公开(公告)号：US20250028995A1

公开(公告)日：2025-01-23

申请号：US18224889

申请日：2023-07-21

Applicant: X Development LLC

Inventor： Rishabh Singh ,  David Andre ,  Garrett Raymond Honke ,  Falak Shah ,  Nisarg Vyas ,  Jayendra Parmar ,  Brian M. Rosen ,  Shaili Trivedi

IPC: G06N20/00

Abstract: Disclosed implementations relate to adding “bottleneck” models to machine learning pipelines that already apply domain models to translate and/or transfer representations of high-level semantic concepts between domains. In various implementations, an initial representation in a first domain of a transition from an initial state of an environment to a goal state of the environment may be processed based on a pre-trained first domain encoder to generate a first embedding that semantically represents the transition. The first embedding may be processed based on one or more bottleneck models to generate a second embedding with fewer dimensions than the first embedding. In various implementations, the second embedding may be processed in various ways to train one or more of the bottleneck model(s) based on various different auxiliary loss functions.