Presentation
Edge Intelligence & GenAI: Exploring Challenges and Ethics
DescriptionThe convergence of the Internet of Things (IoT), Heterogeneous Computing Architectures, Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) is ushering in a new era of computation and analysis. Our panelists will explore a deeper understanding of the intricate interplay between Edge Intelligence and GenAI, with a focus on the technical hurdles and ethical considerations.
By processing data closer to its source, edge computing can harness the power of AI-ML in real-time. This paradigm shift is redefining the capabilities of IoT and computational architectures. Join us as we explore the practical challenges involved in integrating GenAI into edge computing such as limited computational resources, latency reduction, and the development of lightweight AI models.
Edge computing, fortified by GenAI, is changing the game in critical sectors like healthcare, manufacturing, automotive, smart cities, and semiconductor design and manufacturing. Real-time data processing is enhancing decision-making, improving efficiency, and even saving lives. Through case studies and examples, we'll discuss how engineers and researchers are at the forefront of developing solutions that drive these innovations.
While the technical aspects are fascinating, with great power comes great responsibility. The ubiquity of edge computing and GenAI raises crucial ethical questions. How can we ensure data privacy and security at the edge? What safeguards can be put in place to mitigate bias in AI algorithms? Who is accountable when autonomous systems make critical decisions?
Our panel comprises seasoned experts who have grappled with these questions in academic research, policy making, product and infrastructure design and deployment as well as investing and mentoring. We invite you to be a part of the conversation that is shaping the future of technology.
By processing data closer to its source, edge computing can harness the power of AI-ML in real-time. This paradigm shift is redefining the capabilities of IoT and computational architectures. Join us as we explore the practical challenges involved in integrating GenAI into edge computing such as limited computational resources, latency reduction, and the development of lightweight AI models.
Edge computing, fortified by GenAI, is changing the game in critical sectors like healthcare, manufacturing, automotive, smart cities, and semiconductor design and manufacturing. Real-time data processing is enhancing decision-making, improving efficiency, and even saving lives. Through case studies and examples, we'll discuss how engineers and researchers are at the forefront of developing solutions that drive these innovations.
While the technical aspects are fascinating, with great power comes great responsibility. The ubiquity of edge computing and GenAI raises crucial ethical questions. How can we ensure data privacy and security at the edge? What safeguards can be put in place to mitigate bias in AI algorithms? Who is accountable when autonomous systems make critical decisions?
Our panel comprises seasoned experts who have grappled with these questions in academic research, policy making, product and infrastructure design and deployment as well as investing and mentoring. We invite you to be a part of the conversation that is shaping the future of technology.
Event Type
Embedded Systems and Software
TimeWednesday, June 2610:30am - 12:00pm PDT
Location2012, 2nd Floor
AI
Embedded Systems
Engineering Tracks