# Introduction



<figure><img src="https://4269003536-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fz2ewhfaUwAaayupPjFcz%2Fuploads%2FeYTzUqMbN13iDKQJFvsp%2FGroup%2032.png?alt=media&#x26;token=ae315ae6-815e-445f-bfe3-ac678f020391" alt="" width="280"><figcaption></figcaption></figure>

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ZkAGI (Zero-Knowledge Artificial General Intelligence) 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. ZkAGI achieves this through the integration of federated learning and zero-knowledge proofs, ensuring that AI model inference and data remain private.

### Key features of ZkAGI 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 (ZKML) for verifiable AI execution without revealing sensitive data.
* Utilization of Transformer-based Large Language Models (LLMs) for accurate natural language processing.\


### Architecture

<figure><img src="https://4269003536-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fz2ewhfaUwAaayupPjFcz%2Fuploads%2FhXMSfqfiubSvjmAYgyvX%2Fimage.png?alt=media&#x26;token=682d9be4-96f2-4a93-9b71-29d466e09540" alt=""><figcaption><p>Overview of the ZkAGI Integration Architecture</p></figcaption></figure>
