Rohith Venkata Sai Kumar Potladurthy
Rohith Venkata Sai Kumar Potladurthy
Software Enginner, St Louis, Mo
The Rise of Cognitive AI: From Generative Models to Autonomous Decision Intelligence
AI is moving to a new stage where systems are no longer just about creating content, but about cognitive functions, such as reasoning, planning, learning and decision making. Generative AI has revolutionized the way people produce and engage with information, but the next step is for intelligent systems to demonstrate capabilities of Cognitive AI: understanding context, adapting to new environments, working with humans, and making decisions with minimal supervision. This keynote explores the evolution of AI from traditional machine learning and deep learning to generative AI and the emergence of Cognitive AI. It features technologies that are inciting this shift such as large language models, retrieval-augmented generation, knowledge graphs, multimodal learning, long-term memory, reasoning frameworks, and autonomous AI agents. These advances are facilitating the transition of AI systems from questions to solutions of complex real-world problems. The session also explores the impact of Cognitive AI in industries like finance, healthcare, manufacturing, education and smart enterprises, and how it is helping to make decisions smarter and automating sophisticated workflows and processes to make them more efficient and to complement human expertise. Alongside these opportunities, the keynote addresses key challenges related to reliability, explainability, security, governance, ethical AI, and human oversight, emphasizing the importance of building AI systems that are trustworthy, transparent, and aligned with organizational goals. This keynote will bring together insights from cutting-edge AI research and will give the audience a glimpse into the future of intelligent systems and how Cognitive AI will shape them in the next decade or so, from an enterprise perspective. It concludes by outlining future research directions and the skills, architectures, and governance frameworks needed to develop autonomous decision intelligence that delivers meaningful value while maintaining human trust and accountability.