Micron develops edge inference memory for physical AI applications

Micron is advancing the development of a specialized storage chip for physical AI applications called Edge Inference Memory (EIM). At a semiconductor forum in Seoul during SEDEX 2026, Micron executive Lee Jeok emphasized the rapid growth of markets such as autonomous driving, humanoid robots, and AR/VR, and noted the company's collaboration with key clients to develop products tailored for these areas. EIM is designed to process AI inference data quickly by stacking low-power memory on top of logic chips, differing from in-memory computing (PIM) in architecture but sharing the goal of improving data efficiency. Micron has not yet disclosed performance metrics for EIM, but is working on integrating it with LPDDR6. Industry experts predict mass production by late 2028. Humanoid robots, which require real-time environmental sensing and decision-making, demand higher memory bandwidth than traditional industrial robots. Currently, they rely on LPDDR memory, but as AI models grow in complexity, Micron forecasts a shift to high-bandwidth memory (HBM). Lee Jeok noted that while current models use 1B–2B parameters, future visual language models will necessitate HBM. Micron also anticipates a need for 200GB DRAM and 4TB storage in advanced humanoid robots, compared to 12GB DRAM and 256GB storage in current models. The company is collaborating with robot manufacturers, chip designers, and cloud providers to shape early system designs for physical AI.