Inferix Decentralized GPU
  • Overview
  • Tokenomics
  • Introduction
    • Rendering network using crowdsourced GPU
    • Rendering verification problem
  • Decentralized visual computing
    • Client Apps plugin
    • Client API and SDK
    • Manager node
    • Worker node
    • Decentralized storage
      • Data categories
      • Multi-level 3D polygon data
      • Polygon digester
      • Decentralized storage
      • Decentralized cache
    • Data security with FHE and TEE
      • Verifier data security enhancement with FHE
      • Worker and Manager data security enhancement with FHE
    • Decentralized federated AI
      • Federated learning with TensorOpera
      • Meta LLaMA
      • Stable Diffusion
      • Other AI models
      • Inferix AI
  • Inferix Testnet 1
    • Inferix GPU Solutions
    • Adding GPUs to the Network
    • Renting GPU Devices
    • GPU Staking
  • Future development
    • PoR and NFT minting for graphics creative assets
    • ZKP and PoR communication
    • Inferix RemotePC
    • Rendering professional network
  • Terms of Service
    • Privacy Policy
    • Airdrop Terms of Service
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  1. Decentralized visual computing

Decentralized federated AI

In the discussion about decentralized visual computing service, we have introduced the physical GPU network used for graphics rendering. We discuss now how we utilize this GPU network for AI training and inference. These processes are essential items of Inferix's Phase 2 strategy, aligning with the core principles of Web3: openness, decentralization, self-governance, and diversity.

Currently, AI advancements are predominantly driven by industry giants like Google and OpenAI, relegating most users to passive roles. This situation runs counter to the principles of Web3 and DePIN. To bridge this gap, we propose an application framework for deploying federated learning models on the Inferix GPU infrastructure in the following sections. This framework is designed not only to reshape the existing landscape but also to elevate the intelligence of the evolving DePIN ecosystem.

PreviousWorker and Manager data security enhancement with FHENextFederated learning with TensorOpera

Last updated 4 months ago