Cars Require Regular Inspection, Why Should AI Models Be any Different?

Like the development of a car model (say, electrical cars), developing AI models is a costly and time-consuming process. The lifecycle of an AI model can be divided into two phases: training and deployment. The training phase includes data collection and pre-processing, model selection (e.g., architecture search and design), hyperparameter tuning, model parameter optimization, and validation. AI model training can be quite expensive, especially when it comes to the training of foundation models4 that require pre-training on large-scale datasets with neural networks consisting of a gigantic size of trainable parameters. Take the Generative Pre-trained Transformer 3 (GPT-3)5 as an example, which is one of the largest languages models ever trained to date.