👉 Prepare computing is a specialized form of data preparation that involves the creation and optimization of datasets tailored for machine learning models, particularly those utilizing large language models (LLMs). This process includes tasks like data cleaning, augmentation, and encoding, with the goal of enhancing model performance by providing high-quality, relevant, and diverse input data. Prepare computing leverages techniques such as synthetic data generation, data augmentation through transformations like synonym replacement or back-translation, and the use of specialized tools to ensure that datasets are not only large but also well-structured and aligned with the model's intended use case, ultimately leading to more accurate and efficient LLMs.
