 Hello everyone, this is Lixiang from Channelbuy. This time, I want to introduce one AI evolution with the OLAB case. Wiping to the ETSI AI which is implemented by Channelbuy with the cooperation of Intel, Cloud, and Hong Kong S3. Okay, let's begin. Firstly, with more and more infrastructure being involved into the network, that's the network becoming a lot more competitive. So how to make the operation more impenetrable and lead the network more tangent and smarter is a big challenge. Thanks to the OLAB, however, network and services design fantasy. What is OLAB? OLAB is a comprehensive platform for orchestration management and automation of network and edge computing services for network operators, cloud providers, and enterprise. At the same time, policy-driven orchestration and automation of physical and virtual networks functions enable repeat automation of new services and complete life cycle management critical for 5G and next-generation networks. What is the AI? Its printable network intelligence is defined as connectivity. Network management architectures using AI techniques and contains a wide policy to adjust offered service based on change in the user's needs, environmental conditions, and business goals. It therefore fully deface the 5G network with automated service-providing operation and assurance as well as optimized select management and resource orchestration. AI has also launched the protocol concepts aiming to demonstrate how AI techniques can be used to assess network operations include 5G. The user of AI techniques in the network were so proper of future networks deploying and operations. We introduced a case of AI combined with OLAB, which is an AI property. It is an intelligent telecom network energy optimization, which is mainly implemented by users of OLAB, approved in January 2020, not for one year. The team members include China Mobile, Intel, ConeCloud, and S3. The case is meant to showcase the network FAAO7 proposed and developed by the co-led network with a special attention to the AI ML aspects in the context defined by the AI. The case intends to test an automated AI-based approach that is proposed by the AI architecture of network self-organization and energy optimization. This case concerns two scenarios. The first scenario is to demonstrate that the AI-based techniques enable the network to be horizontal and a medical scanning network of PMF to be staffed and shut down. The second scenario shows that CPU frequency can be wise to turn off a turning down internet to CPU power saving. The case mainly can be split into four parts, real-time series telemetry data connector from the CPU and VF-EPC infrastructure by the platform connection agent. Using all of AI application technology and inference to be processed online or offline as required. VF-Scanning, PMF-Shutdown, and CPU-Turningoff-Turningdown commands send back to the EEPC infrastructure. In the following video, it will showcase how we achieved intelligent power management by Old Diamond. We have several scanning and adjusting CPU frequency based on the integration with OLAP and ML Drive data elastic platform. In this project, we work together and offer the highly-managed BNT, Easier Maintenance, and Adriven Management, orchestrating several achievable elastic and local server scanning and intelligent power management. Working something in 5G environment must be covered before to forfeit high-speed network connectivity and various kinds of server-level agreements. In this case, we developed an Adriven Management with Automatic Auschwitz to pre-configure and pre-segulate the servers for the future demands. Also CPU frequency is optimized to improve power efficiency. When the system determined to scan in, the system automatically slowed down the CPU frequency. Then, start to terminate two waves and mark the status penalty late. Show in the dashboard. In the same scenario, when the system determined to scale out, the system must be lab, CPU frequency meanwhile, the system will also launch two waves, and mark the status assigned to show in the dashboard to scale out the community of the servers. Okay, that's all. Thank you.