7 Artificial Intelligence Trends and How They Work With Operational Machine Learning

As artificial intelligence (AI) becomes more prevalent and every industry races to develop AI solutions to advance their use cases, practical challenges have arisen around production deployment. In my previous blog post [1], I described a process for taking machine learning (ML) experiments to production deployments. In this follow up post, I outline seven AI industry trends that help users simplify and scale the overall ML lifecycle. We describe each trend, discuss why it matters for operational ML and what factors should be considered as a business decides to exploit a trend to accelerate or improve their operational ML practice. Figure 1 shows a typical machine learning (ML) lifecycle.