Introduction

Inferix is a DePIN network of GPUs for visual computing and AI, it is built to bridge the needs of users and hardware owners. Its solution meets real-world problems across a range of industries, not only for the AI field but also for high-quality graphics rendering. Users (e.g. 3D graphics artists, game developers, enterprises) who need GPU computing power for rendering high-quality graphics can use the Inferix system to continuously access these precious resources with faster processing time and more efficient spending. Owners of GPUs can share idle resources to the Inferix network and earn long-term passive income while simultaneously balancing their main jobs or leisure activities.

At high-level, Inferix network is naturally a dynamic system where demands of digital content creators and supplies of GPU owners are created continuously over time. Users are concerned with the security and privacy of the system, with the facility of accessing computing resources, as well as with the price that they have to pay for their demands.

This section first describes the high-level flow of a decentralized rendering network. Next, we describe one of the main challenges that we have to deal with, that is the authenticity of rendering. Section 2 presents the main idea of the proposed solution then introduces a mathematical model for the Active Noise Generation and Verification algorithm. Section 3 describes an implementation for the algorithm and its integration into the existing layers of the Inferix network. Section 4 presents the main components in the system architecture of the Inferix decentralized GPU network. In Section 5, we discuss how to use this network infrastructure for the AI training and inference, then Inferix is actually a GPU network for visual computing and federated AI. In Section 6, we present the token economy model of Inferix with a novel algorithm called Burn-Mint-Work for the token issuance problem. Finally, Section 7 is reserved for ongoing developments in improving the robustness, performance and availability of the network.