Power Is Limiting Machine Learning Deployments

The total amount of power consumed for machine learning tasks is staggering. Until a few years ago we did not have computers powerful enough to run many of the algorithms, but the repurposing of the GPU gave the industry the horsepower that it needed. The problem is that the GPU is not well suited to the task, and most of the power consumed is waste. While machine learning has provided many benefits, much bigger gains will come from pushing machine learning to the edge. To get there, power must be addressed. "You read about how datacenters may consume 5% of the energy today," says Ron Lowman, product marketing manager for Artificial Intelligence at Synopsys.