Patent · US Active

Platform for unsupervised machine learning training on unseeable user generated assets

US12153705B2 · kind B2 · utility

1Cited by

1References

9Claims

0Family size

Assignee

Adobe Inc. · US

Inventors

William Marino · New York, US
Tim Converse · San Francisco, US
Sudharshan reddy Kakumanu · Overland Park, US
Shabnam Ghadar · Menlo Park, US
Nico Becherer · Hamburg, DE
Dhaval K. Shah · Tankara, IN
Ben Bowles · Fremont, US
Alvin Ghouas · San Francisco, US
Alexander Riss · Hamburg, DE

Key dates

Filing date	Mar 30, 2021
Grant date	Nov 26, 2024
Priority date	—
Expiry date	Mar 19, 2042

Classification

Technology area (CPC G)Physics
CPC primaryG06N20/00
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

The present disclosure describes systems and methods for a privacy sensitive computing system. One or more embodiments provide a protected computing environment, a code authorization unit, and a data aggregation unit. For example, some embodiments of the privacy sensitive computing system may train unsupervised or self-supervised ML models on user-generated assets subject to privacy considerations that mandate those assets are not viewed directly by human eyes.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.