This inventor holds 1 USPTO granted patent. Top assignee: Amazon Technologies, Inc.. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: The Innovations of Qiushi Wuye
Introduction
Qiushi Wuye is an accomplished inventor based in Seattle, WA. He is known for his contributions to the field of machine learning, particularly in the area of access restrictions for fine-tuning models. His innovative approach has garnered attention in the tech industry, especially through his work at Amazon Technologies, Inc.
Latest Patents
Qiushi Wuye holds a patent titled "Enforcing access restrictions for fine-tuning machine learning models." This patent addresses the enforcement of access restrictions when fine-tuning a machine learning model. The process involves receiving a request to fine-tune the model, which may be subject to provider and consumer access restrictions. The fine-tuning process ensures that both types of restrictions are adhered to, resulting in a tuned set of weights that can be combined with the trained model for improved inferences. He has 1 patent to his name.
Career Highlights
Throughout his career, Qiushi has made significant strides in the field of machine learning. His work at Amazon Technologies, Inc. has positioned him as a key player in developing innovative solutions that enhance the capabilities of machine learning models. His expertise in enforcing access restrictions has paved the way for more secure and efficient model fine-tuning processes.
Collaborations
Qiushi Wuye has collaborated with notable colleagues such as Arun Babu Nagarajan and Paras Mehra. These partnerships have contributed to the advancement of machine learning technologies and have fostered a collaborative environment for innovation.
Conclusion
In summary, Qiushi Wuye is a prominent inventor whose work in machine learning has led to significant advancements in the field. His patent on enforcing access restrictions showcases his innovative thinking and commitment to enhancing technology. His contributions continue to influence the landscape of machine learning and its applications.
