The field of artificial intelligence is witnessing a significant shift towards agentic AI, characterized by autonomy, goal-driven behavior, and multi-agent collaboration. This trend is transforming various aspects of research and industry, including scientific discovery, product management, and manufacturing. Agentic AI is enabling the automation of complex tasks, such as research workflows, and is poised to revolutionize the way we approach problem-solving. The integration of large language models and generative AI is further accelerating this transformation, allowing for more efficient and effective decision-making. Noteworthy papers in this area include:

• Innovative Research on IoT Architecture and Robotic Operating Platforms, which introduces a novel design for robotic operating platforms underpinned by a transformative Internet of Things architecture.
• URSA, which presents a scientific agent ecosystem for accelerating research tasks and highlights the potential of the system.
• Agent4S, which proposes a five-level classification for Agent4S, outlining a clear roadmap from simple task automation to fully autonomous, collaborative AI Scientists.
• State and Memory is All You Need for Robust and Reliable AI Agents, which introduces SciBORG, a modular agentic framework that allows LLM-based agents to autonomously plan, reason, and achieve robust and reliable domain-specific task execution.