AI Framework Support
The iExec Platform provides comprehensive support for popular AI and machine learning frameworks. Deploy confidential AI with ease. iExec supports popular AI/ML frameworks, running in secure Trusted Execution Environments (TEEs) with optimized configurations.
Quick Start
Want to get started immediately?
- 📚 AI Frameworks Hello World - Ready-to-use Docker examples for TensorFlow, PyTorch, and more
- 🛠️ Build & Test - General iApp development guide (not AI-specific)
- 🔬 TDX App Guide - Build TDX applications (works well for AI workloads)
Why iExec for AI?
Confidential Computing
Trusted Execution Environments (TEEs) protect your AI models and data end-to-end:
- Data Privacy: TEEs isolate AI computations in secure Trust Domains
- Secure Training & Inference: Unauthorized entities can never access your models and data
- Hardware-Level Security: Intel TDX provides enterprise-grade protection
AI Monetization
Monetize your AI assets easily and securely:
- Datasets: Encrypt and sell access to your training data
- Models: Deploy and monetize your trained AI models
- Agents: Create and sell AI agents and applications
- Ownership Preserved: Your digital assets always remain yours
Decentralized Infrastructure
Scale AI applications without centralized cloud dependencies:
- On-Demand Compute: Access powerful resources when you need them
- Fair Pricing: Blockchain verifies execution costs transparently
- Global Network: Deploy across a worldwide network of secure workers
AI Framework Support
Overview
| Framework | TDX Support | Best For |
|---|---|---|
| TensorFlow | ✅ Yes (3.01GB) | Deep learning, production ML |
| PyTorch | ✅ Yes (6.44GB) | Research, computer vision |
| Scikit-learn | ✅ Yes (1.18GB) | Traditional ML, data analysis |
| OpenVINO | ✅ Yes (1.82GB) | Computer vision, inference |
| NumPy | ✅ Yes (1.25GB) | Scientific computing |
| Matplotlib | ✅ Yes (1.25GB) | Data visualization |
Framework Details
| Framework | Version | Description | TDX Support | Use Cases | Resources |
|---|---|---|---|---|---|
| TensorFlow | 2.19.0 | Google's ML framework for production AI | ✅ 3.01GB | Deep learning, CV, NLP | Docs • Quickstart • Docker |
| PyTorch | 2.7.0+cu126 | Facebook's research-focused DL framework | ✅ 6.44GB | Research, DL, CV, NLP | Docs • Quickstart • Docker |
| Scikit-learn | 1.6.1 | Comprehensive ML library for Python | ✅ 1.18GB | Classification, regression, clustering | Docs • Examples • Docker |
| OpenVINO | 2024.6.0 | Intel's high-performance AI inference toolkit | ✅ 1.82GB | Computer vision, inference | Docs • Tutorial • Docker |
| NumPy | 2.0.2 | Fundamental package for scientific computing | ✅ 1.25GB | Scientific computing, data analysis | Docs • User Guide • Docker |
| Matplotlib | 3.9.4 | Comprehensive library for data visualization | ✅ 1.25GB | Data visualization, plotting | Docs • Gallery • Docker |
Getting Started with Docker Examples
What's Included
Our AI Frameworks Hello World repository includes ready-to-use examples:
ai-frameworks-hello-world/
├── tensorflow/ # TensorFlow 2.19.0 example
├── pytorch/ # PyTorch 2.7.0+cu126 example
├── scikit/ # Scikit-learn 1.6.1 example
├── openvino/ # OpenVINO 2024.6.0 example
├── numpy/ # NumPy 2.0.2 example
└── matplotlib/ # Matplotlib 3.9.4 exampleQuick Start Commands
bash
# Clone the repository
git clone https://github.com/iExecBlockchainComputing/ai-frameworks-hello-world.git
cd ai-frameworks-hello-world
# Try TensorFlow example
cd tensorflow
docker build -t hello-tensorflow .
docker run --rm hello-tensorflow
# Try PyTorch example
cd ../pytorch
docker build -t hello-pytorch .
docker run --rm hello-pytorchFeatures
- ✅ Isolated Testing: Each framework runs in its own container
- ✅ Reproducible: Consistent environment across systems
- ✅ TDX Ready: All containers tested for Intel TDX compatibility
- ✅ Easy Deployment: Simple build and run commands
Next Steps
Learn TEE Technologies
- Intel TDX Technology - TDX advantages for AI
- Introduction to TEE Technologies - TEE foundations
Build AI Applications
- Build & Test - Build and test your AI application
- Deploy & Run - Deploy and run your AI application
- Build Intel TDX App - TDX applications for AI workloads
- Inputs - Handle data inputs
- Outputs - Handle data outputs flow in TEE environment
Explore Examples
- AI Frameworks Hello World - Ready-to-use Docker examples
- iExec Discord - Community support