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On this page
  • AI Browser Overview
  • Interaction with AI Agents and LLM Systems
  • Distributed Validation and Data Integrity
  • Access Control and Permissions
  • Analytics and Performance Dashboard
  1. Product

Supernet | AI Explorer

Enabling developers and users to more easily access AI OS and manage Agents.

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Last updated 5 months ago

AI Browser Overview

The AI Browser serves as a decentralized interface for monitoring and managing AI agents and Supernet components, similar to how Etherscan operates for blockchain data. It allows users to view real-time system status, performance metrics, and task logs for AI agents and LLM systems. This includes tracking task progress, viewing resource consumption (CPU, memory), and controlling the execution of AI agents within the Supernet.

Interaction with AI Agents and LLM Systems

Through the AI Browser, users can interact with AI agents and LLM systems by issuing commands, monitoring outputs, and controlling the execution flow. The browser enables users to initiate tasks, view intermediate results, and pause or resume operations. For example, a user can query an LLM for data analysis and track its processing steps in real-time.

Distributed Validation and Data Integrity

The AI Browser integrates with the Supernet Distributed Validator to ensure the integrity and security of data across the network. The browser displays real-time validation logs that confirm all actions taken by AI agents and LLMs are consistent and tamper-proof. This validation ensures trustworthy results, especially in sensitive applications like healthcare or finance.

Access Control and Permissions

The AI Browser includes an Access Control Mechanism that allows users to manage permissions for AI agents and components. Roles such as admin, user, or read-only can be assigned to control access. This ensures that sensitive data is protected and only authorized users can modify or interact with specific components.

Analytics and Performance Dashboard

The AI Browser features an analytics dashboard that provides insights into the overall health and performance of the Supernet AI ecosystem. Key metrics such as system load, agent response times, and resource utilization are displayed. Users can optimize performance by controlling resource allocation or offloading tasks from overburdened agents.

Easily search and control AI module with AI explorer.