\n ## Diagram: Agentic Intelligence Evolution ### Overview This diagram illustrates the evolution of agentic intelligence, starting from Large Language Models (LLMs) and progressing towards next-generation agentic intelligence. It depicts the stages of foundation agents, self-evolving agents, and a future state represented by a question mark, alongside the increasing level of intelligence. The diagram uses arrows to show the flow of development and influence between different components. ### Components/Axes The diagram is structured horizontally, representing a progression. Key components include: * **LLMs (Language Understanding & Generation):** Located on the left, serving as the base. * **Foundation Agents:** Situated to the right of LLMs, representing the next stage. * **Self-evolving Agents:** Positioned further to the right, building upon foundation agents. * **Next-generation Agentic Intelligence:** Represented by a purple box with question marks, indicating a future state. * **Level of Intelligence:** A vertical axis on the right, with an upward arrow indicating increasing intelligence. * **Planning, Tool Calling, Workflow Construction:** Listed vertically on the left, representing capabilities. * **Learning & Evolution Mechanisms:** Listed vertically in the center, representing processes. Specific agents/models mentioned: * GPT-4 * Claude-4 * DeepSeek-R1 * smolagents * Manus * ChatGPT agent * Alta * Gödel agent ### Detailed Analysis or Content Details The diagram shows a flow from LLMs to Foundation Agents, then to Self-evolving Agents, and finally to Next-generation Agentic Intelligence. * **LLMs:** Represented by a green rounded rectangle labeled "LLMs" and "Language Understanding & Generation". Below this are listed specific LLMs: GPT-4 (green), Claude-4 (orange), DeepSeek-R1 (blue). A "..." indicates more LLMs exist. A small robot icon is positioned to the right of the LLM block. * **Foundation Agents:** A blue rectangle labeled "Foundation Agents" and "Execution via Tools & Planning". A robot icon is positioned to the right of this block. The agents listed as contributing to this stage are: ChatGPT agent (green), smolagents (yellow), Manus (teal). * **Self-evolving Agents:** A yellow rectangle labeled "Self-evolving Agents" and "Learning from Feedback & Experience". A robot icon is positioned to the right of this block. The agents listed as contributing to this stage are: Alta (yellow), Gödel agent (purple). * **Next-generation Agentic Intelligence:** A purple rectangle labeled "Next-generation Agentic Intelligence" and containing three question marks ("???"). * **Level of Intelligence:** A vertical axis on the right, with a small robot icon at the bottom and a crown icon at the top, connected by an upward-pointing arrow. * **Arrows:** Arrows indicate the flow of development. Arrows point from LLMs to Foundation Agents, from Foundation Agents to Self-evolving Agents, and from Self-evolving Agents to Next-generation Agentic Intelligence. An arrow also points from "Learning & Evolution Mechanisms" to "Self-evolving Agents". A curved arrow labeled "To be explored..." points from "Self-evolving Agents" to the "Next-generation Agentic Intelligence" block. * **"Our Survey"**: A red location pin icon is placed within the "Learning from Feedback & Experience" section, labeled "Our Survey". ### Key Observations The diagram highlights a clear progression in agentic intelligence. The increasing level of intelligence is visually represented by the upward arrow on the right. The use of question marks for the next generation suggests uncertainty about the future direction of this field. The inclusion of specific agents (GPT-4, Claude-4, etc.) provides concrete examples of current technologies driving this evolution. The "Our Survey" pin suggests the authors are actively researching this area. ### Interpretation The diagram illustrates a conceptual model of how agentic intelligence is evolving. It suggests that LLMs are the foundational building blocks, which are then used to create foundation agents capable of executing tasks via tools and planning. These foundation agents, through learning and evolution mechanisms, can become self-evolving agents, and ultimately lead to next-generation agentic intelligence. The diagram emphasizes the importance of feedback and experience in driving this evolution. The question marks indicate that the ultimate form of next-generation agentic intelligence is still unknown and requires further exploration. The diagram is a high-level overview and doesn't provide specific data points or quantitative measurements, but rather a qualitative representation of the relationships between different components. The positioning of "Our Survey" suggests the authors are actively involved in gathering data to better understand this evolution.