This New Tool Can Track the Environmental Cost of Your Machine Learning Model

Energy consumption is a major factor to plan for when implementing a long-term project or service that uses large-scale machine learning algorithms. Now, a team of researchers from Georgia Tech has created an interactive tool called EnergyVis that allows users to compare energy consumption across locations and against other models. "Sometimes, training machine learning models from end-to-end takes the same amount of energy as a transatlantic flight. Is every organization using machine learning able to budget for such an expense? What if the grid in which a business runs is running on coal versus green energy?" said Omar Shaikh, a computer science undergraduate student.