Artificial intelligence is on the cusp of a significant evolution, moving beyond helpful chatbots and insightful reasoners towards truly autonomous agents capable of tackling complex tasks with minimal human intervention. While current methods rely heavily on meticulously engineered pipelines and prompt tuning, a growing consensus suggests that reinforcement learning (RL) will be the key to unlocking the next level of AI agency. Will Brown, a Machine Learning Researcher at Morgan Stanley, recently shared his perspective on this transformative trend, highlighting the potential of RL to imbue AI systems with the ability to learn and improve through trial and error. Today's advanced Large Language Models (LLMs) excel as chatbots, engaging in conversational interactions, and as reasoners, adept at question answering and interactive problem-solving. Models like OpenAI's O1, O3, and the recently unveiled Grok-1 and Gemini demonstrate remarkable capabilities in longer-form thinking...