This AI technique could use a digital version of Earth to help fight climate change

There are applications for this in nearly every industry. For example, whereas once retailers could reasonably expect that past consumer behaviors would indicate future preferences, they now operate in a world where consumer purchase patterns and preferences evolve rapidly--all the more so as the COVID-19 pandemic repeatedly redefines life. Manufacturers and consumer-packaged-goods companies are under pressure to build dynamic supply chains that account for climate, political and societal shifts anywhere in the world at a moment's notice. Each of these challenges represents a complex and highly dynamic optimization problem, which, with the right data and feedback loops, is well suited for solving with reinforcement learning.