The Challenges of Pruning AI Models on the Edge

In this special guest feature, Nick Romano, CEO, Deeplite, discusses how struggling to fit advanced models in edge devices with limited resources forces deep learning teams to start “pruning” models – essentially trimming parts of it that are deemed not critical, but that also comes with a price: significantly reduced model accuracy. For the power of AI to be unleashed at the edge with full accuracy and the ability to run on devices with limited resources, there’s a need for AI optimization.