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楊子翔 - From no-code, low-code to full-code AI model DevOps: QOCA aim, an AI Medical Platform - 2024 Taiwan AI Academy Conf

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From no-code, low-code to full-code AI model DevOps: QOCA aim, an AI Medical Platform

Time / Place:

⏱️ 09/27 (Fri.) 16:00-16:30 at R2 - 2nd Conference Room

Abstract:

In recent years, the rapid development of artificial intelligence (AI) hardware and software technologies has made the development and utilization of data to train AI models a significant topic. Training AI models not only requires clean domain data and expertise but is also closely related to programming skills. Since AI models can be applied across various industries, familiarity with industry-specific knowledge is very important. This lecture will introduce Quanta Computer's AI Medical Platform (QOCA aim), showcasing how AI and IT experts collaborate with medical specialists from various fields to fast develop more AI models applicable to different industries. These AI models are then quickly integrated into business operations to help enhance efficiency and service quality across sectors.

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Biography:

楊子翔
  • 楊子翔 Robe Yang
  • Quanta Computer Inc. / BU12. Senior Director.
  • Dr. Robe Yang is Senior Director at Quanta Computer Inc, he joined Quanta in 2011 and was promoted to Senior Director in 2024. Since joining the company, he has held various roles including leading the development of hospital project collaborations for healthcare solutions and working as a senior engineer on the digital asset management system for a Japanese publishing company. Currently, Dr. Yang serves as the QOCA air product R&D director at Quanta, overseeing the development of cutting-edge AI solutions for smart medicine and industries.

    Dr. Yang holds a Ph.D. from the Department of Information Management at National Taiwan University. He served as an information engineer, systems network leader, and deputy director in National Taiwan University Hospital's information department. In this role, Dr. Yang was responsible for overseeing the hospital information system transformation project, which included the software system architecture and hardware solutions for migrating the information system from an IBM mainframe to an open systems architecture. This initiative allowed for a significant reduction in maintenance costs and improved operational efficiency. With an extensive background in healthcare information systems, containerized architecture, and cloud computing architecture, Dr. Yang’s research interests now focus on developing and implementing machine learning and deep learning DevOps solutions for smart medicine and various industries.

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