AI/ML Solutions for Large-Scale Development and Deployment
Join Equinix at NVIDIA #GTC22 to hear the latest breakthroughs in AI and for our on-demand session where we’ll explore new consumption models for AI infrastructure that make it easier for enterprises to speed time-to-insight. About the Session In a recent survey, 91% of enterprise respondents indicated a preference for hybrid cloud infrastructure for AI development, and 93% said hosted/managed infrastructure services is critical to AI success. Businesses today are turning to new approaches that can simplify and expedite the process of delivering business-critical AI apps without the complexity of standing up their own infrastructure, or building out their own data centers. In this joint Equinix and NVIDIA session, we’ll explore new consumption models for AI infrastructure that make it easier for enterprises to speed time-to-insight.Equinix + Nvidia: Building the AI Factories of the Future
Look, AI isn’t coming. It’s already here — and it’s growing fast. Not linear growth. We’re talking exponential. The kind that breaks things. AI workloads are now so intense they’re overwhelming the networks, data centers, and power grids we built for a different era. The old infrastructure? It’s like trying to power a space launch with a car battery. Just doesn’t work. That’s why Equinix and NVIDIA are working together to rethink how we build and scale the physical backbone of AI. We’re not talking about incremental upgrades. This is about building AI factories — purpose-built, energy-efficient, high-performance, globally distributed systems that can actually keep up. Here's 3 principles to get us there: First: Everything starts with data. No data, no intelligence. And moving massive volumes of data — fast — requires serious interconnection. Equinix just happens to sit at the core of that. Clouds, enterprises, AI services — they all plug in here. That kind of neutral ground is critical when the entire AI ecosystem is converging. Second: Latency matters. A lot. AI inference is becoming incredibly time-sensitive. Location is crucial. With presence in 73 metros worldwide, Equinix lets you put compute where the data is and where the users are — edge, core, whatever. This isn’t a nice-to-have; it’s fundamental to real-time AI. Third: Trust. Enterprises don’t want black boxes. They want control over their AI environments — the data, the models, the infrastructure. That’s where private AI with NVIDIA DGX comes in. Combine that with Blackwell and you get 30x more energy efficiency and 35x better AI performance. Which is, frankly, insane. Now layer on Equinix’s work in liquid cooling — which is cool, literally — and the push to 100% renewable energy across their entire footprint? We’re not just scaling AI. We’re making it sustainable. Bottom line: AI is the next industrial revolution. But revolutions don’t run on yesterday’s infrastructure. They need something new. And fast. That’s what we’re building. Together. Want to see how it all comes together? Watch how Equinix and Nvidia together are building what's actually needed for the AI era. Check out this full video >>
