Parallel AI
  • Overview
    • Introduction
    • Problem Statement
    • The Parallel AI Solution
    • Key Benefits
  • HOW PARALLEL PROCESSING IMPROVES AI EFFICIENCY
    • Boosting The Performance Of GPUs / CPUs
    • Efficient Use Of Processing Cores
    • Competitive Advantages
  • Technology
    • Technology Overview
    • Parallel Code Inputting & Analysis
    • Automatic Parallelization
    • Execution Model
    • Integration With Decentralized Networks
    • Example Applications
  • REVENUE MODEL & TOKENOMICS
    • The $PAI Token
    • Revenue Model
    • Tokenomics
  • Roadmap
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Roadmap

Phase 1: AI Parallel Code Writer

Parallel AI will start by launching its AI-powered code writer that can automatically convert sequential code into highly efficient parallelized versions. This will empower developers to leverage the full potential of Parallel AI's technology without requiring deep expertise in parallel programming.

Phase 2: GPU Network Host for Rent

Parallel AI will establish its aggregated decentralized GPU network through partnerships, so that code can be automatically executed via the most task-appropriate and cost-efficient hardware.

Phase 3: Bespoke Virtual Processing on GPU Network

In the final phase, Parallel AI will offer a comprehensive virtual processing service, allowing users to seamlessly tap into the distributed GPU network and execute their parallelized workloads. This will provide a turnkey solution for organizations seeking to harness the power of Parallel AI without the need for complex infrastructure management.

PreviousTokenomics

Last updated 9 months ago