Real-Time Data Anywhere: Powering Edge AI and Cloud with Data-Centricity

Is Your Edge-to-Cloud Data Flow Ready for Next-Gen Autonomous Systems? Whether you're building advanced autonomous systems in smarter farming, safer mining or transportation, one question remains: Can your edge-to-cloud infrastructure keep pace? AI-enabled systems require unified edge-cloud connectivity for intelligent, real-time information exchange in order to achieve operational agility. Traditional edge-to-cloud connectivity architectures often fall short due to higher costs, slower data pipelines, and the creation of data silos. A data-centric architecture revolutionizes edge-to-cloud communication by forming a common global databus that enables seamless, reliable, real-time data flow across edge APIs and cloud services. This approach is critical for supporting real-time AI, autonomy and operational intelligence where data needs to be accessed from anywhere, anytime. Join leading experts for an overview and panel discussion of the challenges and best practice approaches for distributed AI systems. Key Learnings: 1. AI's Impact: Discover how AI is revolutionizing connectivity requirements for future autonomous vehicles in agriculture, mining and transportation. 2. Data-Centricity: Understand data-centricity and its seamless operation across cloud and edge, encompassing the entire distributed enterprise. 3. Overcoming Limitations: Discover how data centricity overcomes the limitations of traditional message-based methods in the expanding era of AI.