Pushing the Boundaries of Knowledge

We'll be able to simulate earthquakes more accurately so we can better protect people and infrastructure. Smarter crop analysis will help make farming more efficient so we can better feed the world's growing population. We'll be able to accelerate medical diagnoses and drug discovery.

In industries such as energy and manufacturing, machine learning could refine the inputs to better focus simulations. And simulation could be used to generate scenarios for AI to analyze. If we use a generative adversarial network to combine simulation data with massive amounts of satellite imagery, we'll even be able to emulate the universe.

So what can you do to get started with AI workloads today? When you're already tackling the world's thorniest scientific challenges, you don't want additional complexity in your computing infrastructure. Intel has optimized popular deep learning frameworks so you can run deep learning applications on your familiar Intel Xeon processor-based architecture. This means you can benefit from balanced, scalable performance without needing to invest in installing, configuring, and managing dedicated accelerators, all while you develop and optimize the AI algorithms to meet your specific business and mission requirements.

Take your first step toward using AI on your familiar Intel Xeon-based infrastructure today. Find out more at intel.com/hpc.