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# Mission
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## The Two Critical Challenges in AI's Future
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### 1. The Data Ownership Crisis
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In today's digital world, there's a fundamental disconnect between data generation and data ownership. Individuals and enterprises generate vast amounts of valuable information, yet they lack true ownership and control over this data. For individuals, digital footprints are scattered across various platforms, social media channels, messenger apps, and cloud storage services. While they can view and interact with this information within each platform, they cannot truly own, analyze, or leverage it as an asset.
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The situation is equally challenging for enterprises. Companies generate immense amounts of valuable information through internal communications, team chats, and shared files, but this knowledge remains unstructured and inaccessible. The inability to fully harness this data prevents organizations from building specialized AI tools or leveraging their collective knowledge effectively. Meanwhile, tech giants maintain privileged access to and profit from this data, creating an imbalance in the digital economy.
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### 2. The AI Training Data Quality Crisis
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As AI development accelerates, we face a growing crisis in training data quality. The increasing reliance on synthetic data, while necessary given current limitations, raises serious concerns about the future of AI development. Synthetic data, by its nature, lacks the genetic diversity and authentic complexity found in real human-generated content. This limitation could lead to AI systems that appear sophisticated but lack deep understanding and genuine intelligence.
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The irony is that while AI researchers struggle with data scarcity and turn to synthetic alternatives, vast amounts of authentic, human-generated data remain locked away in personal and enterprise digital spaces. This disconnection between available authentic data and AI development needs threatens to create a bottleneck in the advancement toward more sophisticated and genuinely intelligent AI systems.
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## Our Two-Pronged Solution
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### 1. Democratizing Data Ownership
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We are creating foundational tools for true data ownership and control. Through our open-source data extraction engine, we enable individuals and organizations to structure, retrieve, and fully own their digital footprints. This technology allows users to consolidate their scattered data into organized, usable assets that they can analyze, share, or leverage as they see fit.
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Our solution transforms raw digital information into structured, valuable assets. For individuals, this means the ability to build personal AI assistants or monetize their data. For enterprises, it enables the creation of private language models based on their collective knowledge, enhancing productivity and innovation while maintaining data security.
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### 2. Expanding Access to Authentic Data
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By empowering individuals and organizations to own their data, we simultaneously create new opportunities for willing participation in AI development. Our platform facilitates a marketplace where individuals and enterprises can choose to share their authentic, structured data with researchers and developers. This creates a new source of high-quality, diverse training data for AI systems, reducing reliance on synthetic alternatives.
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This approach not only solves the data quality crisis but also ensures that AI development benefits from the rich complexity of real-world data. By enabling access to diverse, authentic data sources, we support the development of more sophisticated and genuinely intelligent AI systems.
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## Economic Vision: Towards a Free Market of Data
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Just as the establishment of property rights by classical economists like Adam Smith revolutionized the market economy, we believe that establishing true data ownership will transform the digital economy. By turning data into a legitimate, tradeable asset class, we create the foundation for a new economic paradigm where individuals and organizations can participate fully in the AI economy.
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This transformation creates a regulated, ethical marketplace where:
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- Individuals can monetize their digital footprints while maintaining control over their privacy
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- Enterprises can leverage their internal knowledge for competitive advantage
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- Researchers can access diverse, high-quality training data
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- AI development becomes more democratic and distributed
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The path to Artificial General Intelligence (AGI) lies not in concentrated data control but in the orchestration of diverse, community-driven models trained on authentic human data. By democratizing data ownership and creating a free market for data exchange, we lay the groundwork for a future where AGI emerges from the collective intelligence of humanity rather than the limited perspective of a few dominant players.
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Our vision is to create an ecosystem where data becomes a true asset class, regulated and valued appropriately, leading to a more equitable distribution of power in the AI economy. This democratization of data ownership is the first crucial step toward democratizing AI itself, ensuring that the benefits of artificial intelligence are accessible to all and that its development reflects the full spectrum of human knowledge and experience.
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README.md
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Happy Crawling! 🕸️🚀
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Happy Crawling! 🕸️🚀
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## Mission
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Our mission is to address two critical challenges in AI's future: the data ownership crisis and the AI training data quality crisis. While individuals and enterprises lack true ownership of their valuable digital footprints, AI researchers increasingly rely on synthetic data due to limited access to authentic human-generated content.
