Large language models (LLMs) are impressive, but their tendency to sometimes generate toxic or harmful content raises serious concerns. Researchers are constantly working on ways to make these powerful AI tools safer, and a new technique called Precision Knowledge Editing (PKE) offers a promising solution. Imagine being able to precisely edit an AI's knowledge, correcting its flaws without affecting its overall capabilities. That's the core idea behind PKE. Instead of retraining the entire model, which can be computationally expensive and time-consuming, PKE focuses on identifying and modifying the specific parts of the model responsible for generating toxic outputs. This method builds on previous work but introduces a more nuanced approach, allowing for a more targeted intervention. The method uses clever mathematical formulations to pinpoint the problematic areas within the model, which are the neuronal connections or weights that make the AI produce toxic text. The algorithm traces the activation paths of these neurons and their respective weight changes and identifies the most significant modifications, marking them as probable sources of harmful content. Then, a custom loss function is applied which ensures a balance between reduced toxicity and maintaining the correctness of the model’s outputs. Essentially, PKE tweaks the problematic connections to nudge the AI away from harmful outputs while ensuring it doesn’t lose its overall knowledge or start generating nonsensical text. In tests, PKE significantly reduced the success rate of attacks aimed at triggering harmful outputs across several LLM architectures, including Llama2-7b and Llama-3-8b-instruct. Remarkably, this improvement in safety didn't come at the expense of performance – the models retained their ability to perform general tasks effectively. This research is a significant step towards making LLMs more reliable and suitable for real-world applications. While PKE mainly focuses on text-based attacks, future research could explore its potential for addressing other issues like bias or factual inaccuracies. As LLMs become increasingly integrated into our lives, precision editing techniques like PKE will be crucial for ensuring their responsible and beneficial use.