Generative AI At Purdue University

shaping the future

Explore best practices for leveraging AI while safeguarding university assets and upholding Purdue’s commitment to technology advancement and innovation.

ABOUT GENAI

What is Generative AI?

Generative AI refers to artificial intelligence systems that can generate new content — like text, images, music, videos, and even code — based on the data they’ve been trained on.

Large Language Models (LLMs)

LLMs are a specific type of generative AI that focus on understanding and generating human-like text. They are trained on huge amounts of text data (books, articles, websites) and learn patterns, grammar, and logic. Once trained, they can write emails, summarize text, answer questions, code, or even have conversations.

EXAMPLES

Generative Media Models

Generative media AI models are artificial intelligence systems designed to create or synthesize non-text media content such as images, audio, video, and 3D assets. These models rely on deep learning techniques—like Generative Adversarial Networks (GANs), diffusion models and transformer based models—to generate new, realistic content from prompts or input parameters.

EXAMPLES

Instead of just analyzing or classifying information, GenAI can create something entirely new. While AI can enhance productivity, responsible and ethical use is essential to maintain academic integrity, data security, and institutional standards.

BEST PRACTICES

What are the best practices in generative AI use?

If your organization wants to implement generative AI solutions, consider the following best practices to enhance your efforts.

AI should enhance human capabilities, not replace them. It can help streamline tasks, generate insights, and automate workflows. However, human oversight is essential for ethical, creative, and critical thinking. AI should be utilized as a collaborator.

AI-generated content should be disclosed to maintain integrity and avoid misrepresentation. Protecting data privacy is crucial, requiring strong security measures and compliance with Purdue University policies.

AI improves efficiency but requires fact-checking to ensure accuracy. Cross-referencing sources prevents misinformation. Refining prompts helps generate precise, relevant responses, maximizing productivity while maintaining quality.

AI evolves rapidly, making continuous learning essential. Staying updated on advancements, best practices, and ethical considerations ensures responsible and effective use of AI.