artificial intelligence is an important driving force for a new round of technological revolution and industrial change. Data from McKinsey & Company shows that artificial intelligence can create 3.5 trillion to 5.8 trillion US dollars in business value every year, increasing the business value of traditional industries by more than 60%. As one of the core elements of artificial intelligence, data plays a vital role in the positive development of artificial intelligence technology.
Judging from the development and future development trends of the AI industry chain, the market size of China's AI data service industry is gradually expanding. On the one hand, with the optimization and innovation of algorithm models, technical theories and application scenarios, the AI industry's scalable and forward-looking needs for training data are growing rapidly; on the other hand, with the increase in the types of training data demands within the industry As the requirements for service standards increase, the professional division of labor in the industrial chain will become increasingly clear, and the industry will rapidly develop in the direction of specialization and standardization.
As one of the representative manufacturers in the AI data service market, Cloud Test Data provides one-stop data processing services on the business side for many fields such as smart driving, smart cities, smart homes, smart finance, new retail, etc., providing general data sets, data Production tools such as the annotation platform data management system continue to provide high-value data support for mainstream AI technology fields such as , computer vision, , speech recognition, natural language processing, knowledge graphs, etc.; on the industry side, we are also actively promoting and improving the ecological development of AI data services. Through the accumulation of rich and mature data services and strategies, we have joined forces with major representative companies in the AI field to actively promote the systematic construction of industry-related standards and contribute to the rapid and healthy development of the industry.
participated in the compilation of AI development management standards and led the output of capabilities
In recent years, Model/MLOps has attracted widespread attention in the artificial intelligence industry, and has helped various roles in the enterprise collaborate efficiently from the perspective of model full life cycle governance, thereby empowering business value enhancement. . At present, the Model/MLOps management system is still in the initial stage of development, and needs to be improved in terms of process standardization, process automation, and standard consistency. It is urgent to compile the Model/MLOps standard system.
The world's first AI model development and management standard - "Artificial Intelligence R&D Operations Integration (Model/MLOps) Capability Maturity Model Part 1: Development Management" released by China Academy of Information and Communications Technology Yunda has filled the gap for domestic and foreign machine learning project development Gaps in management standards. Among them, Cloud Test Data and more than 30+ well-known companies in the industry, including Baidu , Huawei , JD , etc., participated in the formulation of this series of standards. The standard starts from three capability sub-domains: demand management, data engineering and model development, including 10 capability items and 28 capability sub-items. It proposes five levels of capability requirements for the machine learning development management process, namely basic level. , professional level, excellent level, excellence level and pilot level. At the same time, this standard provides guidance for efficient collaboration among various roles in the enterprise from the perspective of model lifecycle governance. It can help enterprises improve the efficiency of AI R&D operations, enable business value enhancement, and promote the intelligent transformation of enterprises.
Output intelligent driving annotation specifications to exert professional value
With the advent of the intelligent AI era and the 5G era, intelligent connected cars have become the development direction of the global automobile industry, and data is used as raw material to drive the process of automobile intelligence. In recent years, domestic and foreign companies, universities and research institutes have released numerous autonomous driving data sets, and the complexity of intelligent connected vehicles has increased exponentially. In the future, the development and safety verification of intelligent connected vehicles will need to be based on massive scenario data. . Scene data annotation and point cloud and annotation in smart car scenarios still have problems of varying forms and uneven quality.
"Intelligent Connected Vehicle Scene Data Image Annotation Requirements and Methods" "Intelligent Connected Vehicle LiDAR Point Cloud Data Annotation Requirements and Methods" proposed by China Intelligent Connected Vehicle Industry Innovation Alliance, China Automobile (Beijing) Intelligent Connected Vehicle Research The Institute Co., Ltd. has joined forces with industry forces to complete the preparation. As the only representative manufacturer of training data services, Yunmei Data jointly drafted and compiled it with industry representatives such as Institute of Automation of the Chinese Academy of Sciences , China Automotive Technology Research Center , Beijing Automotive Research Institute , and FAW Co., Ltd.The release of the two standards
aims to provide the industry with basic specifications for scene data image annotation and data point cloud annotation, and provide a set of practical annotation methods, which promotes the standardization of scene data image annotation and improves the versatility of scene data. and ease of use. The research and formulation of standards is of great significance to the construction of the standard system for intelligent networked vehicle scene data annotation in my country. It fills the gap in my country's intelligent networked vehicle scene data annotation standards, thereby assisting the research and development and testing of intelligent networked vehicles and promoting The intelligent connected automobile industry will develop better and faster. Since the establishment of
, Cloud Measurement Data has been taking technological innovation to accelerate the development of the industry as its mission. It has successively launched technical achievements such as "Cloud Measurement Data Annotation Platform" and "AI Data Set Management System" to provide AI-related enterprises with solutions for processing large-scale sensing data. ability. In the future, Cloud Measurement Data will continue to uphold its sense of responsibility for the long-term development of the industry, actively play the role of a practical leader, and contribute "standard power" to promote the high-quality development of the AI data service industry.
