A quick-service restaurant chain is running its AI models on machines inside its stores to localize delivery logistics. At the same time, a global pharma company is training its machine learning models on premises, using servers it manages by itself. Cloud computing isn't going anywhere, but some companies that use machine learning models and the tech vendors supplying the platforms to manage them say machine learning is having an on-premises moment. For many years, cloud providers have argued that the computing requirements for machine learning would be far too expensive and cumbersome to start up on their own, but the field is maturing. "We still have a ton of customers who want to go on a cloud migration, but we're definitely now seeing -- at least in the past year or so -- a lot more customers who want to repatriate workloads back onto on-premise because of cost," said Thomas Robinson, vice president of strategic partnerships and corporate development at MLOps platform company Domino Data Lab.

Ed Ikeguchi, chief medical officer at AiCure, an artificial intelligence (AI) and data analytics company, said 2018 was a year filled with change – both positive and negative. On the upside, the pharmaceutical industry more broadly adopted innovative technology leveraging AI and machine learning for use across R&D as well as commercial development, he told us. Regulators also got on board, with the US Food and Drug Administration (FDA) releasing a statement backing the idea of AI-enabled technology and encouraging its use in health care. Larger technology companies like Google, Apple, and Amazon also have shown greater investment and interest in the health care space, Ikeguchi noted. As one example, Amazon, JP Morgan, and Berkshire Hathaway teamed up to form a new company that aims to address US employee health care.