A naukri.com initiative
Medium
4w
272
Image Credit: Medium
Google AI Agents: Bridging Models with the Real World
- AI agents bridge the gap between conventional language models and real-world interaction by dynamically accessing external information and executing actions.
- They can plan multi-step processes, access real-time data, and make decisions based on real-time inputs.
- Google's AI agents consist of three key components: the Model, the Tools, and the Orchestration Layer.
- The Model serves as the core intelligence, while Tools enable interaction with external data sources and APIs.
- The Orchestration Layer governs the AI agent's reasoning process and decision-making abilities.
- Google AI agents combine reasoning, logic, and external information connected to a Generative AI model to function as agents.
- Key reasoning frameworks used by Google AI agents include ReAct, Chain-of-Thought, and Tree-of-Thoughts.
- Tools provided by Google for AI agents include Extensions, Functions, and Data Stores, enabling seamless API integration, controlled execution, and real-time knowledge access.
- Targeted learning techniques like In-Context Learning, Retrieval-Based Learning, and Fine-Tuning improve AI agent performance.
- AI agents can handle complex queries by integrating reasoning frameworks with external tools like search and location APIs.
Read Full Article
16 Likes
For uninterrupted reading, download the app