As Machine Learning and Deep Learning projects evolve into mainstream adoption, the architectural considerations for platforms that support large scale production deployments of AI applications change significantly as you mature beyond small scale sandbox and proof-of-concept environments. How do you ensure IO bottlenecks are eliminated to keep your GPUs fully saturated with data? This session addresses these questions, draws key business and architectural requirements for compute and storage, and discusses how companies can achieve the maximum benefit from AI platforms that align with these requirements. This session concludes by introducing the Dell Technologies solution portfolio which makes AI simple, flexible, and accessible for organizations looking to deploy large scale machine learning and deep learning.