Sisense Sf, Inc.

Openai Opco, LLC

Periscope Data Inc.

Ilge Akkaya

Steven Griffith

Jason Freidman

Audrey McGowan

Jeff Watts

Chris Tice

Jie Tang

Raul Gonzalez

Jeffrey Clune

Brandon Houghton

Adrien Ecoffet

Peter Zhokhov

Bowen Baker

Joost Huizanga

Joost Huizinga

Disclosed herein are methods, systems, and computer-readable media for training a machine learning model to label unlabeled data and/or perform automated actions. In an embodiment, a method comprises receiving unlabeled digital video data, generating pseudo-labels for the unlabeled digital video data, the generating comprising receiving labeled digital video data, training an inverse dynamics model (IDM) using the labeled digital video data, and generating at least one pseudo-label for the unlabeled digital video data, wherein the at least one pseudo-label is based on a prediction, generated by the IDM, of one or more actions that mimic at least one timestep of the unlabeled digital video data. In some embodiments, the method further comprises adding the at least one pseudo-label to the unlabeled digital video data and further training the IDM or a machine learning model using the pseudo-labeled digital video data.

Using machine learning to train and use a model to perform automatic interface actions based on video and input datasets

In an embodiment, a query system sends compact code to a database service for expansion of the compact code to partially-expanded code and expanded code. In an embodiment, a hash value is generated based on the partially-expanded code and indexed in memory with the expanded code. In an embodiment, a hash value is received as part of a command and expanded code is identified based on the hash value and sent to a database service.

Method for automated query language expansion and indexing

Growing community of inventors

Palo Alto, CA, United States of America

Ilge Akkaya