Data-driven artificial intelligence is generally recognized as an industry consensus, and the demand for high-quality data is growing exponentially.

Recently, the "2024 China Academy of Information and Communications Technology ICT In-depth Observation Report" was hosted by the China Academy of Information and Communications Technology (hereinafter referred to as the "CAICT") and co-organized by the Key Laboratory of Artificial Intelligence Key Technology and Application Evaluation of the Ministry of Industry and Information Technology. The Artificial Intelligence Partner Forum was held in Beijing. At the meeting, China Academy of Information and Communications Technology launched the "CAICT Artificial Intelligence Partnership Plan" and released major results such as the large model implementation roadmap 1.0, the 2023 large model data resource map and governance paths.

It is understood that the "2023 Large Model Data Resource Map and Governance Path" provides an effective set of tools and methods for "searching for numbers" in large model training; "Artificial Intelligence Data Set Governance Standard System V1.0" "Provide governance methods and references for building high-quality data sets to better promote the development and application of models. At present, three industry standard projects have been completed, and the first draft of some standards has been completed.

The demand for data from large models continues to grow exponentially. High-quality, large-scale and diverse data have become the fundamental elements to ensure the rapid development of artificial intelligence in our country. "Data-Centric Artificial Intelligence" (Data-Centric Artificial Intelligence) AI) has become an industry consensus. Cloud Test Data is a representative of high-quality, scenario-based artificial intelligence data service providers. It also participated as a core participating unit in the "Data Delivery Service Capability Maturity Model for Artificial Intelligence" and "Artificial Intelligence Data Set Quality Management Capability Assessment Method" The preparation of standards will contribute to the rapid and healthy development of the industry.

Cloud Test Data has rich practical experience and profound professional background in the field of artificial intelligence data, and continues to provide high-quality data sets, data collection/data annotation services for many fields such as smart driving, smart cities, smart homes, and smart finance. , data standard platform & data management tools to achieve professionalization and high-quality delivery of scene data, helping enterprises to successfully implement AI applications faster and better. On the business side, Cloud Test Data aims at data needs and development trends in the artificial intelligence era, taking technological innovation to accelerate industry development as its own responsibility, and has successively launched "Cloud Test Data Annotation Platform", "AI Data Set Management System" and other technical achievements to help enterprise AI The overall efficiency of data training has been increased by 200%, and the annotation accuracy is as high as 99.99%, which has accelerated the development of the artificial intelligence industry and improved the large-scale implementation of Al applications.

This year, Cloud Test Data is the first to launch an AI data solution for vertical industry large models based on the characteristics and application needs of industry vertical large models to help enterprises quickly obtain diversified training data, efficiently complete data annotation, and establish A unified and standardized data management system, the output of standardized data sets that can be directly used for model training, and the provision of end-to-end full-process data services, etc., thus meeting the needs of continuous iteration of large models, accelerating the application of models in actual scenarios, and helping Enterprises can improve the performance of large model applications at the data level and gain core competitiveness.

Currently, cloud measurement data in-depth partners cover industries such as automobiles, security, mobile phones, home furnishings, finance, education, new retail, and ecosystems. It includes many Fortune 500 companies, university research institutions, government agencies, leading AI companies and large Internet companies, covering mainstream AI technology fields such as computer vision, speech recognition, natural language processing, and knowledge graphs.

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