This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Microsoft Technology Licensing, LLC. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Innovations of Mario Emil Inchiosa in Adaptive Artificial Intelligence
Introduction
Mario Emil Inchiosa is an accomplished inventor based in San Francisco, CA. He has made significant contributions to the field of artificial intelligence, particularly in the area of three-dimensional object detection. His innovative approach utilizes synthetic training data to enhance the capabilities of machine learning models.
Latest Patents
Mario holds a patent for "Adaptive artificial intelligence for three-dimensional object detection using synthetic training data." This patent describes an adaptive AI model designed to detect specific items of interest within three-dimensional environments. The model is trained using a synthetically generated training set that is created in real-time during the training process. This training set includes a variety of images depicting containers filled with items of interest, allowing the model to learn effectively and accurately.
Career Highlights
Mario Emil Inchiosa is currently associated with Microsoft Technology Licensing, LLC, where he applies his expertise in artificial intelligence and machine learning. His work focuses on developing advanced technologies that improve object detection capabilities in various applications.
Collaborations
Mario collaborates with Matthew Anthony William Hyde, contributing to innovative projects within the realm of artificial intelligence and machine learning.
Conclusion
Mario Emil Inchiosa's work in adaptive artificial intelligence showcases his commitment to advancing technology through innovative solutions. His patent reflects a significant step forward in the field of three-dimensional object detection, demonstrating the potential of synthetic training data in machine learning applications.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
