公开(公告)号：US20240330602A1

公开(公告)日：2024-10-03

申请号：US18194644

申请日：2023-04-02

申请人： Microsoft Technology Licensing, LLC

发明人： Linsey LAMBA ,  Hongmei LIU ,  Aarushi ARORA ,  Balaji SEETHARAMAN ,  Aakanksha Prithwi RAJ ,  Gokul Prasanth P ,  Jaiprakash SEKAR ,  Prasanna VENKATESAN ,  Rajesh K

IPC分类号： G06F40/47 ,  G06F40/253 ,  G06F40/55 ,  G06N3/0455 ,  G06N3/0895

CPC分类号： G06F40/47 ,  G06F40/253 ,  G06F40/55 ,  G06N3/0455 ,  G06N3/0895

摘要： A method for training a machine learning model using positive and negative synthetic data is implemented via a computing system including a processor. The method includes generating synthetic data using a generative pre-trained transformer bidirectional language model and self-supervising the generated synthetic data based on positive traits including rule-based criteria and/or model-based criteria. The method also includes generating a set of positive synthetic data labels with gradient scale rating based on the self-supervised synthetic data, synthesizing a set of negative synthetic data labels by self-supervising the positive synthetic data labels, and training a machine learning model using the set of positive synthetic data labels and the set of negative synthetic data labels. Another method further includes utilizing the trained machine learning model to generate Objectives and Key Results (OKRs) within the context of an enterprise application.