Tonya Hall and Dr. Eli David, co-founder at Deep Instinct and DeepCube, talk about the battle between cloud and edge and how the solution may be a combination of the two.

This does not work for many manufacturers, who tend to avoid the security and latency issues from Cloud-reliant software to manage the day-to-day complex workflows. Fortunately, technology evolving, and in a 2020 that has otherwise been challenging for the sector, a paradigm-changing evolution of Deep Learning and AI is coming to benefit the need for manufacturing. But first, let's understand what we mean by Deep Learning and how hardware -- Cloud vs Edge -- plays such an important role. AI's generic name hides a variety of approaches that span from huge Artificial Intelligence models crunching data on a distributed cloud infrastructure, to tiny Edge-friendly AI that analyzes and mines data on small processors. Let's simplify the landscape and split AI into two main classes, the'heavy' and'light' types.