"开年就领到这么大的'红包'，我们对今年的发展更有底气了！"数据宝公司项目资质总监杨洁的现场感 言，道出了获奖企业的共同心声。 据了解，此次兑现的奖补中，世纪恒通因2025年数据标注业务收入首次破1亿元获300万元奖励，迦太利 华、梦动科技等4家企业凭借数据标注业务收入突破3000万元各获100万元奖励，数据宝核心团队因技术 成果转化新增营收达标获30万元补贴。 原标题：七百万元"红包"精准送达 贵州首次为数据标注企业发放奖补 1月4日，2026年上班第一天，贵州省大数据发展管理局召开数据企业座谈会暨数据产业政策免申即享兑 现会，并在现场为6家优秀数据企业集中发放730万元奖补资金，以"真金白银"为贵州数据标注产业注入 发展新动能，这也是贵州首次为从事数据标注类业务的企业发放奖补。 "以往申报补贴要跑多部门、备数十份材料，如今资金主动到账，真正感受到了'贵州速度'。"迦太利华 董事长黄出为介绍，在政策加持下，企业数据标注业务收入一年增长近4倍，成为第三大业务支柱。谈 及2026年规划，他信心满满："我们将通过组建500人以上本地标注团队，把更多大客户订单落户贵 州。" 省大数据局相关负责人表示，后续还将持续优 ...

（来源：辽宁日报） 转自：辽宁日报 | 关键词 | 新兴产业与未来产业 | | | --- | --- | --- | | 黑保 | 新兴产业布局重点 | 未来产业布局重点 | | 辽宁 | 集成电路装备 机器人 | 深地深海空天 先进储能 | | | 生物医药 航空航天 | 具身智能 | | 江苏 | 新一代信息技术 高端装备 | 第三代半导体 | | | 大飞机集群 | 原子级制造 | | 山东 | 集成电路 智能网联 商业航天 | 深海空天 量子科技 | | | 能源汽车 低空经济 | 元宇宙 | | | 人工智能 低空经济 | 人形机器人 类脑智能 | | 广东 | 商业航天 新型储能 | 量子科技 具身智能 | | | 无人机和无人船 | 氢能和核聚变能 | | 关键词 | 数字化发展 | | | --- | --- | --- | | ક્તરિ | 战略定位 | 差异化举措 | | 辽宁 | 数字辽宁 | 发展数据标注产业 | | | 融入全国一体化 算力体系 | 人工智能赋能工业全要素 | | | | 加强高端芯片、基础软件等关 | | 北京 | 全球数字经济 标杆城市 | 键核心技术攻关 做 ...

Core Insights - The rise of data labeling as a new profession in Guizhou's mountainous regions is driven by the increasing demand for high-quality datasets in the context of the digital economy and generative artificial intelligence [1][3]. Industry Overview - Guizhou is actively cultivating a complete data labeling industry chain, with policies in place to incentivize companies. For instance, companies achieving 300 data labeling employees or 30 million yuan in revenue can receive a reward of 1 million yuan, with the highest reward reaching 10 million yuan [3][5]. - The local data labeling industry has begun to take shape, with 67 companies and over 9,100 employees currently involved [5]. Employment and Talent Development - The South National Data Labeling Incubation Base has expanded its workforce to over 700 employees, with plans to create more than 2,000 jobs in the future [3][5]. - The integration of education and industry is emphasized, with partnerships established between local educational institutions and companies to provide practical opportunities for students. Over 400 students have interned at the company, with about 20% securing positions post-internship [4][5]. Technological Advancements - The nature of data labeling work is evolving from simple tasks to more complex roles requiring specialized knowledge, driven by advancements in AI technology [5]. - Companies are collaborating with educational institutions to develop their own labeling platforms to enhance efficiency in data processing [5]. Economic Impact - Guizhou's digital industry is projected to grow at an annual rate of 16.2%, with an expected scale of approximately 280 billion yuan by the end of the year, including software and IT services surpassing 100 billion yuan [5].

