Trending...
- New Book "Three Permissions" Redefines Self-Leadership for a Burnout-Weary Culture
- Donna Cardellino and Paul Lafrance Sign Exclusive Deal for Worldwide Expansion into Commercial and Luxury Real Estate Design Projects
- Opening a new era of USDC smart cloud mining: CJB Crypto makes digital dollar earnings within reach
NEW YORK - PrAtlas -- Vinnetwork, a blockchain-based decentralized artificial intelligence platform, today released its whitepaper outlining plans to democratize AI development through a distributed network that allows users to share data, computational resources, and AI models while maintaining data sovereignty.
The platform aims to address "centralization bottlenecks" in the current AI ecosystem, where large technology corporations control vast data silos and expensive computational infrastructure, limiting innovation from smaller players and independent researchers.
Three-Layer Architecture
Vinnetwork's platform operates on three interconnected layers: a Decentralized Data Layer (DDL) for secure data sharing, a Decentralized Compute Layer (DCL) that creates a peer-to-peer marketplace for computational resources, and a Decentralized Model Layer (DML) for AI model development and sharing.
The platform's native Vinnetwork (VIN) token serves as the primary currency for transactions across all three layers, enabling users to pay for data access, computational power, and AI model licensing. Token holders also receive governance rights in the planned Decentralized Autonomous Organization (DAO).
More on PrAtlas
Token Economics
The project plans to issue 2 billion VIN tokens, with 35% allocated for ecosystem incentives and community rewards. The token distribution includes 20% for public sale through an Initial Exchange Offering (IEO), 18% for foundation treasury, 15% for the core team, and 10% for private investors.
Privacy-Preserving Technology
Vinnetwork's integration of Privacy-Enhancing Technologies (PETs) includes federated learning, zero-knowledge proofs, and secure multi-party computation. These technologies aim to enable AI model training on distributed datasets without exposing raw data, addressing privacy concerns in traditional AI development.
The platform initially launches as an ERC-20 token on Ethereum but plans to migrate to a dedicated high-performance blockchain optimized for AI workloads.
Leadership and Use Cases
The project is led by CEO Dr. Alex Mason, who previously headed Advanced AI Research at Innovatech Solutions Inc., and CTO Sofia Bronte, a former Principal Engineer at CyberSecure Protocols Ltd. The team includes Dr. Lena Petrova, a former Cambridge University researcher specializing in privacy-enhancing technologies.
More on PrAtlas
Proposed use cases include privacy-preserving medical AI diagnostics, decentralized finance risk modeling, and collaborative scientific research where institutions can pool datasets and computational resources without compromising data privacy.
Market Context
The announcement comes as the AI industry faces increasing scrutiny over data privacy, algorithmic bias, and the concentration of AI capabilities among major technology companies. The whitepaper acknowledges risks including technological challenges, regulatory uncertainty, and market adoption hurdles.
The company plans to release initial SDKs and API documentation following its mainnet launch, with a phased development roadmap extending through mainstream enterprise adoption.
More information about Vinnetwork is available at https://www.vinnetworkvin.com/, with the complete whitepaper accessible at https://www.vinnetworkvin.com/assets/file/vinnetwork-whitepaper.pdf.
The platform aims to address "centralization bottlenecks" in the current AI ecosystem, where large technology corporations control vast data silos and expensive computational infrastructure, limiting innovation from smaller players and independent researchers.
Three-Layer Architecture
Vinnetwork's platform operates on three interconnected layers: a Decentralized Data Layer (DDL) for secure data sharing, a Decentralized Compute Layer (DCL) that creates a peer-to-peer marketplace for computational resources, and a Decentralized Model Layer (DML) for AI model development and sharing.
The platform's native Vinnetwork (VIN) token serves as the primary currency for transactions across all three layers, enabling users to pay for data access, computational power, and AI model licensing. Token holders also receive governance rights in the planned Decentralized Autonomous Organization (DAO).
More on PrAtlas
- purelyIV Launches Niagen® IV Therapy – A Breakthrough in NAD+ Cellular Wellness
- Jewellok Unveils Cutting-Edge Specialty Gas Changeover Manifolds to Revolutionize Industrial and Medical Gas Delivery
- Press Snooze on Summer: 8 Inns Team Up to Help Guests Sleep In
- On the 30th anniversary of the Netscape IPO the inventor of the banner ad warns: "Trouble ahead."
