International Business Machines had 126 patents in future of work during Q1 2024. IBM Corp filed patents in Q1 2024 for a decision-improvement framework, integrating uncertainty quantifications into a long-term risk based calendar, intelligently assigning robotic edge devices to tasks, data transfer from legacy systems to modernized applications using Robotic Process Automation, and dynamically customizing meeting experiences based on user preferences. GlobalData’s report on International Business Machines gives a 360-degree view of the company including its patenting strategy. Buy the report here.

International Business Machines grant share with future of work as a theme is 49% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Machine learning-based decision framework for physical systems (Patent ID: US20240103457A1)

The patent filed by IBM describes a decision-improvement framework that involves obtaining regression functions to predict outputs of processes in a physical system, generating constraints and objective functions based on these regression functions and the system's representation, identifying parameter values to control the system, generating a score based on predicted improvements, and configuring the system based on the score meeting a threshold. The system uses machine learning to automatically generate regression functions and can update the model based on feedback signals, allowing for the identification of new parameter values if the score does not meet the threshold.

The framework utilizes a directed graph representation of the physical system, where processes are nodes and relationships are edges, potentially including cycles. The system is particularly applicable to manufacturing plants producing products, where parameter values specify configurations for each process. The method, system, and computer program product outlined in the patent aim to optimize decision-making processes by leveraging regression functions, constraints, and objective functions to improve the performance of physical systems based on historical data and predicted improvements.

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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.