Introduction

Zyger is a framework designed to advance decentralized physical infrastructure networks (DePIN) by promoting privacy-preserving AI technologies. Its primary objective is to incentivize GPU providers, model trainers, AI developers, and data owners to participate in a secure ecosystem. Zyger achieves this through the integration of federated learning and zero-knowledge proofs, ensuring that AI model inference and data remain private.

Key features of Zyger include:

• Privacy-preserving AI using cryptographic techniques for zero-leakage model inference.

• Decentralized AI model training and inference using GPU networks across a global scale.

• Zero-Knowledge Machine Learning (Zyger) for verifiable AI execution without revealing sensitive data.

• Utilization of Transformer-based Large Language Models (LLMs) for accurate natural language processing.