Service feasibility assessment and monitoring for initial ai model handling

Abstract

Embodiments of the present application provide a method, apparatus, and computer readable medium for evaluating service feasibility of AI models training on a global dataset. At least one AI model, data requirements for the AI model, and a target training accuracy performance indicator for the AI model when trained are received from a user. Relevant data is determined from a global dataset, the relevant data is based on the received data requirements. A training accuracy estimation module is used to calculate a model score for the AI model based on the relevant data, the model score representing an estimated training accuracy to which the AI model can be trained. Based on the model score, it is determined whether the target training accuracy performance indicator can be satisfied. When the target training accuracy performance indicator can be satisfied, the at least one AI model is communicated to a model training environment.

Dependencies are inferred from the claim text.