In <2 years, AES built out a global team, its underlying infrastructure, and they’ve built and deployed 50+ models to date. Today, AES models optimize liquid gas shipping and logistics, predict when power generation equipment will need maintenance, guide fintech energy trades, make hydrology predictions, inform bids on power generation facilities, provide weather forecasting for utilities, and more. Their cloud infrastructure supports the diverse needs of data scientists, giving them access to compute resources (including NVIDIA Tesla) and tools (including SAS Viya and H2O) within a centralized Domino Data Lab platform for MLOps.
Speaker: Sean Otto - Director of Analytics, AES Corporation