Good things happen if you can put artificial intelligence at the network edge. Pushing AI to the edge means a lot of the processing resources have to be right there at the edge too. That almost always means machine learning, but doing ML at the edge isn’t easy. It requires a nearly perfect balance of performance and minimal energy consumption to make it feasible at an affordable price. Arm’s ML strikes that balance, paving the way for the spread of AI-based applications.