OmniTensor
  • Welcome
  • Introduction
    • What is OmniTensor?
    • Vision & Mission
    • Key Features
    • Why OmniTensor?
      • Current Challenges in AI
      • How OmniTensor Addresses These Challenges
  • Core Concepts
    • AI Grid as a Service (AI-GaaS)
      • Overview of AI-GaaS
      • Benefits of AI-GaaS
      • Use Cases of AI-GaaS
    • Decentralized Physical Infrastructure Network (DePIN)
      • GPU Sharing Model
      • Incentive Mechanisms
    • AI OmniChain
      • Layer 1 and Layer 2 Integration
      • AI Model Marketplace and Interoperability
    • DualProof Consensus Mechanism
      • Proof-of-Work (PoW) for AI Compute
      • Proof-of-Stake (PoS) for Validation
    • OMNIT Token
      • Overview
      • Utility
      • Governance
  • Tokenomics
    • Token Allocations
    • Token Locks
    • ERC20 Token
    • Audit
  • OmniTensor Infrastructure
    • L1 EVM Chain
      • Overview & Benefits
      • Development Tools & API
    • AI OmniChain
      • Interoperability
      • Scalability
      • Decentralized Data & Model Management
    • Nodes & Network Management
      • AI Consensus Validator Nodes
      • AI Compute Nodes (GPUs)
  • Roadmap & Updates
    • Roadmap
    • Future Features
  • PRODUCTS
    • AI Model Marketplace
    • dApp Store
    • Data Layer
    • Customizable Solutions
    • AI Inference Network
  • For the Community
    • Contributing to OmniTensor
      • Sharing Your GPU
      • Data Collection & Validation
    • Earning OMNIT Tokens
      • Computation Rewards
      • Data Processing & Validation Rewards
    • Community Incentives & Gamification
      • Participation Rewards
      • Leaderboards & Competitions
  • For Developers
    • Building on OmniTensor
      • dApp Development Overview
      • Using Pre-trained AI Models
    • SDK & Tools
      • OmniTensor SDK Overview
      • API Documentation
    • AI Model Training & Deployment
      • Training Custom Models
      • Deploying Models on OmniTensor
    • Decentralized Inference Network
      • Running AI Inference
      • Managing and Scaling Inference Tasks
    • Advanced Topics
      • Cross-Chain Interoperability
      • Custom AI Model Fine-Tuning
  • For Businesses
    • AI Solutions for Businesses
      • Ready-Made AI dApps
      • Custom AI Solution Development
    • Integrating OmniTensor with Existing Systems
      • Web2 & Web3 Integration
      • API Usage & Examples
    • Privacy & Security
      • Data Encryption & Privacy Measures
      • Secure AI Model Hosting
  • Getting Started
    • Setting Up Your Account
    • Installing SDK & CLI Tools
  • Tutorials & Examples
    • Building AI dApps Step by Step
    • Integrating AI Models with OmniTensor
    • Case Studies
      • AI dApp Implementations
      • Real-World Applications
  • FAQ
    • Common Questions & Issues
    • Troubleshooting
  • Glossary
    • Definitions of Key Terms & Concepts
  • Community and Support
    • Official Links
    • Community Channels
  • Legal
    • Terms of Service
    • Privacy Policy
    • Licensing Information
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On this page
  • 1. Expansion of AI Grid as a Service (AI-GaaS)
  • 2. Scaling the Decentralized Physical Infrastructure Network (DePIN)
  • 3. New AI OmniChain Capabilities
  • 4. DualProof Consensus Mechanism Enhancements
  • 5. OMNIT Token Utility Expansion
  • 6. AI dApp Marketplace Evolution
  • 7. Privacy & Security Innovations
  • 8. Gamification and Community Engagement
  • 9. Long-Term Vision: AI for Web3
  1. Roadmap & Updates

Future Features

1. Expansion of AI Grid as a Service (AI-GaaS)

OmniTensor is extending its AI Grid as a Service to support more advanced AI models and wider applications, including:

  • AI Model Integration

    Growing the range of pre-trained models in the AI marketplace to incorporate emerging models like large-scale language models, generative adversarial networks (GANs) and AI for predictive analytics.

