USPTO Patent Grant: Personalized Content Generation Using AI

ChangeBridge: Patent Grants - Business Methods (G06Q)

Published March 24th, 2026

Detected March 25th, 2026

Summary

The USPTO has granted Verizon Patent and Licensing Inc. a patent for systems and methods for generating personalized content using AI language models and reinforcement techniques. The patent, US12586081B2, was filed on December 18, 2023, and is effective March 24, 2026.

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What changed

The United States Patent and Trademark Office (USPTO) has issued patent US12586081B2 to Verizon Patent and Licensing Inc. This patent covers systems and methods for generating personalized content using a language model and reinforcement techniques. The technology involves receiving user activity and content data to generate custom embeddings, predict user intent and next actions, and ultimately create personalized documents based on these insights.

This patent grant is primarily an intellectual property matter and does not impose direct regulatory obligations on businesses. However, companies developing or utilizing AI for personalized content generation, particularly those in the technology sector, should be aware of this patented technology. It may influence future product development, licensing agreements, or potential infringement considerations within the business methods and AI application space.

Source document (simplified)

← USPTO Patent Grants

Systems and methods for generating personalized content using a language model and reinforcement techniques

Grant US12586081B2 Kind: B2 Mar 24, 2026

Assignee

Verizon Patent and Licensing Inc.

Inventors

Dheeraj Singh, Durgesh Kumar, Miruna Jayakrishnasamy, Saurabh Tahiliani

Abstract

A device may receive user activity data identifying activities of a user, and content data identifying text transcripts associated with the user. The device may generate a first custom embedding associated with the user based on the user activity data, and may process the first custom embedding, with a machine learning model, to generate an intent of the user and a next action for the user based on the intent. The device may process the content data to generate a second custom embedding for the user and an end user vector based on the second custom embedding, and may generate a document vector for the user based on the next action for the user. The device may process the document vector and the end user vector, with a language model, to generate a document for the user, and may perform one or more actions based on the document.