This inventor holds 45 USPTO granted patents and 3 published patent applications and 8 EPO patents, primarily in Machine Learning Applications. Top assignees: Google Inc., Other. Active years: 1994-2026.
Location History:
- Norman, OK (US) (1994)
- Checotah, OK (US) (2005)
- Mountain View, CA (US) (2020 - 2021)
- San Fancisco, CA (US) (2023)
- San Francisco, CA (US) (2015 - 2024)
Company Filing History:
43 out of 33,862 
2 out of 834,350 Years Active: 1994-2026
Areas of Expertise:
Title: The Innovative Contributions of Thomas Price in Machine Learning
Introduction
Thomas Price is a prominent inventor based in San Francisco, CA, with an impressive portfolio that includes 41 patents. He is recognized for his groundbreaking work in the field of machine learning and its application to content distribution and user preferences. His efforts have significantly enhanced the way digital media is managed and consumed.
Latest Patents
Thomas Price's latest patents showcase his inventive spirit and dedication to advancing technology. One of his recent innovations involves assessing the accuracy of machine learning models. The patent outlines a method where a server balances content distribution between a machine learning model and a statistical model. By assigning request proportions to each group, the server can select content variations effectively, leading to improved performance based on acceptance rates for different variations. This approach helps in dynamically adjusting the audience share based on performance metrics.
Another notable patent focuses on using machine learning to determine user preferences regarding media transmissions. The invention involves generating training data that captures contextual information from user devices, enabling the model to identify preferences concerning canceling media streams. This innovative approach ensures a personalized experience for users, enhancing their overall interaction with media services.
Career Highlights
Throughout his career, Thomas Price has made significant contributions to the field of technology, particularly while working at Google Inc. His expertise in machine learning has positioned him as a key figure in developing innovative approaches that improve content delivery systems. His 41 patents reflect a commitment to driving the industry forward and showcasing the potential of machine learning applications.
Collaborations
Thomas has collaborated with several talented individuals, including Tuna Toksoz and Justin Lewis. Their joint efforts have led to advancements in technology that are shaping the future of content distribution and user experience. These collaborations underline the importance of teamwork in achieving groundbreaking innovations.
Conclusion
Thomas Price's work exemplifies the spirit of innovation that drives progress in technology. His contributions to the field of machine learning, particularly in balancing content selection between statistical models and machine learning models, have set new standards in the industry. With a string of patents to his name and meaningful collaborations with other innovators, Thomas continues to push the boundaries of what is possible in the realm of digital media and beyond.