SK hynix projected Wednesday that the performance scale of artificial intelligence (AI) infrastructure will grow roughly 20-fold by 2030, driven by rapidly rising demand for AI inference. Ahn Hyun, head of development at the Korean chip giant, made the projection during his keynote speech at the 2026 Semiconductor Exhibition (SEDEX), which opened earlier in the day for a three-day run in southern Seoul. Ahn said the AI inference market is expanding simultaneously in three areas — task complexity, the amount of information processed at a time, and the volume of inference requests. The interaction of the three factors is rapidly increasing demand for AI infrastructure, he said. As demand for AI inference surges, memory is becoming increasingly important for storing and transferring large volumes of data. In particular, the growing capacity requirements of key-value (KV) caches, which store and reuse information previously processed by AI models, are requiring data to be distributed across different types of memory, including high-bandwidth memory (HBM), dynamic random-access memory (DRAM)