Google has published a comprehensive whitepaper exploring the development and capabilities of Generative AI agents. This document provides an overview of how these agents work and extend their functionality beyond the traditional language model with the help of external tools.
The whitepaper defines a Generative AI agent as an application designed to achieve a specific goal by observing its environment and acting on it using available tools. These agents are characterized by autonomy and can operate independently of human intervention when given a clear purpose.
“Agents extend the capabilities of language models by leveraging tools to access real-time information, suggest real-world actions, and autonomously plan and execute complex tasks,” the authors write. states.
According to the paper, key components of an agent’s architecture include a cognitive framework that structures the reasoning, planning, and decision-making processes. The orchestration layer is critical because it guides agents through the cyclical process of ingesting information and performing actions.
This document also explains the importance of tools such as extensions and functions that enable agents to interact with external systems. These tools allow agents to perform tasks such as updating databases and retrieving real-time data.
According to the authors, “tools bridge the gap between an agent’s internal capabilities and the external world.” These provide examples of how agents can utilize various APIs to enhance their functionality.
Additionally, the paper highlights the role of data stores in providing agents with access to dynamic information and ensuring response relevance and factual accuracy. This feature is particularly important because it allows agents to adapt to changing information situations.
This whitepaper introduces various use cases where Generative AI agents can be effectively applied. For example, an agent can interact with multiple APIs to dynamically collect necessary information to help users book flights.
Additionally, Google explained how developers can leverage these agents within applications such as Vertex AI. The platform provides a managed environment where developers can define goals, task instructions, and examples to efficiently build desired system behavior.
Meanwhile, OpenAI head Sam Altman recently published a blog titled “Reflections,” in which he said AI agents could enter the workforce by 2025. change the output of a company,” Altman wrote.
