Bringing AI Workloads to the Mainframe

We’ve been pitched a fantastic vision over the past decades about the expected capabilities of artificial intelligence (AI). Maybe AI appeared in our collective consciousness via enthusiastic TED talks, or perhaps the thread started in our favorite sci-fi shows and novels. According to some storytellers, we should be immersed in a general form of AI soon and have ‘robots with personalities’ at our service.

While that’s fun to think about, there’s much more productive work to be done by AI today. AI is being used to change the game in some of the most sophisticated arenas in business and science. The most relevant applications of AI today involve near-real-time data interpretation and decision-making—or inferencing—to meet critical business needs. We must lean on AI to make inferences about what exactly should be done to resolve complex problems, help customers, or drive new opportunities when moments matter.

Bringing AI Workloads to the Mainframe