AI System for Generating Computer Bills of Materials Using GANs

ChangeBridge: Patent Grants - AI & Computing (G06N)

Published March 31st, 2026

Detected March 31st, 2026

Summary

The USPTO granted patent US12591774B2 to Dell Products L.P. covering a system that uses generative adversarial networks (GANs) to automatically generate computer bills of materials based on functional requirements. The patent (20 claims) was filed on July 13, 2022, under application number 17812272. Inventors include Rachna Lalwani, Owen Martin, and Arieh Don.

View original document View source feed page

What changed

USPTO granted patent US12591774B2 to Dell Products L.P. for an AI system that trains generator and discriminator neural networks to create and validate computer bills of materials from functional requirements. The generator produces bills of materials while the discriminator evaluates whether they satisfy specified requirements. The system outputs and stores validated bills of materials.

This patent grant is informational and does not impose compliance obligations on other entities. Companies developing AI systems for infrastructure ordering or manufacturing planning may want to review the claims to ensure their products do not infringe. The patent has CPC classifications G06Q 10/0875 (inventory management) and G06N 3/08 (neural networks).

Source document (simplified)

← USPTO Patent Grants

Ordering infrastructure using application terms

Grant US12591774B2 Kind: B2 Mar 31, 2026

Assignee

Dell Products L.P.

Inventors

Rachna Lalwani, Owen Martin, Arieh Don

Abstract

A system can train a generator neural network to produce a trained generator neural network of a generative adversarial network, wherein the trained generator neural network is configured to output a bill of materials in response to receiving functional requirements for a computer system. The system can train a discriminator neural network to produce a trained discriminator neural network of the generative adversarial network, wherein the trained discriminator neural network is configured to output whether the bill of materials received from the trained generator neural network satisfies the functional requirements for the computer system. The system can produce an output bill of materials from the generative adversarial network based on the functional requirements. The system can store the output bill of materials in the system.