1. Executive Summary
Mission: The "Root of Trust" in the AI Era
[The Economic Impact of AI] In modern society, generative AI technology has undergone explosive evolution. According to estimates by McKinsey & Company, it is predicted to generate up to $4.4 trillion (approx. 660 trillion JPY) in value for the global economy annually. Against the backdrop of this massive economic impact, AI development companies worldwide are fiercely vying to secure the "high-quality training data" that determines model performance. However, a historic turning point has arrived.
[The Scarcity of Human Data] That turning point is the depletion of high-quality "human-derived data." Public data on the internet is already being exhausted by AI training, and research institutions like Epoch AI have warned that high-quality language data could run dry by 2026. Due to this "resource scarcity," the value of accurate and verified human-derived data is skyrocketing.
[The "New Oil" Demand] In fact, surveys by Grand View Research and others predict that the AI training data market will expand to $8.6 billion (approx. 1.3 trillion JPY) by 2030, and the entire generative AI market will reach $1.3 trillion (approx. 195 trillion JPY) by 2032. "Verified human data" is now creating explosive demand worldwide as the "new oil" of AI development.
[The Crisis of Data Quality] On the other hand, the "quality" of the data space is facing a serious crisis. While high-quality data is becoming scarce, much of the data being generated—which IDC projects will reach 175 zettabytes by 2025—is being overwhelmed by inaccurate information and AI-generated fake data. The economic loss caused by such "bad data" is astronomical, with IBM analysis estimating it to reach a global scale of $15 trillion annually.
[The Liability of "Lack of Trust"] In particular, the "lack of trust" has become the greatest liability of the AI era. This includes costs to prevent "Model Collapse" and hallucinations—which AI developers fear most—as well as ad fraud damages in the digital advertising sector, which Juniper Research warns will exceed $172 billion (approx. 25.8 trillion JPY) annually by 2028.
[DEP Protocol Solution] The DEP Protocol was designed as one of the world's largest data infrastructures to bring order to the gap between this "huge demand for depleting authentic data" and the "flood of chaotic fake data." By utilizing blockchain technology to mathematically prove the "origin" and "validity" of data the moment it is generated, we function not merely as data storage, but as a "manufacturing plant of trust" that supplies only "pure facts without impurities" to society. To realize this, we are leveraging the Avalanche technology stack to develop and implement a proprietary Layer 1 blockchain equipped with high processing capacity and scalability.
[Vision for the Future] With this infrastructure established, AI developers can secure verified "human-derived data" rather than polluted data to build safe AI, and companies can distinguish real humans from bots to avoid massive fraud losses. Just as central banks once secured the value of currency, the DEP Protocol realizes a sustainable social foundation where AI and humans coexist, serving as the internet's new "Root of Trust" that guarantees the value and reliability of increasingly scarce data.
2. Introduction: Why is it Necessary Now?3. Solution4. Technical Architecture5. Token Economics6. Validator Configuration and Roles7. Ecosystem and Developer Support8. Roadmap9. Team and Advisors10. Risk Factors & Disclaimer