Explosive growth in AI compute shows enterprises must get smart about strategy

Artificial intelligence research organization OpenAI recently released a report that shows the amount of compute power needed for training runs in the largest machine learning systems has increased by 300,000 times since 2012. Because machine learning results improve when given additional computing resources, we'll likely see even greater demands for silicon infrastructure to drive better results. Enterprises are increasingly using machine learning to automate complex problems and analytical tasks. But OpenAI's research shows there's a key challenge ahead: How can enterprises build the infrastructure they need to produce the business results they want when the technical requirements keep changing? First off, enterprises should try to find the least complicated algorithm necessary to solve the business problem at hand.