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Bringing AI into the data center starts with solving real-world enterprise challenges. Hear AMD SVP and GM of Compute and Enterprise AI Dan McNamara explain how AMD is helping organizations deploy AI to build what's next within existing power, cooling and space constraints.
22,679 просмотров • 3 дней назад •via X (Twitter)
Комментарии: 7
power, cooling and space constraints are the boring parts of ai infrastructure, but they’re also where the real bottlenecks are. if amd can squeeze more ai out of existing data centers, that’s a pretty useful upgrade.
thermal density limits dictate enterprise hardware cycles far more than raw flops do
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Well said!
enterprise ai has entered the thermostat negotiation
Most enterprise DCs I've worked with were built for 5-10kW racks. Inference at scale pushes past that fast, and liquid cooling retrofits or power upgrades take years to permit and commission.
Existing power/cooling/space constraints are becoming a credit filter: lenders underwrite energized IT MW and usable rack density, not nameplate GPU capacity. The financing unlock comes when deployment is bounded by contracted offtake and DSCR—not simply denser compute.
