Home > Storage > PowerScale (Isilon) > Product Documentation > Storage (general) > PowerScale All-Flash F210, F710 & F910 > Preprocessing Unstructured data
Preprocessing unstructured data for generative AI is a crucial step that involves preparing the raw data for use in training AI models. This process includes several tasks such as cleaning, normalizing, and transforming the data into a format that the AI can understand and learn from. The goal is to enhance the quality and structure of the data to improve the performance of generative models. This can involve removing noise, handling missing values, labeling data for supervised learning, and augmenting the dataset to increase its size and diversity. By doing so, the AI models can generate more accurate and coherent outputs.