Mr. Aravind Nuthalapati

Synthetic Data and Gen AI: Transforming Privacy and Innovation

Abstract:

Synthetic data has emerged as a groundbreaking solution to address the growing concerns around data privacy, regulatory compliance, and limited data availability in artificial intelligence. This session explores synthetic data’s transformative role in enabling organizations to safely innovate while preserving privacy. We’ll discuss key generation techniques—ranging from traditional statistical approaches to advanced generative AI methods such as Generative Adversarial Networks (GANs). Real-world applications across healthcare, finance, and autonomous vehicles demonstrate synthetic data's practical impact, highlighting significant benefits, including cost efficiency, accelerated AI training, and compliance adherence. Yet, synthetic data presents unique challenges related to data realism, validation complexities, and ethical considerations. Leveraging insights from industry practices, including cloud-native solutions, attendees will gain strategic perspectives on balancing innovation and privacy. Join this session to discover how synthetic data is shaping the future of ethical and efficient AI-driven innovation.