Balancing performance, mobility, and cost is essential when selecting external storage for AI computing.

Although physically transporting hard drives remains the cheapest way to move data between research locations, it is inefficient and wastes valuable time.

A more seamless solution that enables smooth data transfer across offices, labs, data centers, and software platforms would greatly improve workflow integration.

At the same time, any new technology adopted must maintain a reasonable cost structure suitable for academic environments, where high upfront investments are not feasible.