AI Use Case

Reduce data training set requirements

Reducing data training set requirements is a significant move towards lowering the cost and challenge of data deployment for modelling purposes, however it does have risks.

Function

Strategy

Data Science

Benefits

Cost - Reduced inventory costs,Data - Data enhancement

Case Studies

Fast.AI~Fast.AI more accurately classifies text while requiring less training data due to a new natural language processing technique,University College London~UCL researchers optimise generated training set data for use in machine learning to decrease data requirements and improve model robustness ,Baidu~Baidu researchers synthesise speech through neural voice cloning with limited data samples,Facebook~Facebook reduces time needed to support new queries to its internal reactive cache by using machine learning from weeks to minutes,Boston University~Researchers from Boston University improve automatic parameter selection for synthetic data creation,MIT~MIT researchers propose an efficient and accurate system for protecting privacy in healthcare datasets

Industry

Data Sets

Structured / Semi-structured,Audio

AI Technologies

Machine Learning (ML),ML Task - Prediction - Generation

Potential Vendors

fast.ai