The memory supercycle is about to get A LOT bigger, Every single new wave of AI is creating an entirely NEW layer of demand for memory, and we're still in the EARLY stages of this cycle. HBM capacity per GPU has already increased 3.6X from Nvidia's H100 to B300. Memory per server is expected to DOUBLE over three years as inference and reasoning workloads become increasingly complex. Meanwhile, AI context lengths are growing roughly 30X annually as we move toward agentic AI, and autonomous vehicles could require more than 10X the DRAM capacity of today's advanced vehicles. And here's what makes this so interesting for $MU. We're no longer talking about memory demand being driven primarily by training larger AI models. Every time these models become more capable, they need additional memory to store context, process information, run complex reasoning tasks, and interact with other AI agents. And as AI moves beyond data centers into robotics, autonomous vehicles, and physical devices, we're going to see an entirely new category of memory consumption. This is especially important because Micron isn't just exposed to HBM. It also benefits from server DRAM, LPDDR, and NAND storage, meaning the company has exposure across practically the ENTIRE memory hierarchy. And unlike previous memory cycles, supply cannot simply expand overnight. Building new fabrication facilities takes YEARS, while manufacturers are increasingly allocating capacity toward more complex, higher value products like HBM. That's precisely why I continue to believe investors are underestimating just how long this memory upcycle could last. Bullish on $MU, if you want to see how I’m investing around this memory supercycle and the other AI infrastructure names I’m positioned in, check out my full Milk Road Pro portfolio below. link.milkroad.com/d8cj6v