Large language models (LLMs) like ChatGPT are impressive, but they still make mistakes. Imagine an AI that could catch and fix its own errors, learning from them in the process. That's the promise of a new technique called Internalized Self-Correction (InSeC). Researchers are exploring how to build this self-critiquing ability directly into the training process of LLMs. Instead of relying solely on external feedback, InSeC allows the model to generate both correct and incorrect answers, then identify and correct the mistakes. This approach, similar to how we learn from our own errors, could lead to more efficient learning and better overall performance. Think of it like having a built-in editor that constantly refines the AI’s responses. In early tests, InSeC-trained models showed a remarkable ability to self-correct, catching factual errors and even correcting illogical reasoning. This has exciting implications for the future of AI. Imagine LLMs that are less prone to hallucinations and more reliable in their responses. While this research is still in its early stages, it offers a glimpse into how future AIs might learn and evolve, ultimately becoming more accurate and trustworthy.