Yogi Berra famously said: "In theory there is no difference between theory and practice - in practice there is". This applies verbatim to the process of bringing scientific discoveries, including innovative algorithms and computational breakthroughs, to market. For example, hard-science-based technologies like quantum computing promise a … quantum step forward in the way we crunch numbers – while the world is still waiting for a compelling application in a specific market. Other math-based technologies, in primis Artificial Intelligence (AI), have crossed the chasm from lab to industry after a few decades of trial and error. There is a fundamental difference between a scientific breakthrough and creating value in the marketplace, and so many scientists-aspiring-entrepreneurs, in large part, get it (initially, at least) wrong. In this session, we will discuss flaws and successes of bringing math-based technologies such as AI to market, drawing lessons that could help us transitioning our work to mainstream commercial adoption.