Navigating AI Infrastructure Design Challenges

This white paper discusses the complexities involved in designing and deploying AI applications at scale, focusing on the balance between power availability, latency requirements, data gravity, and system reliability. It outlines foundational concepts such as 'power gravity' and 'data gravity' to explain the driving forces behind AI infrastructure design. The document details various deployment models including SaaS-hosted, cloud-hosted, self-hosted, and edge-hosted, highlighting their unique challenges and providing strategies for achieving optimal performance and sustainability. Advanced strategies such as model optimization, federated learning, and hybrid approaches are examined to meet the diverse business and technical requirements of AI workloads. Additionally, the paper addresses regulatory compliance and environmental considerations, emphasizing the importance of informed design decisions that align with technological advancements and business objectives. Through case studies and a discussion of future trends, including the role of nuclear energy and emerging technologies, the document serves as a guide for organizations aiming to efficiently scale AI applications.