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NuNet Whitepaper
NuNet Whitepaper
  • NuNet Whitepaper
  • Summary
  • ๐ŸŒŽGlobal Computing Infrastructure
    • Current State: data and computing silos
    • A flexible, decentralized computational universe
  • ๐ŸŒSystem architecture
    • Overview
    • Computational and Functional Principles
      • Context Awareness
      • Mobility
      • Value Exchange
    • Supported functionalities
      • Mobile Computational Processes
      • Flexible Workflow Design
      • Data and Value Production & Exchange
      • Logical Scalability
      • Verification and Validation
      • An Ecosystem of Adaptive Decentralized Computations
      • Learning and Meta-Learning
      • Human-mediated Cognitive Development
  • ๐Ÿ’ผBusiness and Operational Model
    • Multi-sided platform
      • Compute providers
      • Data Providers
      • AI Service Providers
      • Consumers
      • Network Operators
      • Technical Partners
      • Platform Developers
      • NuNet Organization
    • Partnerships and envisioned interoperations
      • SingularityNET
      • Decentralized AI Alliance (DAIA)
      • SingularityDAO
      • COD
      • Others
  • ๐Ÿ‘จโ€๐Ÿ’ปGovernance & Decentralization
    • Governance
    • Governance Roadmap
    • Future NuNet Token
      • Dynamic Pricing and Demand/Supply Dynamics
    • Ecosystem Building and Token Distribution
  • ๐Ÿ’ปTechnical roadmap and Use Cases
    • Initial technical roadmap
    • Potential Use Cases
    • Large Partnerships
  • ๐Ÿ”—Whitepaper download and references
  • Important Notice
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  1. System architecture
  2. Supported functionalities

Mobile Computational Processes

PreviousSupported functionalitiesNextFlexible Workflow Design

Last updated 2 years ago

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A computational agent encloses a computational process that turns input data into output data, without any restriction whatsoever on the nature of the process or the amount of computational resources that it needs. Agents isolate the processโ€™ computational logic from the physical implementation, resources and location. A computational process encapsulated into an agent can be any combination of memory and processing, which can range from complex AI and machine learning processes to simple queries for retrieving data from a database or a streaming data source. The abstraction layer that isolates computational logic from physical implementation enables agents to be agnostic to the physical infrastructure and location, which can be dynamically changed as per demands of specific workflow.

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