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Our open-source solution tackles both problems by democratizing data ownership through powerful extraction tools while creating a marketplace for willing data sharing. By transforming personal and enterprise data into structured, tradeable assets, we're laying the foundation for a free market of data where individuals can monetize their digital footprints, enterprises can leverage their collective knowledge, and researchers can access diverse, high-quality training data.
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This democratization of data ownership is the crucial first step toward democratizing AI itself, ensuring its development reflects the full spectrum of human knowledge and experience. Through this approach, we're building a future where AI advancement is driven by authentic human data rather than synthetic alternatives.
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## Star History
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## Star History
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[](https://star-history.com/#unclecode/crawl4ai&Date)
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[](https://star-history.com/#unclecode/crawl4ai&Date)
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 800 500">
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<!-- Background -->
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<rect width="800" height="500" fill="#1a1a1a"/>
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<!-- Problem Boxes -->
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<rect x="0" y="0" width="300" height="150" rx="10" fill="#2d1a1a" stroke="#ff4444" stroke-width="2"/>
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<text x="150" y="30" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#ff6666">Problem 1: Data Ownership Crisis</text>
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<text x="150" y="60" text-anchor="middle" font-family="Arial" font-size="12" fill="#e0e0e0">
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<tspan x="150" dy="0">Scattered personal data</tspan>
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<tspan x="150" dy="20">Inaccessible enterprise knowledge</tspan>
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<tspan x="150" dy="20">No true data ownership</tspan>
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<tspan x="150" dy="20">Tech giants control access</tspan>
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</text>
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<!-- Problem 2 Box -->
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<rect x="0" y="200" width="300" height="150" rx="10" fill="#1a2d1a" stroke="#4caf50" stroke-width="2"/>
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<text x="150" y="230" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#81c784">Problem 2: AI Training Data Crisis</text>
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<text x="150" y="260" text-anchor="middle" font-family="Arial" font-size="12" fill="#e0e0e0">
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<tspan x="150" dy="0">Over-reliance on synthetic data</tspan>
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<tspan x="150" dy="20">Limited genetic diversity</tspan>
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<tspan x="150" dy="20">Shallow AI understanding</tspan>
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<tspan x="150" dy="20">Data scarcity for researchers</tspan>
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</text>
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</g>
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<!-- Arrows -->
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<g transform="translate(400,125)">
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<path d="M-20,0 L40,0" stroke="#666" stroke-width="2" marker-end="url(#arrowhead)"/>
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<path d="M-20,200 L40,200" stroke="#666" stroke-width="2" marker-end="url(#arrowhead)"/>
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</g>
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<!-- Arrow Marker -->
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<defs>
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<marker id="arrowhead" markerWidth="10" markerHeight="7" refX="9" refY="3.5" orient="auto">
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<polygon points="0 0, 10 3.5, 0 7" fill="#666"/>
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</marker>
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</defs>
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<!-- Solution Boxes -->
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<g transform="translate(450,50)">
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<!-- Solution 1 Box -->
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<rect x="0" y="0" width="300" height="150" rx="10" fill="#1a2d3d" stroke="#2196f3" stroke-width="2"/>
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<text x="150" y="30" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#64b5f6">Solution 1: Democratizing Ownership</text>
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<text x="150" y="60" text-anchor="middle" font-family="Arial" font-size="12" fill="#e0e0e0">
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<tspan x="150" dy="0">Open-source extraction tools</tspan>
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<tspan x="150" dy="20">Data as structured assets</tspan>
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<tspan x="150" dy="20">Personal AI assistants</tspan>
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<tspan x="150" dy="20">Enterprise knowledge bases</tspan>
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</text>
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<!-- Solution 2 Box -->
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<rect x="0" y="200" width="300" height="150" rx="10" fill="#2d2613" stroke="#ffa726" stroke-width="2"/>
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<text x="150" y="230" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#ffb74d">Solution 2: Authentic Data Access</text>
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<text x="150" y="260" text-anchor="middle" font-family="Arial" font-size="12" fill="#e0e0e0">
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<tspan x="150" dy="0">Data marketplace</tspan>
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<tspan x="150" dy="20">Willing participation</tspan>
