❗️AI has a memory problem

❗️AI has a memory problem AI companies can keep buying faster chips. The problem is, those chips are only useful if they have enough ultra-fast memory to feed them. That memory is called HBM, High Bandwidth Memory. It sits right next to AI processors and moves data at ridiculous speeds, keeping the chip busy instead of making it wait around for information. And demand is about to go absolutely crazy. Morgan Stanley estimates the AI industry could need up to 50 billion gigabytes of HBM in 2027 alone. The reason is that AI is evolving from chatbots that answer a question and stop to agents that actually do things. An agent might research a topic, browse dozens of pages, write code, run tests, analyze the results, remember what happened five steps ago, and then decide what to do next. Every one of those steps creates more data that has to stay close and instantly accessible. Think of a chef cooking a complicated meal. A chatbot gets one ingredient, uses it, and goes home. An AI agent needs the entire kitchen stocked and within arm’s reach for hours. But not everyone can build that kitchen. Only a handful of companies, mainly SK Hynix, Samsung and Micron can manufacture advanced HBM at the scale AI companies need. Building new memory fabs takes years, not a few months. That means the AI race isn’t simply about who can build the fastest GPU anymore, it’s increasingly about who can secure enough memory to keep those GPUs fed. The industry could have mountains of computing power sitting in data centers, but if there isn’t enough HBM to feed it, those expensive AI chips are basically starving. @aipost 🏴