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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.

AMD

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22,679 次观看 • 11 天前 •via X (Twitter)

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7 条评论

Kate | Neuromancer 的头像

Kate | Neuromancer11 天前

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.

BullBear.News 的头像

BullBear.News11 天前

thermal density limits dictate enterprise hardware cycles far more than raw flops do

Vladislav Mikhalev 的头像

Vladislav Mikhalev11 天前

🌞😉💯👍

· sophia h. 的头像

· sophia h.11 天前

Well said!

Raven 的头像

Raven11 天前

enterprise ai has entered the thermostat negotiation

TechGeekDavid 的头像

TechGeekDavid11 天前

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.

Jay Komsa 🇺🇸 的头像

Jay Komsa 🇺🇸11 天前

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.

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