Google Unveils Whitepaper on Generative AI Agents

Google has published a comprehensive whitepaper that explores the development and functionality of Generative AI agents. This document outlines how these agents operate by utilising external tools to enhance their capabilities beyond traditional language models.

The whitepaper defines a Generative AI agent as an application designed to achieve specific goals by observing its environment and acting upon it using available tools. These agents are characterised by their autonomy, allowing them to operate independently of human intervention when provided with clear objectives.

“Agents extend the capabilities of language models by leveraging tools to access real-time information, suggest real-world actions, and plan and execute complex tasks autonomously,” the authors stated. 

According to the paper, the key components of the agent’s architecture include a cognitive framework that structures reasoning, planning, and decision-making processes. The orchestration layer is crucial as it guides agents through a cyclical process of information intake and action execution.

The document also discusses the importance of tools, such as Extensions and Functions, which allow agents to interact with external systems. These tools enable agents to perform tasks like updating databases or fetching real-time data.

“Tools bridge the gap between the agent’s internal capabilities and the external world,” according to the authors. They provide examples of how agents can utilize various APIs to enhance their functionality.

Moreover, the whitepaper highlights the role of Data Stores in providing agents with access to dynamic information, ensuring that responses remain relevant and factually accurate. This capability is particularly important as it allows agents to adapt to changing information landscapes.

The whitepaper presents various use cases where Generative AI agents can be applied effectively. For instance, an agent could assist users in booking flights by interacting with multiple APIs to gather necessary information dynamically.

In addition, Google described how developers can leverage these agents within applications like Vertex AI. The platform provides a managed environment where developers can define goals, task instructions, and examples to efficiently construct desired system behaviors.

On the other hand, OpenAI chief Sam Altman recently published a blog titled Reflections, in which he stated that AI agents could enter the workforce by 2025. “We believe that, in 2025, we may see the first AI agents join the workforce and materially change the output of companies,” Altman wrote.