USPTO Patent Application for AI Content Analysis System

ChangeBridge: Patent Apps - Business Methods (G06Q)

Detected March 26th, 2026

Summary

The USPTO has published a patent application (US20260087516A1) detailing a system for analyzing screen-recorded user content using on-device AI. The application focuses on privacy-preserving processing of digital advertisements and AI-generated media.

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What changed

This document is a published patent application from the USPTO, specifically application number US20260087516A1, titled "SYSTEMS AND METHODS FOR CAPTURING AND PROCESSING SCREEN-RECORDED USER-SPECIFIC RECOMMENDED OUTPUT, DIGITAL ADVERTISEMENTS, AND AI-GENERATED MIXED MEDIA." The application describes a method for analyzing screen-recorded content using on-device computer vision and generative AI, with a focus on privacy-preserving processing and efficient transmission of metadata. It outlines a system that captures user content, processes it using CLIP-style embeddings and OCR, flags advertisements and content similarities, and generates metadata summaries via a compact generative AI model before transmitting to a cloud system while deleting raw media.

As this is a patent application, it does not impose direct regulatory obligations or compliance deadlines on entities. However, it signals potential future technological developments and intellectual property claims in the area of AI-driven content analysis and privacy-preserving media processing. Companies operating in the digital advertising, content recommendation, and AI sectors should be aware of this application as it may influence future product development, licensing, or patent landscape considerations.

Source document (simplified)

← USPTO Patent Applications

SYSTEMS AND METHODS FOR CAPTURING AND PROCESSING SCREEN-RECORDED USER-SPECIFIC RECOMMENDED OUTPUT, DIGITAL ADVERTISEMENTS, AND AI-GENERATED MIXED MEDIA

Application US20260087516A1 Kind: A1 Mar 26, 2026

Inventors

MANH NGUYEN, BRICE GOWER, AKASH CHOUDHARY, ETHAN CABRAL, MENGSHU NIE, ANNE-MARIE MULUMBA, WASALA Rankothge Waruna Gayan KULAWANSHA, JOSEPH ALBI, SAACHI BAGDE, HO SHING KWONG, Kareem Rahaman, Akash Sidhu, Amir Ali Vahid Kassiri

Abstract

A system and method for analyzing screen-recorded personalized digital content using on-device computer vision and generative AI. A user captures content from a recommender system interface, such as screen activity or browser-rendered content, optionally with concurrent voice commentary. On-device processing generates intermediate representations using CLIP-style embeddings, OCR text, and transcribed audio tokens, flagging advertisements, changes in content, diversity in content, and similarities in content. A compact generative AI model produces metadata summaries, which users may annotate with tags or comments. A composite metadata package is transmitted to a cloud system, while raw media is deleted. The invention enables privacy-preserving, bandwidth-efficient insight into recommender-based media and user feedback.