Next-Generation DLT: Neural Networks, Federated Learning, and DAG Synergy

Navid Kiani Larijani - Jun 27 - - Dev Community

As a dedicated advocate for decentralized systems, I’m thrilled by the possibilities of blockchain technology. But let’s face it—current solutions still struggle with security, scalability, and efficiency. It’s time for a breakthrough.

The traditional blockchain model, despite its innovations, hasn’t fully realized the dream of a decentralized web. We need to push the envelope and redefine what’s possible.

Introducing SYNNQ! 🚀 By integrating Neural Networks (NN) and Federated Learning within a Directed Acyclic Graph (DAG) structure, SYNNQ addresses these challenges head-on. Here’s how:

• Unmatched Security: Advanced fraud detection with NN-based validation and federated learning.

• Incredible Scalability: Up to 1,000,000 transactions per second with lightning-fast confirmation times.

• Efficient Resource Use: 65% reduction in computational overhead and 40% decrease in bandwidth usage.

• Rock-Solid Resilience: Maintains efficiency even with 30% of nodes compromised.

• Decentralized Governance: Fair and transparent reputation-based voting system.

SYNNQ is not just an upgrade—it’s a revolution. Let’s challenge the status quo and drive the future of decentralized technology together. Join me in powering the next generation of blockchains! 🌟

For more details and collaboration, read our full whitepaper or contact us at dev@synnq.io.

https://www.academia.edu/121565045/Next_Generation_Blockchain_Neural_Networks_Federated_Learning_and_DAG_Synergy_June_2024?source=swp_share

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