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AI Resources at ODU CS

Empowering AI Exploration at ODU CS

The ODU Computer Science Department is committed to providing students and faculty with access to cutting-edge Artificial Intelligence (AI) resources. Our offerings primarily focus on Large Language Models (LLMs) and the computational infrastructure needed to support learning, innovative projects, and research in this rapidly evolving field.

Department-Hosted AI Services

ChatCS: Your CS Department AI Assistant

Meet ChatCS!

ChatCS is the CS Systems Group's dedicated AI assistant, designed to help you navigate various ODU CS topics. From getting help with connecting to the VPN, to learning about CS courses and degree options, ChatCS is here to assist!

🚀 Try it out at: ai.cs.odu.edu

Verify Information

Like all Large Language Models, ChatCS can occasionally make mistakes or provide incomplete information. Its knowledge base is primarily derived from this documentation wiki and the official ODU website. Always critically evaluate its responses and verify important details if unsure.

CS AI Service (chat.cs.odu.edu): Access Powerful LLMs

On-Demand LLM Access: chat.cs.odu.edu

To make powerful AI models readily available, the department hosts its own AI service, running various LLMs for you to use.

🚀 Access the service here: chat.cs.odu.edu (ODU CS Account login required)

Key Features:

  • Universal Access: Available to all ODU CS students, faculty, and staff.
  • Simple Authentication: Sign in securely using your ODU CS Account credentials.
  • Diverse Model Selection: Access a variety of LLMs, including models with multimodal capabilities (e.g., understanding images alongside text).
  • User-Friendly Web Interface: An intuitive chat interface, powered by Open WebUI, is directly accessible at chat.cs.odu.edu .

  • Powerful API Access: Integrate LLM capabilities directly into your applications and research projects via an OpenAI-compatible API.

Resources for AI Model Training & Advanced Use

For students and researchers needing more control, or those engaged in AI model training, fine-tuning, or computationally intensive experiments, the department offers dedicated resources.

JupyterLab with GPU Access

:material-jupyter: JupyterLab environments are provided for interactive computing, ideal for developing, training, and experimenting with AI models.

  • GPU Integration: JupyterLab instances are configured to run on the department's GPU servers, providing the necessary computational power for demanding AI tasks.
  • Standard Allocation: All CS students typically have access to a GPU slice and a baseline storage allocation (e.g., 15GB) on these servers.
  • Resource Escalation: Additional GPU time, processing power, or storage can often be allocated upon request, especially for research projects or advanced coursework, subject to availability and faculty approval.

🚀 Access JupyterLab: jupyter.cs.odu.edu (ODU CS Account login required)

Running LLMs Locally (Self-Managed Option)

For users wishing to experiment with smaller models on their personal hardware, or for development workflows that benefit from local execution, several tools are available.

Self-Managed LLMs with ollama

Ollama is a popular tool designed to simplify the process of downloading, setting up, and running LLMs on your own computer.

  • Ease of Use: Relatively straightforward to install and use.
  • Cross-Platform: Runs on macOS, Linux, and Windows.
  • Web UI Integration: Can be integrated with user interfaces like Open WebUI for a chat-like experience with your local models.
  • Local API: Provides an OpenAI-compatible API endpoint (e.g., http://localhost:11434), allowing you to develop applications that interact with models running locally.
  • Model Library: Offers easy access to download a variety of open-source models.

Hardware Dependent & Self-Supported

  • Running LLMs locally is heavily dependent on your personal computer's resources (CPU, RAM, and especially GPU VRAM for larger models).
  • This is a self-managed and self-supported option, distinct from the department-hosted chat.cs.odu.edu service and JupyterLab resources. The CS Systems Group does not provide direct support for personal ollama setups.

Support & Contact

Need Help with Department AI Resources?

For questions, issues, or support requests related to:

  • The CS AI Service (chat.cs.odu.edu)
  • Access to or usage of GPU servers
  • JupyterLab environments for AI work

Please contact the CS Systems Group at root@cs.odu.edu. For course-specific AI resource questions, it's often best to first consult your course instructor or faculty advisor.