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<tspan x="150" dy="20">High-quality training data</tspan>
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<tspan x="150" dy="20">Path to distributed AGI</tspan>
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</text>
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</g>
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<!-- Future Vision Box at Bottom -->
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<g transform="translate(200,420)">
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<rect x="0" y="0" width="400" height="60" rx="10" fill="#2d1a2d" stroke="#ba68c8" stroke-width="2"/>
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<text x="200" y="35" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#ce93d8">Economic Vision: Free Market of Data</text>
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</g>
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</svg>
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 800 500">
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<!-- Background -->
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<rect width="800" height="500" fill="#ffffff"/>
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<!-- Problem Boxes -->
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<g transform="translate(50,50)">
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<rect x="0" y="0" width="300" height="150" rx="10" fill="#ffebee" stroke="#ef5350" stroke-width="2"/>
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<text x="150" y="30" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#d32f2f">Problem 1: Data Ownership Crisis</text>
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<text x="150" y="60" text-anchor="middle" font-family="Arial" font-size="12" fill="#333">
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<tspan x="150" dy="0">Scattered personal data</tspan>
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<tspan x="150" dy="20">Inaccessible enterprise knowledge</tspan>
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<tspan x="150" dy="20">No true data ownership</tspan>
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<tspan x="150" dy="20">Tech giants control access</tspan>
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</text>
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<!-- Problem 2 Box -->
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<rect x="0" y="200" width="300" height="150" rx="10" fill="#e8f5e9" stroke="#66bb6a" stroke-width="2"/>
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<text x="150" y="230" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#2e7d32">Problem 2: AI Training Data Crisis</text>
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<text x="150" y="260" text-anchor="middle" font-family="Arial" font-size="12" fill="#333">
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<tspan x="150" dy="0">Over-reliance on synthetic data</tspan>
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<tspan x="150" dy="20">Limited genetic diversity</tspan>
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<tspan x="150" dy="20">Shallow AI understanding</tspan>
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<tspan x="150" dy="20">Data scarcity for researchers</tspan>
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</text>
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</g>
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<g transform="translate(400,125)">
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<path d="M-20,0 L40,0" stroke="#666" stroke-width="2" marker-end="url(#arrowhead)"/>
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<path d="M-20,200 L40,200" stroke="#666" stroke-width="2" marker-end="url(#arrowhead)"/>
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<!-- Solution 1 Box -->
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<rect x="0" y="0" width="300" height="150" rx="10" fill="#e3f2fd" stroke="#42a5f5" stroke-width="2"/>
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<text x="150" y="30" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#1565c0">Solution 1: Democratizing Ownership</text>
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<text x="150" y="60" text-anchor="middle" font-family="Arial" font-size="12" fill="#333">
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<tspan x="150" dy="0">Open-source extraction tools</tspan>
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<tspan x="150" dy="20">Data as structured assets</tspan>
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<tspan x="150" dy="20">Personal AI assistants</tspan>
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<tspan x="150" dy="20">Enterprise knowledge bases</tspan>
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</text>
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<!-- Solution 2 Box -->
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<rect x="0" y="200" width="300" height="150" rx="10" fill="#fff3e0" stroke="#ffa726" stroke-width="2"/>
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<text x="150" y="230" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#ef6c00">Solution 2: Authentic Data Access</text>
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<text x="150" y="260" text-anchor="middle" font-family="Arial" font-size="12" fill="#333">
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<tspan x="150" dy="0">Data marketplace</tspan>
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<tspan x="150" dy="20">Willing participation</tspan>
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<tspan x="150" dy="20">High-quality training data</tspan>
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<tspan x="150" dy="20">Path to distributed AGI</tspan>
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</text>
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</g>
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<!-- Future Vision Box at Bottom -->
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<g transform="translate(200,420)">
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<rect x="0" y="0" width="400" height="60" rx="10" fill="#f3e5f5" stroke="#ab47bc" stroke-width="2"/>
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<text x="200" y="35" text-anchor="middle" font-family="Arial" font-weight="bold" font-size="16" fill="#6a1b9a">Economic Vision: Free Market of Data</text>
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</g>
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</svg>
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