Qualcomm and AMD are reportedly considering the integration of SOCAMM2 memory into their AI product lines to enhance memory capacity and speed. Following NVIDIA’s "Vera" CPU, which features LPDDR5X memory on the SOCAMM factor, offering 1.2 TB/s of memory bandwidth and supporting up to 1.5 TB of LPDDR5X memory, Qualcomm and AMD aim to pursue a similar strategy to achieve high-speed, high-capacity AI systems. These systems require fast memory close to AI accelerators, and SOCAMM can complement the extensive HBM memory on the accelerators. It acts as a fast memory pool with sufficient capacity to store entire models in memory, reducing the need for data transfer to SSD flash storage.

NVIDIA’s SOCAMM approach involves surrounding the CPU with multiple SOCAMM modules, a strategy Qualcomm and AMD are expected to adopt in their AI solutions. AMD’s Instinct MI accelerators, paired with EPYC CPUs, might be the next candidates for this integration, or AMD may develop a completely new system. Qualcomm already offers AI solutions like the AI200 and AI250 inference accelerators, which include up to 768 GB of LPDDR5 per card. These could soon be complemented by SOCAMM, allowing for standardized memory expansion based on the SOCAMM standard rather than soldering individual memory modules. This approach would enable manufacturers to offer various system versions and solutions by simply adding or removing SOCAMM modules, without the need for extensive PCB soldering work.