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Ahmed Shihab, Chief Product Officer of Western Digital, stated that the key to AI storage competition is not simply pursuing the fastest medium, but whether it can continuously scale capacity at an affordable cost. He believes that many architectures run well in the early stages, but when the data scale grows from several PB to hundreds of PB or even EB levels, issues may arise due to uncontrolled costs.Flash storage is suitable for high-performance, low-latency scenarios such as model weights, GPU overflow, KV caches, and session contexts; HDDs are more suitable for large-scale, long-term storage, and cost-sensitive data such as training corpora, logs, checkpoints, compliance records, synthetic data, and inference outputs. He summarized: "Flash handles the present, HDD handles the entire lifecycle."At the scale of AI, storage costs themselves will become an architectural issue. Long-term storage of large volumes of data on high-performance media will crowd out budgets for computing, networking, power, and personnel. For many bulk storage workloads, the issue is not whether flash can store, but whether customers can afford the total cost of using flash in the long term.In the future, AI storage will not be dominated by a single technology, but should be designed in layers based on performance, cost, power consumption, density, reliability, and data lifecycle. He emphasized that this is not a competition between flash and HDD, but rather a need to match the appropriate medium for different workloads from the very beginning; otherwise, the architecture may impact business sustainability as it scales.