（据新华社电） 《 人民日报 》（ 2025年12月18日 11 版） (责编：胡永秋、杨光宇) 走进贵州贵阳市白云区的一家数据标注孵化基地，此起彼伏的鼠标点击声传来。项目经理赵玉徕正在指 导组内的年轻人在电脑屏幕上将一张张真实道路图片里的车辆、路沿、红绿灯逐一框线标注，再精准填 写"无遮挡""路沿高15厘米"等属性信息。另一边的年轻人，正逐帧为动漫画面补充解释说明。 近年来，随着生成式人工智能、数据要素市场化加快推进，高质量数据集需求旺盛。在此背景下，贵州 的山区县乡不断"长"出一座座数据标注基地。为数据打上标签，正成为贵州年轻人的新职业。 2025年，贵州出台鼓励政策，对数据标注企业给予奖励：企业当年数据标注从业人员首次达300人或营 收达3000万元，即可获得100万元奖励。根据企业规模，奖励分为多档，最高奖励达1000万元。"我们已 建成多个企业特色园区和超8万平方米的白云数据空间产业化基地。"白云区大数据发展管理局局长吴利 豪介绍，白云区规划数个数据标注基地，预计将带动超5000人就业。 "要撑起这样大规模的产业布局，人才是关键。"吴利豪介绍，为此，白云区已与当地多所开设大数据专 业的院校建立紧密联 ...

项目经理赵玉徕正在指导组内的年轻人在电脑屏幕上将一张张真实道路图片里的车辆、路沿、红绿灯逐 一框线标注，再精准填写"无遮挡""路沿高15厘米"等属性信息。另一排的年轻人正逐帧为动漫画面补充 解释说明。 "这些对空间、逻辑和意图进行说明的业务，主要服务于汽车自动驾驶的路况识别、AI动画视频生成 等，是让人工智能更加'智能'的基础。"赵玉徕解释道。 当数字经济的浪潮涌入黔贵大地，贵州的山区县乡里不断"长"出一座座数据标注基地。为数据打上标 签，正成为贵州年轻人毕业后"触手可及"的新职业。 走进贵州省贵阳市白云区的南国数据标注孵化基地，此起彼伏的鼠标点击声传来。 "要撑起这样大规模的产业布局，人才支撑是关键。"吴利豪介绍，为此白云区已与全市多所开设大数据 专业的院校建立紧密联系，向企业进行人才输送，也为数据产业相关专业人才提供实践机会和职业发展 平台。 "这种产教融合的模式，让学生在校期间就接触实际项目，兼具理论和实操技能的毕业生，经过考核可 以直接上岗。"李长春介绍，今年超过400名来自合作院校的学生在该企业完成实习，其中约20%的人通 过考核留任。 记者了解到，以往数据标注员的工作比较简单枯燥，技术含量不高。 ...

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 article highlights the abrupt termination of the "Musen project" by Mercor, leading to the layoff of 5,000 data annotators, who are crucial for AI training [2][4] - Following the layoffs, Mercor introduced a new project called "Nova" with similar tasks but at reduced pay, illustrating a trend of cost-cutting in the AI industry [4][11] - Despite the growth of AI companies and their contributions to GDP, the labor force supporting these advancements faces job insecurity and wage reductions, raising questions about the true beneficiaries of the AI revolution [12][15] Company Overview - Mercor specializes in data annotation for major AI firms like OpenAI, Anthropic, and Meta, playing a vital role in training AI systems [2][6] - The company recently secured a new round of funding, valuing it at nearly $10 billion, while simultaneously reducing labor costs by re-hiring workers at lower wages [6][8] Industry Trends - The AI industry is experiencing a paradox where profits are rising, yet layoffs are at record levels, with companies like Amazon and Google also reducing their workforce [12] - The structure of employment in the AI sector is shifting towards "flexible employment," where workers are classified as independent contractors, stripping them of benefits and job security [16] - This trend reflects a broader industry pattern where companies outsource tasks to minimize costs, leaving workers in precarious positions despite their essential contributions to AI development [16]

