Edge Machine Learning

Chris emphasizes the importance of machine learning at the edge, highlighting the common misconception that model deployment is straightforward. He warns against changing hardware midstream, as this can lead to significant reengineering costs. With the rapid increase in devices per capita, understanding edge deployment is crucial for future advancements in the field.