Innovations in Healthcare in the Age of Generative AI |
---|
The concept of artificial intelligence (AI) has undergone a significant transformation since the advent of ChatGPT in late 2022. What were once considered advanced AI technologies, including deep neural network training and inference, are now referred to as “conventional AI”‘conventional AI’. From a user's user’s perspective, conventional AI technology offers solutions to well-defined, specific problems. In contrast, generative AI can accomplish a broad range of tasks. Although the cost of training new generative AI models has become prohibitively expensive, limiting the field to a select few resource-rich entities, the threshold for innovation in generative AI is, in some respects, lower. Indeed, the locus of innovation in this new era has begun to shift towards the general user. Even those with limited knowledge of conventional AI now have the opportunity, and potentially the ability, to determine how to effectively apply the broad capabilities of generative AI to areas with which they are familiar with. Drawing from my experience in pharmaceutical R&D since late 2022, I will illustrate how generative AI has empowered is empowering every innovative mind. This forum will be taking place over zoom on 17 April 14:00 – 15:30 (GMT) / 09:00 -10:30 (EDT). |
Presenter | Bio |
---|---|
Dr. Junshui Ma, Merck Dr. Junshui Ma serves as an AVP and the Head of the Biometrics Research Department at Merck Research Lab. He obtained his Ph.D. from Ohio State University in 2001. Following his tenure at Los Alamos National Lab, a biotech startup, and the faculty at Ohio State University, he joined Merck in January 2005. Over the past 19 years, he has navigated the entire spectrum of pharmaceutical R&D. This includes preclinical discovery, clinical development, regulatory filing and approval, biomarker research, and translational medicine. A key area of his research is integrating AI and Machine Learning into pharmaceutical R&D, including recently spearheading the development and deployment of transformative generative AI applications. |