Optilensai
  • Introduction
  • Overview
  • Problem Statement
  • Vision and Mission
  • The Ecosystem
    • Key Components
      • DAO Governance
      • AI Integration
    • Core Principles
  • HOW IT WORKS
    • Workflow and Interactions
    • NFT Minitng and Ownership
    • DAO Governance Mechanism
    • AI's Role in the Ecosystem
  • USE CASES
    • Funding Research Projects
    • Licensing Data and Findings
    • Community-Driven Innovations
  • TECHNICAL ARCHITECTURE
    • Blockchain and Smart Contracts
    • NFT Standards (ERC-721, ERC-1155)
    • DAO Framework (e.g., Snapshot, Aragon)
    • AI Technology Stack
  • TOKENOMICS
    • Token Detail and Distribution
    • Token Utility
    • Supply Management
  • ROADMAP
    • Q1 2025 : Foundation and Launch
    • Q2–Q4 2025: Ecosystem Expansion and Scaling
    • 2026 and Beyond: Sustainability and Autonomy
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Problem Statement

The current research landscape is riddled with challenges, including:

  1. Centralized Control

    • Research funding and decision-making are often controlled by a few institutions, limiting opportunities for smaller or unconventional projects.

  2. Lack of Transparency

    • The allocation of research funds and the outcomes of projects are not always transparent, leading to inefficiencies and distrust.

  3. Barriers to Collaboration

    • Researchers, funders, and collaborators are often siloed, making it difficult to share resources, data, and expertise effectively.

  4. Limited Monetization Options

    • Researchers struggle to monetize their intellectual property (IP) and findings, reducing incentives for innovation.

  5. Underutilized AI Potential

    • AI's ability to analyze data, predict outcomes, and optimize decisions remains largely untapped in the research sector.

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Last updated 3 months ago