👉 Trained computing refers to the process of using large neural networks, typically deep learning models, that have been extensively trained on vast datasets to perform specific tasks with high accuracy. This training involves feeding the model enormous amounts of data, allowing it to learn patterns, relationships, and features within the data. Through this iterative process, the model adjusts its internal parameters to minimize prediction errors, effectively becoming adept at tasks such as image recognition, natural language processing, or predictive analytics. Once trained, these models can be deployed to make predictions or decisions on new, unseen data with remarkable precision, leveraging the learned knowledge without needing explicit programming for each specific task.
