This talk offers an overview of optimization needs and opportunities in distributed computing, driven by the emergence of novel applications that are hungry for computing and communication capacity. While artificial intelligence tops the list of rapidly expanding application domains with the proliferation of large language models, foundation models, and generative AI, other important application areas contribute unique needs as well. For example, the democratization of content sharing media allows individuals to offer real-time content for potentially global consumption, creating the potential for large bottlenecks as five billion Internet users generate “globally accessible” content. There arises a need to bridge the gap between the growing data generation volume on one end and consumers’ limited capacity to process it on the other. This need is further magnified by the increasing demands on more resource-consuming content modalities (e.g., video, as opposed to text), the increasing need for personalized information processing and summarization, and the rise of increasingly more immersive content. Additional consumption is envisioned from the growth of physical sensing devices driven by the rise of autonomous machines and Internet of Things (IoT) applications. Pervasive automation will increasingly delegate physical functions to drones, robotic assistants at home or business, and autonomous vehicles. At the same time, a growing number of IoT applications continue to contribute to major growth in connected devices. Eventually, data generation and consumption in the world may become dominated by untethered Edge AI. How do these application domains shape future graph algorithms? How do they shape trends in hardware architecture? What challenges arise in the resulting landscape of computing resource optimization? The talk offers a vision of potential challenges and directions in this field.