DIY AI Infrastructure Build Your Own Privacy-Preserving AI at Home
AI Summary
Title: Building Your Own AI Model Hosting System
- Introduction to AI and Personalization
- AI is increasingly accessible and can understand natural language.
- Example: Chatbots can provide information on car choices (e.g., gas vs hybrid vs EV).
- Learning to host AI can enhance DIY projects.
- Personal Infrastructure Setup
- Robert Murray hosts AI models like Llama 3 and IBM’s Granite at home.
- High-level overview of his system:
- Operating System: Windows 11 with WSL2 (Windows Subsystem for Linux).
- Virtualization: Docker for container management.
- AI Model Acquisition
- Models downloaded from Ollama.com.
- Examples of models used: Granite and Llama.
- User Interface and Remote Access
- UI managed through Open WebUI for easy interaction.
- Remote access via a VPN configured with a personal domain, allowing access from anywhere.
- System Requirements
- Recommended RAM: At least 8GB (actual use: 96GB).
- Recommended storage: Minimum of 1TB.
- Model sizes varied, between 7 to 14 billion parameters; larger sizes (up to 70 billion) might be slow.
- GPUs: Having GPUs is beneficial, though initial setup was without them.
- Document Management
- Uses a NAS for document storage, allowing secure interaction with personal documents without uploading to cloud servers.
- Security Considerations
- Complete control of infrastructure increases data privacy.
- Open source components mitigate proprietary risks and enhance security visibility.
- Multi-factor authentication adds a layer of security for remote access.
- Conclusion
- The ability to run complex AI models on personal hardware reflects evolving technology.
- Encourages hands-on exploration of technology while ensuring data security.