Rearchitecting your infrastructure for generative AI

As generative AI propels organizations into the future, IT leaders must construct infrastructure able to withstand the performance requirements these revolutionary technologies bring. With exponential growth in data generation, model size, and computation demands, existing infrastructure cannot handle the requirements of training and serving Large Language Models like PaLM2. This guide provides technology leaders a real-world roadmap for architecting robust generative AI systems, examining cost, scalability, security, and performance dimensions. The paper outlines best practices for leveraging specialized virtual machines optimized for AI, managed machine learning offerings like Vertex AI, and flexible container environments like Google Kubernetes Engine to develop and run generative AI applications wherever they're needed.