Large Language Models (LLMs) gain their power through two distinct phases of learning: pre-training and fine-tuning. Understanding the difference between these processes is fundamental to building effective AI applications.
Agentic Reinforcement Learning (Agentic RL): A Technical Overview Overview Agentic Reinforcement Learning (Agentic RL) is a paradigm that uses reinforcement learning to train Large Language Models (LLMs) to function as autonomous, decision-making agents. This approach moves beyond simply aligning an LLM’s text output with human preferences and instead teaches it to perform multi-step tasks, use