Universal AI - Execute Your Models Where Your Data and Users Are

Learn how to implement "compute over data" architectures that bring machine learning models directly to distributed data locations rather than centralizing processing in this 37-minute conference talk. Explore the challenges of data explosion across distributed environments and discover why centralized processing approaches are becoming increasingly unsustainable. Examine practical solutions for executing AI models where your data and users are located, enabling more efficient and scalable machine learning deployments. Discover real-world examples and case studies that demonstrate how compute over data architectures unlock new possibilities for distributed AI systems. Gain insights into overcoming the limitations of traditional centralized ML processing and understand the technical considerations for implementing decentralized AI solutions that can scale with modern data distribution patterns.