  • AI Model Fine-Tuning

    Offering more flexible customization options, giving businesses and developers greater control over fine-tuning pre-trained models with parameters like hyperparameters, batch sizes and training cycles.

  • Interoperability

    Adding integration with more blockchain networks and decentralized ecosystems to facilitate cross-chain AI services beyond the OmniTensor ecosystem.

2. Scaling the Decentralized Physical Infrastructure Network (DePIN)

To meet the rising demand for AI computation:

  • DePIN Expansion

    OmniTensor is decentralizing its computational infrastructure further by adding more geographic locations and supporting both GPU-based and alternative compute solutions, including quantum computing.

  • GPU Resource Utilization

    Introducing smarter resource allocation techniques to optimize the distribution of computational tasks across the network based on real-time demand and availability.

  • Mobile AI Compute

    Developing AI inference capabilities on mobile and edge devices, allowing more users to contribute computational resources, further expanding the network’s scalability.

3. New AI OmniChain Capabilities

The AI OmniChain, which focuses on decentralized AI processing, will receive substantial updates:

  • OmniChain 2.0

    Upgrades to the Layer 2 infrastructure will improve scalability and throughput, enabling faster transactions, better data validation and support for larger datasets.

  • Decentralized Model Governance

    Implementing community-driven governance protocols for AI model validation and selection, ensuring transparent decision-making about which models are added.

  • AI Smart Contract Library

    Launching a standardized AI-specific smart contract library to automate tasks such as deploying, validating and monetizing AI models across industries.

4. DualProof Consensus Mechanism Enhancements

Planned improvements to the DualProof consensus mechanism include:

  • Efficiency Updates

    Refining the Proof-of-Work (PoW) for AI computation and Proof-of-Stake (PoS) for validation, aiming to reduce energy usage and improve overall efficiency.

  • Adaptive Security

    Strengthening the security protocols to dynamically adjust to network conditions, identifying and addressing threats such as Sybil attacks or malicious behavior without sacrificing performance.

5. OMNIT Token Utility Expansion

As part of OmniTensor's growth plan:

  • Token Use Case Expansion

    Extending the applications of OMNIT tokens within and beyond the ecosystem, with deeper connections to decentralized finance (DeFi), NFT marketplaces and AI-powered decentralized apps (dApps).

  • Staking Updates Expanding staking options to offer more flexibility and higher rewards, with incentives based on participation in governance, model validation, or GPU contributions.

6. AI dApp Marketplace Evolution

The marketplace will undergo changes to encourage developer creativity:

  • AI dApp Ecosystem Growth

    Incentivizing third-party developers to build AI-driven dApps on OmniTensor’s platform, focusing on areas like healthcare, finance, and autonomous systems.

  • Developer Incentives

    Launching new reward programs for developers, including multipliers for early adopters or dApps that address key market needs.

7. Privacy & Security Innovations

  • Decentralized Data Privacy

    Enhancing privacy features through decentralized data encryption and zero-knowledge proof (ZKP) techniques, ensuring data and AI model processing remain secure.

  • Private Cloud Options

    Allowing enterprises to use OmniTensor’s decentralized infrastructure to deploy AI solutions privately, offering more control over sensitive data and critical AI applications.

8. Gamification and Community Engagement

  • Gamification Elements

    Increasing community participation through leaderboards, AI competitions, and token rewards for contributors involved in model training, data validation, or running network nodes.

  • Educational Programs

    Offering educational content, hackathons, and developer toolkits to bring new developers into the OmniTensor ecosystem, supporting ongoing growth and knowledge exchange.

9. Long-Term Vision: AI for Web3

OmniTensor aims to establish itself as the primary AI infrastructure for Web3, focusing on areas such as decentralized autonomous organizations (DAOs), AI-powered governance, and decentralized identity systems built with AI.

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Last updated 7 months ago