USPTO Patent Grant for ML-Based AR Output Generation by Dell

ChangeBridge: Patent Grants - AI & Computing (G06N)

Published March 24th, 2026

Detected March 25th, 2026

Summary

The USPTO has granted Dell Products L.P. patent US12586263B2 for a machine learning-based system to generate outputs in augmented reality environments. The patent covers an apparatus that uses multiple machine learning models to process input components and generate relevant output responses for users in AR.

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What changed

The United States Patent and Trademark Office (USPTO) has issued patent US12586263B2 to Dell Products L.P. This patent details an apparatus that utilizes three distinct machine learning models to generate outputs within augmented reality (AR) environments. The system processes input components from the AR environment, determines their relevance, and generates an output response presented to the user.

This patent grant signifies a new intellectual property protection for Dell's technology in the AI and AR space. While not a regulatory rule imposing obligations on other entities, it establishes patent rights that could influence future product development and licensing within the technology sector. Compliance officers in technology companies should be aware of this patent as it relates to their own AI and AR development efforts, particularly concerning potential infringement risks or opportunities for licensing.

Source document (simplified)

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Machine learning-based generation of outputs in augmented reality environments

Grant US12586263B2 Kind: B2 Mar 24, 2026

Assignee

Dell Products L.P.

Inventors

Zijia Wang, Jiacheng Ni, Zhen Jia

Abstract

An apparatus comprises at least one processing device configured to generate, using a first machine learning model, a first data structure comprising input representations of one or more input components from an augmented reality environment. The at least one processing device is also configured to generate, using a second machine learning model that takes as input at least a portion of the first data structure, a second data structure comprising at least one vector representation characterizing relevance of one or more of the input representations in the first data structure. The at least one processing device is further configured to generate, using a third machine learning model that takes as input at least a portion of the first data structure and at least a portion of the second data structure, an output response, and to present the output response to a user in the augmented reality environment.