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Highlights

1. Perfect integration of big data technology and deep learning technology, support end-to-end massive network data collection, storage, analysis, model training, deployment of closed-loop. The platform supports rich computing resources and self-developed optimization algorithm to ensure timely analysis of network data, real-time update of model, and meet the strict stability and real-time requirements of communication network.
2. AI Explorer supports docking with data lake, data pipeline arrangement, visual modeling, parallel training, streaming data analysis, built-in hundreds of commonly used AI algorithms, and end-to-end automatic learning ability to help users quickly develop, evaluate and optimize AI models and improve the performance of AI models.
3. Supports to optimize the performance of the model in different environments such as large-scale GPU cluster, all-in-one computer, embedded network element dedicated hardware, etc. of the data center, to meet the complex and diverse deployment scenarios of AI model in the communication network, and to reduce the investment and operation and maintenance costs of AI system.

Business Value
1. Through this solution, AI model development, training and reasoning with high efficiency and low cost are realized, and the intelligent level of network element, network  operation and network maintenance is improved.
2. Reduce the technical threshold and cost of AI model development, training and reasoning, help operators use their own data to complete model training and upgrading, and provide personalized AI services.
3. Through this solution, operators can find new business value from massive data, improve user experience through network data analysis, build user portrait to improve operation revenue, and open up AI capabilities to develop vertical industry business.