NVIDIA had 88 patents in robotics during Q4 2023. NVIDIA Corp filed patents in Q4 2023 for methods to detect inefficiencies in workloads, improve photorealistic image synthesis using Monte Carlo methods, utilize robots to resolve errors in data center equipment, predict errors in processing units using machine learning, and classify audio alerts of emergency response vehicles using deep neural networks. GlobalData’s report on NVIDIA gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

NVIDIA grant share with robotics as a theme is 34% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Detecting and optimizing program workload inefficiencies at runtime (Patent ID: US20230418726A1)

The patent filed by NVIDIA Corp. describes methods and systems for identifying potential inefficiencies in workloads by comparing information obtained during execution to a set of inefficiency patterns. The system can automatically select a workload, detect inefficiencies, determine actions to address them, and provide performance improvement suggestions to users. It can also use machine learning to determine actions and automatically implement them, potentially before the execution completes. The system can produce modified workloads to address inefficiencies and prioritize actions based on the severity of the inefficiency patterns.

Furthermore, the patent outlines a processor with neural networks that can identify potential inefficiencies in workload execution based on information obtained and predefined inefficiency patterns. The processor can import performance analyzer instructions into workload instructions, patch instructions to operations, and perform static analysis or telemetry measurements to analyze hardware components. It can automatically implement actions to improve inefficiencies, providing a comprehensive solution for optimizing workload performance within specific hardware and software domains.

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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.