Keynote speech at the Math 2 Product (M2P) on 30/5, Taormina.

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.”

By maxversace

Max Versace is an AI executive, scientist and entrepreneur specializing in brain-inspired AI, neuromorphic computing, Edge AI and Physical AI. He is VP of Emergent AI at Analog Devices and former co-founder and CEO of Neurala.