Agentic AI: Learning Iteratively, Acting Autonomously

This presentation provides an in-depth analysis of the architectures underpinning agentic AI, explores the cutting-edge technologies enabling their capabilities, and delves into their practical applications. Dr. Fatma Tarlaci discusses how AI agents, built on sophisticated machine learning models, can process and respond to dynamic data inputs in real-time. Unlike traditional LLMs, agentic AI introduces an iterative, dynamic workflow involving planning, data gathering, drafting, assessment, and revision, mirroring human learning for improved outcomes. The talk also addresses key challenges such as scalability and ethical considerations, while exploring future directions and the potential of AI agents to transform industries. The speaker, CTO at Rastegar Capital and former researcher at OpenAI, shares insights from her practical experience and research, highlighting advancements in software development, investment, and other sectors.