AI Compliance
AI Compliance Server Configuration
This article details the server configuration required to ensure AI compliance within our MediaWiki environment. These configurations are crucial for handling data used in AI-powered features like content summarization, search enhancements, and automated moderation. Failure to adhere to these guidelines may result in legal and ethical violations. This guide assumes a basic understanding of Server Administration and MediaWiki Installation.
Overview
The increasing integration of Artificial Intelligence (AI) into our MediaWiki platform necessitates a robust server configuration focused on data privacy, security, and auditability. This configuration addresses key areas including data storage, processing power, access control, and logging. It's intended to assist System Administrators in maintaining a compliant and responsible AI infrastructure. We will focus on specific hardware and software requirements to meet current regulatory standards, such as GDPR and CCPA. This document details the minimum requirements and suggested best practices. See also: Data Security Policy.
Hardware Requirements
The following table outlines the minimum hardware specifications required for an AI compliance server. These specifications are based on the expected workload of processing data for AI features across our entire wiki.
| Component | Minimum Specification | Recommended Specification |
|---|---|---|
| CPU | Intel Xeon Silver 4310 (12 cores) | Intel Xeon Gold 6338 (32 cores) |
| RAM | 64 GB DDR4 ECC | 128 GB DDR4 ECC |
| Storage | 2 TB NVMe SSD (RAID 1) | 4 TB NVMe SSD (RAID 10) |
| Network Interface | 10 Gbps Ethernet | 25 Gbps Ethernet |
| GPU (for accelerated processing) | NVIDIA Tesla T4 | NVIDIA A100 |
These specifications are scalable depending on the number of active users and the complexity of the AI models employed. Regular Performance Monitoring is essential. Consider future growth when making hardware decisions. See also: Hardware Maintenance.
Software Configuration
The software stack is equally important in ensuring AI compliance. We will be using a combination of standard server software and AI-specific libraries. All software must be kept up-to-date with the latest security patches. This includes the operating system, database server, and MediaWiki itself.
| Software | Version | Purpose |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | Provides the foundation for the server environment. |
| Database Server | MariaDB 10.6 | Stores wiki content and AI-related data. |
| Web Server | Apache 2.4 | Serves MediaWiki content to users. |
| PHP | 8.1 | Back-end scripting language for MediaWiki. |
| Python 3.9 | Used for AI model execution and data processing. | |
| TensorFlow/PyTorch | 2.10 / 1.13 | AI/Machine Learning Frameworks. |
All data processed by AI models must be anonymized or pseudonymized where possible. Utilize libraries like Diffprivlib for differential privacy. Furthermore, all data access must be logged and auditable. See also: Software Updates.
Security Measures
Security is paramount when dealing with data used in AI applications. The following security measures must be implemented:
- Access Control: Strict role-based access control (RBAC) must be enforced. Only authorized personnel should have access to AI-related data and models. Utilize MediaWiki's Access Control List functionality effectively.
- Encryption: All data at rest and in transit must be encrypted using strong encryption algorithms (AES-256).
- Firewall: A robust firewall must be configured to restrict network access to the AI compliance server.
- Intrusion Detection System (IDS): An IDS should be implemented to detect and respond to malicious activity.
- Regular Security Audits: Conduct regular security audits to identify and address vulnerabilities. See also: Security Best Practices.
Logging and Auditability
Detailed logging is crucial for demonstrating compliance and investigating potential issues. All AI-related activities must be logged, including:
| Log Event | Description | Retention Period |
|---|---|---|
| Data Access | Records all access to AI-related data. | 2 years |
| Model Training | Logs the training process of AI models. | 1 year |
| Model Deployment | Records the deployment of AI models. | 1 year |
| Data Modification | Logs any changes made to AI-related data. | 2 years |
| AI Prediction | Logs the prediction results generated by AI models. | 6 months |
These logs should be securely stored and regularly reviewed. Consider using a centralized logging system like Elasticsearch for efficient log management and analysis. See also: Log File Analysis. Ensure compliance with Data Retention Policies.
Further Resources
- MediaWiki API
- Database Administration
- Server Backup and Recovery
- Troubleshooting Guide
- Contact Support
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️