- Early Bird Registration Now Open for the Inaugural OpenSSL Conference 2025
Token Economics
The project plans to issue 2 billion VIN tokens, with 35% allocated for ecosystem incentives and community rewards. The token distribution includes 20% for public sale through an Initial Exchange Offering (IEO), 18% for foundation treasury, 15% for the core team, and 10% for private investors.
Privacy-Preserving Technology
Vinnetwork's integration of Privacy-Enhancing Technologies (PETs) includes federated learning, zero-knowledge proofs, and secure multi-party computation. These technologies aim to enable AI model training on distributed datasets without exposing raw data, addressing privacy concerns in traditional AI development.
The platform initially launches as an ERC-20 token on Ethereum but plans to migrate to a dedicated high-performance blockchain optimized for AI workloads.
Leadership and Use Cases
The project is led by CEO Dr. Alex Mason, who previously headed Advanced AI Research at Innovatech Solutions Inc., and CTO Sofia Bronte, a former Principal Engineer at CyberSecure Protocols Ltd. The team includes Dr. Lena Petrova, a former Cambridge University researcher specializing in privacy-enhancing technologies.
More on PrAtlas
- "Google AI and the Quiet War on Sovereignty: The Case of Aquitaine"
- Immigrant-Owned Businesses Across U.S. Face New SBA and Equipment Financing Barriers
- Legendary N.W.A. CoFounder & Tech Visionary OG Arabian Prince Joins Tech Coast Venture Network Board
- Former Irvine Mayor Farrah Khan Joins Tech Coast Venture Network Board
- DT Digital Relaunches as Redouble Digital, Expanding from Freelance Operation to Full-Service E-commerce Marketing Agency
Proposed use cases include privacy-preserving medical AI diagnostics, decentralized finance risk modeling, and collaborative scientific research where institutions can pool datasets and computational resources without compromising data privacy.
Market Context
The announcement comes as the AI industry faces increasing scrutiny over data privacy, algorithmic bias, and the concentration of AI capabilities among major technology companies. The whitepaper acknowledges risks including technological challenges, regulatory uncertainty, and market adoption hurdles.
The company plans to release initial SDKs and API documentation following its mainnet launch, with a phased development roadmap extending through mainstream enterprise adoption.
More information about Vinnetwork is available at https://www.vinnetworkvin.com/, with the complete whitepaper accessible at https://www.vinnetworkvin.com/assets/file/vinnetwork-whitepaper.pdf.
Source: Vinnetwork
0 Comments
Latest on PrAtlas
- Shincheonji Reaches World-Class Level At International Taekwondo Competition
- TNT Removal & Disposal Celebrates Record Year Helping Pennsylvania Property Owners Reclaim Space
- SpaceWERX selects New Frontier Aerospace to Develop Bifröst Orbit Transfer Spacecraft
- Postmortem Pathology Offers Expert Autopsy Services with Dignity and Accuracy
- Private Autopsies Provide Families in Colorado with Answers and Closure
- Vijay Tirathrai named Managing Director in Dubai, UAE
- How smart women use BAY Miner cloud mining to easily earn Bitcoin every day
- Qualis LLC Appoints Jeremy Mallicoat as Chief Financial Officer to Advance Growth and Acquisition Strategy
- Bynn Intelligence Reinvents Document Fraud Detection with Groundbreaking Acquisition and Revolutionary AI Model
- 2A Commerce Launches Firearms eCommerce Platform
- Exposing Psychiatric Abuse, CCHR Has Pushed for Global Human Rights Protections
- RDG Mining launches 1-day XRP、BTC mining contract, XRP short-term investment users surge 500%
- Donna Cardellino and Paul Lafrance Sign Exclusive Deal for Worldwide Expansion into Commercial and Luxury Real Estate Design Projects
- New Book "Three Permissions" Redefines Self-Leadership for a Burnout-Weary Culture
- Opening a new era of USDC smart cloud mining: CJB Crypto makes digital dollar earnings within reach
- The Evolution of the BDCV Platform: Empowering Mental Health & Wellness
- Philadelphia HVAC Company Bypasses Paid Search Ads, Citing Cost Savings for Customers
- Block AI Labs Empowers Startups with Affordable, AI-Driven Software Development from U.S. and Colombia Ask ChatGPT
- "The U.S. is Running Out of Workers" – New Book Offers Urgent, Research-Backed Solution to the Workforce Crisis
- LandGate® Releases Q2 2025 U.S. Data Center Development Summary