"炼油"中 来。 优势凸显与就业赋能 在数据标注行业，残疾人有特殊优势。比如，听力障碍者有更敏锐的视觉感知，能在图像标注中快速捕 捉细微差异；肢体不便者手部动作更稳定，适配长时间键盘鼠标操作的需求；脑瘫人士行动受限，但是 在节奏清晰、流程明确的重复性任务中，却有远超常人的专注力与持久性。 而且残疾人参与数据标注工作，往往能更敏锐地识别出潜在的歧视性表达或不当标签，反向优化人工智 能的工具属性，提升整体标注质量，让人工智能大模型更具包容性、更贴合社会多元需求。 近年来，随着"东数西算"工程的持续推进，全国七大数据标注基地的陆续建成，数据资源大量向中西部 倾斜，依托地区劳动力成本优势，岗位数据标注岗位得以大量布局，也解决了不少残疾人就业难、离家 远的问题。 "我们这里好多人 ...

Jay 发自 凹非寺 量子位 | 公众号 QbitAI 37岁华裔学霸AI创业，0融资，估值240亿美元。 是的，白手起家， 没拿投资人一分钱 。 更强悍的是，纯靠一己之力，轻松斩获谷歌、OpenAI等AI巨头的大单，硬生生给公司干成 了估值240亿美元的超级独角兽。 而这家公司的创始人—— Edwin Chen ，如今也凭借180亿的身价，跻身福布斯400的最年 轻富豪，也是这波新晋富豪中最富有的一位。 AI创业成最年轻新晋富豪 福布斯400新晋最年轻富豪—— Edwin Chen ，美裔华人，年仅37岁。 这时候，Edwin忽然从科幻电影《降临》的原著中得到了灵感。 《降临》讲的是一位人类语言学家，试图通过破译外星文明的文字与其建立沟通。但随着理 解不断加深，她却逐渐掌握了一种语言之外的能力—— 对时间的非线性认知，乃至「预见未 来」 。 在Edwin看来，在我们的世界里，人类，就是那批拥有超能力的外星人。而AI可以通过标注 数据，学习我们的思维模式，最终获得独属于人类的超能力——智能。 从大厂打工人，到硅谷估值240亿的超级独角兽，他仅仅花了5年。 Edwin毕业于MIT，先后在推特、谷歌和脸书工作，担 ...

Core Insights - The establishment of the Dongguan Data Annotation Industrial Park marks a significant step in enhancing the data annotation industry, which is crucial for AI model training and applications in advanced fields like autonomous driving [1][2] - Dongguan is positioning itself as a hub for high-end data annotation, leveraging its industrial strengths and aiming to attract over 50 data companies and create more than 30 high-quality datasets within three years [2][6] - The data annotation industry is evolving from labor-intensive processes to high-tech, knowledge-intensive applications, with a growing demand for skilled data annotators [3][4] Industry Overview - Data annotation is essential for AI systems, with data, algorithms, and computing power being the three core elements [1] - The industry is transitioning from simple manual annotation to complex, high-value applications, particularly in industrial manufacturing, which is currently a national shortfall [2][4] - The demand for high-quality, specialized data annotation is increasing, especially with the rise of large AI models and the need for precise, efficient data processing [4][5] Regional Development - Dongguan is actively developing its AI application pilot base and data industry cluster, focusing on high-quality data annotation to extract value from vast industrial data [1][6] - The Dongguan Data Annotation Industrial Park is supported by significant investments and partnerships with major companies like Baidu and China Telecom, aiming to create a comprehensive data annotation ecosystem [6][8] - The region benefits from a rich talent pool, with approximately 176,500 university students and over 20,000 graduates in AI and big data fields annually [7] Strategic Initiatives - The park aims to provide substantial support to enterprises through rent reductions and talent subsidies, fostering collaboration with local industries [5][6] - The establishment of specialized data annotation bases by Baidu and China Telecom is set to enhance the capabilities of local companies in high-end data annotation [6][8] - The introduction of advanced technologies and platforms for data annotation is expected to create a differentiated, intelligent, and high-level data annotation capacity in Dongguan [8]

