How AMD End-to-End Hardware Turns AI Innovation Into Impact

"AMD AI is no longer a moonshot-it's essential for gaining a competitive edge. Generative AI's transformative potential is undeniable: By one estimate, it's expected to add more value to the global economy than the UK's GDP. Harnessing its once-in-a-generation opportunity is a strategic imperative for enterprises to reshape operations across the spectrum, from customer support to engineering, and set their business up for forward-looking innovation."

"Enterprise AI's unprecedented compute demands and ever-evolving product cycle call for a bottom-up, long-term initiative, one that unifies an organization's complex environment of workloads, legacy systems, and disparate insight sources. The end goal is to enable an omnipresent infrastructure to power AI's lifecycle, spanning model training and intelligent, user-facing experiences. But many enterprises' AI ambitions are stalled by their own tech stack. What's often missing is an end-to-end partner that can anchor and architect an enterprise's AI journey."

"In AI, time-to-insight is critical for extracting meaningful value, but expanding it rapidly comes at an enormous cost for enterprises whose resources are tied up in existing IT infrastructure. And there's no let-up: AI's unquenchable need for computing power is projected to skyrocket, a McKinsey report found. In the next few years alone, data centers will need more than three times in capital expenditures as traditional IT applications."

Generative AI can add vast economic value and requires enterprises to reshape operations from customer support to engineering. Many organizations lack the technical foundation to capitalize on AI opportunities. AMD offers scalable, end-to-end compute and security solutions designed to prepare workforces for an AI-centric future. Effective enterprise AI requires a bottom-up, long-term initiative that unifies workloads, legacy systems, and disparate insight sources into omnipresent infrastructure to power model training and intelligent, user-facing experiences. Tech debt and existing IT resource constraints increase time-to-insight and costs. AI's computing demand is projected to skyrocket, requiring substantially higher data-center capital expenditures than traditional IT.

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