Core Insights - The Northeast region of China aims to establish a globally competitive data annotation industry cluster through collaboration among Liaoning, Jilin, and Heilongjiang provinces, focusing on innovation and high-quality development [1][2] - Data annotation is identified as a critical process in AI training, transforming raw data into usable formats, likened to refining crude oil into gasoline [1] Group 1: Industry Development - A high-quality development seminar for the data annotation industry was held in Shenyang, emphasizing the need for a collective brand for "Northeast Data Annotation" [1] - The region plans to create a data annotation solution consortium to enhance collaborative development and innovation within the industry [2] Group 2: Current Industry Status - Shenyang has annotated over 8323 TB of data, developed 134 high-quality datasets, and engaged in 76 large model applications, contributing to national and industry standards [1] - The data annotation industry in Shenyang has seen the establishment of 65 companies, employing over 11,800 people, with an industry scale of approximately 2.59 billion yuan [1] Group 3: Future Plans - The Northeast region will adopt a professional, intelligent, and international approach to build a distinctive and complementary regional industrial cluster [2] - The data annotation solution consortium will integrate resources to provide comprehensive, high-value solutions for national clients, addressing various industry upgrade needs [2]

Core Insights - The conference held on November 5 focused on high-quality data sets and data annotation, showcasing the vibrant market potential with over 500 participating companies and more than 90 cooperation agreements, resulting in a total transaction amount exceeding 900 million yuan [1][2] Group 1: Conference Overview - The event was guided by the National Bureau of Statistics and aimed to promote high-quality data set construction as a fuel for artificial intelligence [1] - The conference featured five industry-specific sessions, including healthcare, smart energy, industrial manufacturing, transportation, and cultural tourism, addressing data needs in large model training and industry digital transformation [1] Group 2: Industry Participation and Contributions - Nine representative companies, including JD Technology, Alibaba Cloud, and Huawei Cloud, shared practical applications of high-quality data sets across various sectors such as e-commerce, cloud computing, and finance [2] - Key figures from national research institutions discussed the construction paths, standards, and evaluation criteria for high-quality data sets [2] Group 3: Local Development and Innovation - Nanjing has positioned high-quality data set construction as a core strategy to activate data value and support AI development, achieving full coverage in the 16 industry areas identified by the National Bureau of Statistics [3] - The city has developed a unique path for high-quality data set construction, characterized by policy guidance, innovation-driven approaches, industry clustering, rich applications, and open cooperation [3]

Group 1 - The conference focused on the importance of high-quality datasets and data labeling for enhancing artificial intelligence capabilities, attracting over 500 companies and achieving more than 90 cooperation agreements with a total transaction amount exceeding 9 billion yuan [1] - The event featured discussions on data needs in various sectors, including healthcare, smart energy, industrial manufacturing, transportation, and cultural tourism, aiming to create a closed-loop system from data demand to supply and value realization [1][2] - A new public empowerment platform for high-quality dataset construction was launched, providing comprehensive lifecycle services for data collection, governance, annotation, and optimization, ensuring data quality through systematic evaluations [2] Group 2 - Nanjing has established a robust data industry ecosystem with over 3,000 data companies, focusing on secure cross-border data support for energy enterprises through advanced data circulation mechanisms [3] - The conference highlighted the shift from "model competition" to "data competition" in the AI industry, emphasizing the need for high-quality, scenario-specific data to overcome application bottlenecks in complex fields like agriculture and manufacturing [4] - The successful hosting of the conference demonstrated the vibrancy and innovation of China's high-quality data market, laying a solid foundation for a dual-driven industrial ecosystem of "artificial intelligence + data" [4]