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
Potential Vendors
fast.ai
Industry
Data Sets
Structured / Semi-structured,Audio
AI Technologies
Machine Learning (ML),ML Task - Prediction - Generation