Advances in computing technology have made artificial intelligence (AI) a widely used tool with a broad range of applications. Specifically, Generative AI (GenAI) has become a means of improving efficiency in many fields. However, this increased productivity comes with intensive infrastructure requirements. To alleviate this concern, QCT offers the NVIDIA GB200 NVL72 architecture as well as its QCT Platform on Demand (POD) solution. The NVIDIA GB200 NVL72 system is suitable for trillion-parameter large language model (LLM) training, as well as running mixture of experts (MoE) machine learning techniques. Additionally, the QCT POD provides a pre-validated and pre-configured rack-level solution that combines compute, storage, networking components, and infrastructure software. This paper will describe how both the NVIDIA GB200 NVL72 architecture and the QCT POD solution can be used to increase the efficiency and effectiveness of AI workloads.