Riverbed uses AI and ML technologies that can help solve sets of problems that are non-intuitive to humans and impossible for traditional iterative programs. Almost 60 years ago the term artificial intelligence (AI) was coined by John McCarthy at a workshop at Dartmouth College and it spurred a flurry of scientific work on imitating the behavior of the human brain in computer software. The excitement was high, because it seems so logical: capture the magic sauce of human cognition and problem solving in computer program and all that a human can do, now the computer can do. Without the need to write specific computer programs for each problem we are trying to solve, the computer will simply "learn," and mimic the human's problem solving capabilities. But then we entered the dark ages of machine learning (ML). Decades went by without any meaningful progress to speak of.

Let's highlight the transition from WCM platforms to digital experience management with a hypothetical example that Acquia used in a series of presentations at its October Engage user conference in Boston. In the desktop days, a cook planning a dinner party would have to gather recipes, create a grocery list and write it all down on paper. In a digital experience management implementation, actionable data -- perhaps even fished from a data lake using artificial intelligence -- would find recipes based on a voice request, generate a shopping list from the recipes and store it on a mobile app. Automatically, the list arranges itself, so each ingredient appears in order of placement in the store, because it's hashed against the store's floor plan. Finding even the most specialized products is simple -- intelligence baked into the app combines with in-store Wi-Fi beacons to pinpoint the right shelves.