Generative AI has accelerated the automation of complex digital tasks, and now multimodal perception and reasoning make embodied AI the next frontier. This shift brings adaptive reasoning into the physical realm, enabling natural interaction between humans and intelligent machines, from autonomous vehicles to humanoid robots. While advanced self-driving systems helped pave this path, humanoids introduce a different set of constraints: long-horizon reasoning plus dexterous manipulation must run within a tight power and thermal envelope shared across compute, memory and storage. This presentation examines how memory and storage solutions must evolve to meet application-specific requirements, from automotive to humanoid robotics. Attendees will leave with a framework for assessing memory requirements and making design trade-offs as generative reasoning moves into edge devices.