 Hi, I'm Susan Zhou from VMware by Berkham. I'm so honored to be here and share how can the two hot tech teams, Kubernetes and AI, achieve together in the next decade. Over the past decade, Kubernetes has revolutioned the way we deploy and manage applications, establishing as an essential cornerstone of modern infrastructure. AI, after years of sentimentation, has also entered a period of rise and explosion in recent years, quickly re-shipping various fields. Looking ahead to the next decade, the synergy between Kubernetes and AI is inevitable. Considering how the synergy can ignite sparks of technological innovations and bring mutual success, is a subject to a report for exploration. As an elastic and scramble platform for modern application, Kubernetes undeniable needs to take on the mission of supporting and accelerating AI development and deployment. How can Kubernetes benefit AI? Optimize resource utilization to minimize the time and expense involved in training complex model. Automate the governance to ensure AI system complex with regulatory and ethical standards. Or transfer the federator learning to train model on decentralized devices for data progress. Standardize AI resources with OCI for efficient management of transfer replication, sharing, and loading of models and data sites. Introduce a streaming-led model interface for efficient management and the loading of a versioning model, libraries and frameworks, reducing model size and spin-up deployment. Introduce AI-specific workload type to simplify configurations and align with the needs of data sets, sets, and model experts. What can AI bring to Kubernetes to make Kubernetes better and more successful? AI has accumulated a vast amount of the industry knowledge and has the powerful ability to learn and involve quickly. AI can make the Kubernetes platform smarter, more elastic, and more reliable. Assisted the star interactive interface by directly addressing operation requirements that users are afraid of from the complex associated with scraping and YAML configuration failures. Intended scaling AI-driven algorithms enhance scaling, occurrence, and efficiency, optimizing resource use, predictive, and automated operation. AI predicts the system trends and adjusts resources at the configuration in real-time to meet changes requirements. Enhance the security. AI acts as a security expert, automatically identifying and mitigating potential threats and vulnerabilities. Self-healing, ASF diagnosis and repairs the issues detected in the environment automatically to minimize downtime and manual interaction. AI controller introduces a specialized AI controller framework to facilitate smart work flows through advanced decision-making algorithms. The new decade chapter has already begun. The possibility with Kubernetes are limitless. We, here we, we, and the younger generation believe that Kubernetes will continue to thrive in the next decade. Hi, everyone. I'm ID. And I'm nine years old. I've heard lots of cool stuff about something called Kubernetes from my dad. I don't know much about it yet, but I think it must be a very interesting and awesome thing. When I grow up, I hope I can work with Kubernetes and help make it even better. Thanks, my son, ID. Looking forward to gathering again in 10 years to share new stories of Kubernetes. Welcome to the HarperBoss for AMO to support. Welcome to the VMware TedoBoss for Kubernetes for AI. Further discussion, thoughts, and the Open Source Project contact me through the email. Thank you very much.