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AI Agents Vs Agentic AI - Paper Discussion | Audio | Duo | PODCAST | AI-Papers

Dive deep into the world of AI with our breakdown of the research paper "AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications, and Challenges" by Ranjan Sapkota, Konstantinos I. Roumeliotis, and Manoj Karkee. Published on May 15, 2025, this paper provides a crucial framework for understanding the rapidly evolving AI landscape. In this video, based solely on the paper's findings, we clarify the essential distinction between: AI Agents: Modular systems for specific tasks, evolving from generative AI. Agentic AI: More advanced systems involving multiple agents collaborating on complex goals. We explore: The historical roots of autonomous agents discussed in the paper. How the "ChatGPT era" accelerated the shift towards modern agents. The core characteristics and architecture of AI Agents (including the role of LLMs & LIMs). The conceptual leap and architectural enhancements of Agentic AI, enabling multi-agent collaboration and orchestration. Real-world applications for both AI Agents and Agentic AI systems, from customer support to robotic coordination and medical decision support. The significant challenges and limitations each paradigm faces, such as issues with causal understanding, coordination, predictability, and safety. The potential solutions and the future roadmap for developing more robust, scalable, and trustworthy agentic systems. If you want a clear, research-backed understanding of the difference between AI Agents and Agentic AI, and insights into where this technology is heading, this video summarizes a pivotal paper on the topic. Source Paper: "AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges" Authors: Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee arXiv Link: https://arxiv.org/abs/2505.10468