NVIDIA had 290 patents in artificial intelligence during Q1 2024. NVIDIA Corp filed patents in Q1 2024 for techniques to remove unintended variations in data, calibrate interior depth sensors and image sensors for in-cabin monitoring, process image frames using neural networks, control robots using machine learning models, and generate realistic motion in images using neural networks. GlobalData’s report on NVIDIA gives a 360-degree view of the company including its patenting strategy. Buy the report here.

NVIDIA grant share with artificial intelligence as a theme is 29% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Neural network-based perturbation removal (Patent ID: US20240104698A1)

The patent filed by NVIDIA Corp. describes a method and system for removing unintended variations introduced into data by generating a first image of an object based on adding noise to, and then removing the noise from, a second image of the object. The system involves using neural networks, specifically a diffusion network, to iteratively add and remove noise to reduce adversarial perturbations in the second image while retaining semantic structure to ensure correct classification by a classifier.

The processor, system, method, machine-readable medium, and image generation system outlined in the patent claims all focus on the generation of images with reduced unintended variations through the addition and removal of noise. By utilizing neural networks and a stochastic diffusion equation, the technology aims to enhance image quality by minimizing adversarial perturbations while preserving semantic content. The iterative process of adding and removing noise through forward and reverse iterations ensures that the generated first image maintains a high probability of being correctly classified by a classifier. This innovation has the potential to improve image processing tasks in various applications, particularly in scenarios where data integrity and classification accuracy are critical.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.