AI's biggest challenge is not compute - it's data storage
AI continues to evolve at pace. The novelty of generative models producing their own content is already giving way to the buzz around agentic systems that can set goals autonomously and execute multi-step workflows without human involvement.
Each staging post on AI's journey raises the bar for compute resources and demands more powerful processing. But in the headlong dash towards newer and more specialized architectures, and amid the fuss that greets each silicon innovation, the industry is overlooking something important: beyond a certain scale, AI's biggest challenge is not compute but data storage.
AI's trajectory towards human-like reasoning is driving exponential growth in data volume. Better AI needs better data in ever-increasing quantities, which raises the question of what to do with all that information. Picturing today's AI datacenters as giant compute systems is only half right. They are also data storage systems. The principal battleground in the AI arms...
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