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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

1,285,280 subscribers

22,679 Aufrufe • vor 3 Tagen •via X (Twitter)

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7 Kommentare

Profilbild von Kate | Neuromancer

Kate | Neuromancervor 3 Tagen

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.

Profilbild von BullBear.News

BullBear.Newsvor 3 Tagen

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

Profilbild von Vladislav Mikhalev

Vladislav Mikhalevvor 3 Tagen

🌞😉💯👍

Profilbild von · sophia h.

· sophia h.vor 3 Tagen

Well said!

Profilbild von Raven

Ravenvor 3 Tagen

enterprise ai has entered the thermostat negotiation

Profilbild von TechGeekDavid

TechGeekDavidvor 3 Tagen

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.

Profilbild von Jay Komsa 🇺🇸

Jay Komsa 🇺🇸vor 3 Tagen

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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