Core Viewpoint - High Bandwidth Flash (HBF) technology is being promoted and standardized by SanDisk and SK Hynix, seen as a complement to GPU local High Bandwidth Memory (HBM) [2][4] Group 1: HBF Technology Overview - HBF technology faces three main challenges: high operating temperatures of GPU accelerators exceed NAND flash durability, limited write endurance of TLC and QLC NAND flash compared to DRAM, and poor compatibility among different types of NAND flash [2] - HBF is similar to HBM in that both utilize Through-Silicon Via (TSV) technology for vertical stacking of multiple chips, but HBF uses NAND flash, allowing for larger capacity and lower costs [5] Group 2: Market Insights and Predictions - Kim Jung-Ho predicts that in the AI era, memory will play an increasingly crucial role, potentially leading to NVIDIA acquiring a memory company [4] - HBF is viewed as a key technology to overcome storage capacity bottlenecks in AI clusters, with significant importance placed on memory capacity during AI inference [4][6] - The first AI inference systems utilizing HBF technology are expected to debut in early 2027, following the release of HBF memory samples in the second half of 2026 [5] Group 3: Future of Memory Architecture - Kim envisions a multi-layer memory architecture for future AI systems, where HBF will serve as a deep storage solution, complementing HBM and SRAM [6] - The integration of HBM and HBF in GPUs is anticipated to mark a new era of AI computing and memory fusion [6]