Deep-dive research on the structural constraints shaping the AI infrastructure build-out. Each article traces a specific bottleneck from evidence to forecast.
Three years ago, "memory was cheap" was a safe industry aphorism. Now it isn't — and the consequences ripple far beyond chipmakers. As AI training clusters multiply demand for HBM while displacing ordinary DRAM onto the same silicon real estate, server RAM prices have doubled, foundry allocation wars have drawn new entrants like Broadcom into HBM design, and geopolitical export controls are about to redraw the global map.
Data center power infrastructure — UPS systems, gensets, switchgear, grid interconnection — is becoming THE binding constraint on compute deployment in 2026–2028. Every major manufacturer has raised guidance. Every utility faces multi-year waitlists.
Three years ago, "build it and they will come" was the playbook for hyperscale datacenter development. Now the bottleneck has shifted from land, power purchase agreements, and construction crews to something far more fundamental: the physical grid itself.
By mid-2026, the four largest server manufacturers — Dell, Supermicro, HPE, and Lenovo — were sitting on a combined order backlog exceeding $170 billion, each racing to build out capacity while competing for NVIDIA GPUs, TSMC foundry time, and scarce DRAM allocation.
Eighteen months ago, "800G optical" was a roadmap item in an analyst slide deck. Now it is a physical constraint on AI cluster construction, a bottleneck around which entire companies have been funded, and the axis along which a new wave of networking competition is being fought.