AI Agents: The Intelligent Revolution
Abstract: AI agents are autonomous systems designed to perform tasks intelligently and independently. In this talk, we'll explore their journey from basic systems to sophisticated entities capable of perception, reasoning, learning, and action. We'll dive into the foundational components of AI agents, the different types of agents, and their practical applications across fields like robotics, gaming, virtual assistants, and autonomous vehicles.
AI agents can be categorized by capability—reactive, model-based, goal-oriented, and learning agents. We'll look at how they are applied in robotics, gaming, recommender systems, and more. Beyond that, we'll touch on specialized topics like agent-oriented programming, multi-agent systems, and agent-based modeling, showing how these approaches help us design complex, interactive systems.
We'll also discuss ethical considerations like bias, transparency, safety, and workforce impacts, emphasizing the importance of responsible AI development. Finally, we’ll look at where AI agents are headed, highlighting innovations that could reshape industries and foster better collaboration between humans and AI.
This talk aims to provide a clear and comprehensive understanding of AI agents and their role in building a smarter, more efficient, and equitable future.
Biography: Dr. Spandan Mishra is an accomplished AI/ML leader with over a decade of experience in developing cutting-edge machine learning solutions and data-driven strategies. Currently serving as an AI Tech Lead Manager at Palo Alto Networks, Dr. Mishra specializes in leveraging advanced AI techniques, such as reinforcement learning and large language models, to drive innovation in cybersecurity and enterprise applications. His recent work includes leading R&D initiatives to build agentic frameworks, and creating conversational AI systems that enhance user experience.
Dr. Mishra holds a Ph.D. in Industrial Engineering and Applied Statistics from Florida State University, where his research focused on statistical learning and damage detection methodologies.
Throughout his career, he has collaborated with government agencies, global organizations, and interdisciplinary teams to solve complex problems using AI. With a strong commitment to responsible AI development, he continues to push the boundaries of technology while mentoring future leaders in the field.