Core Insights - The data annotation industry, as a critical sector in artificial intelligence, is experiencing rapid growth but faces challenges such as a shortage of application-oriented talent and insufficient practical experience [1] Education Chain - Rizhao City has established a unique path of industry-education integration through a "five co" model, which includes collaborative curriculum development, joint professional construction, project incubation, shared operational bases, and co-managed colleges [1] - Eight local universities have set up data annotation-related majors and developed practical courses like "AI Data Annotation Technology," enabling students to acquire skills directly in the classroom [1] - The introduction of enterprise projects into campuses allows students to engage in real-world tasks such as data cleaning and AI annotation review, ensuring they are job-ready upon graduation [1] Talent Chain - Rizhao is the first in the province to implement a "Three-Year Action Plan for High-Quality Development of the Data Annotation Industry," focusing on a talent cultivation mechanism that integrates industry and education, led by enterprises and supported by universities [1] - The plan encourages the introduction of outstanding teams and the establishment of talent incentive mechanisms within enterprises to stimulate innovation [1] Industry Chain - The industry chain is centered around Rizhao, creating an ecosystem of "on-campus bases + off-campus parks," which provides practical training for nearly 9,000 students annually [1] - This model facilitates a seamless transition from internships to employment, ensuring a stable talent supply for the industry [1]

Core Insights - Datacurve is a new company in the high-quality data labeling sector, aiming to challenge established players like Scale AI, with a unique "gamified labeling" approach that has attracted significant investment and participation from skilled engineers [3][4][12]. Group 1: Company Overview - Datacurve has raised a total of $17.7 million (approximately 120 million RMB) in funding, with a recent $15 million Series A round led by notable investors from top AI companies [4][12]. - The company operates a platform called Shipd, which gamifies data labeling tasks by packaging them as "quests" that engineers can complete for cash rewards [3][10]. Group 2: Unique Business Model - The platform has attracted over 14,000 engineers, who are motivated by the challenge and gaming experience rather than just monetary compensation [7][8]. - Datacurve emphasizes an "engineer-first culture," creating a community that values recognition and professional identity, distinguishing it from traditional data labeling platforms [11][12]. Group 3: User Experience Optimization - The tasks on Shipd are designed to be technically challenging, with multiple validation mechanisms to ensure high data quality [8][10]. - The platform incorporates competitive elements such as leaderboards and rewards for consecutive task completions, enhancing engagement among participants [10][11]. Group 4: Market Position and Competition - Datacurve faces competition from other data labeling companies like Surge AI, which also focus on high-quality data, but Datacurve's unique model may provide a competitive edge if it can maintain data quality and engineer participation [25]. - The company is not solely reliant on data labeling for its future; it plans to expand into other verticals such as finance, medicine, and marketing [25].

Core Insights - Surge AI, founded by Edwin Chen, is set to receive a $1 billion Series A funding, potentially valuing the company at approximately $24 billion, making Chen a billionaire with a net worth of $18 billion [1][4] - Edwin Chen, previously low-profile, has emerged as the youngest billionaire on the Forbes 400 list, raising questions about his background and the rapid success of Surge AI [3][4] Company Overview - Surge AI is a data annotation company that has achieved over $1 billion in annual revenue within five years of its establishment, claiming profitability from day one [4][12] - The company employs a unique human-AI collaboration model for data annotation, contrasting with traditional methods that rely on low-cost labor from developing countries [7][13] - Surge AI has secured major clients, including Google, Meta, and Microsoft, with Meta alone spending over $150 million on Surge's services [7][12] Industry Context - Data annotation is a critical component of the AI industry, providing essential training data for generative AI models, and is often referred to as the "cyber Foxconn" of the AI sector [5][7] - Surge AI differentiates itself from competitors like Scale AI by focusing on high-quality data annotation rather than volume, aiming to meet the complex needs of AI models [13][15] Founder Background - Edwin Chen, a graduate of MIT, has a background in algorithm work and content moderation at major tech companies, which informed his understanding of the importance of quality data annotation [9][11] - Chen's entrepreneurial journey began in 2020 when he founded Surge AI, driven by a desire to improve data quality and avoid the pitfalls of traditional outsourcing [12][14] Future Aspirations - Surge AI aims to become a leading force in the AI industry, with plans for Edwin Chen to take a more prominent role as a thought leader [8][16] - The company has adopted a "反硅谷" (anti-Silicon Valley) approach by self-funding and avoiding venture capital, allowing for greater control over its operations and direction [14][16]