The text highlights several applications of reinforcement learning (RL) across various domains, including recommender systems, games, production planning, and more. RL is being used to optimize traffic control policies, improve gaming bots' performance, boost wind farm energy production, provide counterfactual explanations for loan decisions, and streamline production scheduling. The Ray Summit conference will feature sessions on these topics, as well as updates on the RLlib library, which is being developed to make RL more accessible and performant for various use cases. Industry leaders are already leveraging RLlib in production across different verticals, and newcomers can attend training sessions to learn more about RL and RLlib.