Company Filing History:
Years Active: 2020
Title: Inventor Hao Du: Pioneering Mixed Intelligence Data Labeling Systems
Introduction: Hao Du, an inventive mind based in Campbell, California, has made significant strides in the realm of machine learning. With a sole patent to his name, Hao's contributions focus on enhancing data labeling techniques, which are crucial in training robust machine learning systems.
Latest Patents: Hao Du holds a patent for a "Mixed Intelligence Data Labeling System for Machine Learning." This innovative method presents a hybrid approach to data labeling that involves several steps. It starts with the receipt of multiple unlabeled objects forming an unlabeled data set. A machine learning system pre-labels this data set, creating a pending label data pool. The system then bifurcates this pool into high and low confidence sets. The high confidence set is dispatched to a machine labeler, while the low confidence set is sent to a human labeler. After merging these label sets, a pre-review label data pool is generated, and any discrepancies between this pool and the pending label data pool are assessed. If the difference exceeds a predefined error threshold, the data objects undergo review labeling, ultimately ensuring high-quality labeled data.
Career Highlights: Hao Du is a key player at Black Sesame International Holding Limited, where he has been instrumental in researching and developing innovative machine learning technologies. His expertise in data labeling is reflected in his patent, which aims to streamline the labeling process and enhance the reliability of machine learning models.
Collaborations: Throughout his career, Hao has collaborated with talented peers, including Mengting Tsai and Guan Wang. This teamwork fosters innovation and drives projects that push the boundaries of machine learning applications.
Conclusion: Hao Du's work represents a significant contribution to the field of machine learning, particularly in data labeling methodologies. His patented mixed intelligence data labeling system showcases a unique blend of automation and human insight, helping to advance the capabilities of machine learning systems and pave the way for future innovations.