This "Aha moment" in the DeepSeek-R1 paper is huge: Pure reinforcement learning (RL) enables an LLM to automatically learn to think and reflect. This challenges the prior belief that replicating OpenAI's o1 reasoning models requires extensive CoT data. It turns out you just need to give it the right incentives. We are so back in the AlphaGo excitement era: by playing countless Go games and maximizing the reward function (winning the game) using pure RL, AlphaGo beat the best human players. Now we are entering the LLM RL era. 2025 could be the year of RL.