Artificial Intelligence Laboratory for Future Software Developers

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Project Overview

Artificial intelligence and data science studies require a flexible and secure working environment as well as high processing power. As Mega Computer, we have designed a scalable and isolated Artificial Intelligence Laboratory ecosystem where students and academics can develop their projects to modern world standards.

Solutions Offered and Implementation

Containerized Infrastructure and Automation:

The entire development environment is built on a Docker server infrastructure. GitHub Image integration automates software development processes, enabling users to develop quickly.

Flexible Workspaces:

Users are offered both public and private project spaces, establishing a balance between collaboration and privacy.

Centralized Data and Security:

Data sharing processes are optimized with NFS (Network File System), ensuring files are accessible from anywhere.

All system security and user authorization are protected in a centralized structure with LDAP integration.

Advanced AI Assistant:

As the most innovative step of the project, the Co-Pilot application was optimized specifically for the university environment. This provided students with intelligent support during the coding phase, in line with corporate standards.

Ready-made and Customized Images:

To prevent users from wasting time with complex installations, a library of ready-made images containing popular libraries and institution-specific images was prepared.

Results Obtained

Fast Deployment:

The installation time of an AI development environment was reduced from hours to minutes.

Cyber ​​Security:

Thanks to LDAP and isolated image structure, 100% data security was ensured in the university network.

Innovation in Education:

A unique AI-supported (Co-Pilot) academic work environment, rarely seen in Türkiye, was implemented.

It was passed.

One ​​of Türkiye's most modern AI development centers has been established with Co-Pilot integration.

Details:

  • NVIDIA GPU Models and Kubernetes/Docker Capabilities.

Technical Infrastructure:

  • NVIDIA A100 and RTX 6000 Ada Generation GPU cards were used in the system for high-density computing/artificial intelligence (HPC/AI) needs.

Software and Standards:

  • High availability was ensured by using Docker and Kubernetes architecture in containerization processes.

Results Obtained:

  • An infrastructure meeting NVIDIA Certified Systems standards, necessary for academic studies, has been provided, and with Co-Pilot integration, one of Türkiye's most modern AI development centers has been established.