Microsoft Technology Licensing, LLC

Sathish Kumar Manivannan

Cenk Ergan

Scott Joseph Counts

Reid Andersen

Chirag Deepakkumar Shah

Sujay Kumar Jauhar

Padma Varadharajan

Longqi Yang

Mengting Wan

Raymond Duane Parsons

Siddharth Suri

Jennifer Lynay Neville

Georg Ludwig Wilhelm Buscher

Tara Lynn Safavi

Keren Shushan

Xiaochuan Ni

Various embodiments discussed herein relate to prompting a model, such as a Large Language Model (LLM), to ingest natural language clustering instructions and generate corresponding natural language clustering information, such as a cluster description and/or a cluster label without the need to generate any numeric text embeddings.

Dataset clustering via language model prompts

A system for reporting and analyzing problems encountered by computer users. The system includes a recording tool executing on a user computer to capture a sequence of user interactions in the context of a graphical user interface. When a problem or other stop event is encountered, the tool generates a report indicating user interactions leading to the stop event, including information such as the specific sequence of controls for specific programs accessed by the user. The report can be analyzed to identify a sequence of user interactions characteristic of a problem type, which in turn may be used to find a solution for a particular user's problem. The system may also include a server that receives and analyzes reports from multiple computer users to identify patterns of user interactions that characterize problem types. This information may be used for associating specific problems with future reports or to improve products.

Problem reporting system based on user interface interactions

Growing community of inventors

Redmond, WA, United States of America

Sathish Kumar Manivannan