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Agentic AI is another concept to wrap our heads around and presents new and complex challenges to AI risk management.

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What is Agentic Ai?

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Agentic AI 101: Considering the graphic below, "an AI Agent can be defined as a piece of software, with one or more Language Models as its backbone."

Agentic AI embodies AI agents that can decompose complex tasks into smaller, manageable sub-tasks, leveraging their language model capabilities to navigate through these tasks with a significant level of autonomy. The level of autonomy is determined by the number of iterations they can execute independently and their ability to integrate human input when necessary.

These agents operate on a cycle of action, observation, and adjustment, continuously refining their approach until they reach a conclusive outcome.

The architecture of these agents allows for the integration of various tools or APIs, enhancing their functionality and interaction with external systems.

Symbolic reasoning is a critical aspect of these agents, particularly for those with vision capabilities, as it allows the agents to handle abstract concepts alongside concrete data inputs, making them effective for more complex and dynamic environments.

In essence, an AI Agent according to Greyling, is software capable of independent problem-solving within its operational parameters, and it significantly benefits from being situated within a supportive ecosystem that allows for continuous improvement and integration of new functionalities.

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