Speaker: Mrinal Karvir
Moderator: Lisha Chen
Abstract: As generative AI (GenAI) technologies advance, their impact on industries from healthcare to entertainment is undeniable, with a projected market value exceeding $110 billion by 2030. Gaining an understanding of GenAI solutions is crucial, not just for tech professionals but for anyone looking to stay relevant in an increasingly AI-driven world. We will walk through the core aspects of building GenAI solutions, covering foundational AI models, the art of prompt engineering, and the technical considerations for selecting Large Language Models (LLMs). Engaging in hands-on demonstrations will bring the technology to life. We will address significant challenges and risks, showcasing the dual-edged nature of these technologies. Ethical considerations will be at the forefront, emphasizing the necessity of responsible innovation. Through real-world examples, attendees will gain a clear understanding of GenAI’s potential and pitfalls, equipped to navigate and contribute responsibly to this rapidly evolving field.
Mrinal Karvir’s Bio:
As Senior AI Software Engineering Manager at Intel Corporation, Mrinal leads teams that develop innovative AI solutions. Her work has been recognized with innovation awards at CES and The Edge AI and Vision Alliance. As an Ethical AI Champion, she advocates for responsible AI practices through talks, panel discussions, and mentorship. She serves as Secretary and Board of Governors member for the IEEE Computer Society and is Vice Chair of IEEE Santa Clara Valley Women in Engineering. Mrinal is also an IEEE Distinguished Speaker on GenAI and Responsible AI. She frequently serves on judging panels and as a speaker at AI conferences. She has received the Pathfinder Award from Society of Women Engineers (SWE) for her professional achievements and community outreach and has been featured in the SWE “Women Engineers You Should Know” special section.
Lisha Chen’s Bio: Lisha Chen is a Ph.D. candidate in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI). She will join the Department of Electrical and Computer Engineering, University of Rochester in 2025 as a tenure-track Assistant Professor. Her research focuses on the theoretical foundations of multi-objective learning and meta learning, as well as their applications to machine vision and speech tasks.