About GenAI

What is GenAI?

Artificial Intelligence (AI) is the field dedicated to creating machines capable of performing tasks that typically require human intelligence. These tasks include learning from experiences, understanding languages, and recognizing patterns. Recently, there's been growing interest in Generative AI (GenAI), an exciting branch that focuses on using AI to create original content such as text, audio, and video. Many tools you may have heard of, like ChatGPT, Claude, and Gemini, are examples of GenAI. Some of these are standalone applications, while others are being integrated into technologies we use daily. The field of AI is rapidly evolving, with new developments emerging constantly.

Given AI's increasing impact on academia and beyond, we encourage our university community—students, faculty, staff, and administrators—to stay informed about these advancements. Bookmark this page and check back regularly for updates on how AI is shaping our university experience and the broader world of education and research.

How Can I Use GenAI?

Generative AI is a tool that can be used to simplify your life. It can be used to simplify or reduce repetitive, rote tasks or quickly create content. It can summarize information, create documents with a certain style or format, analyze text, draw pictures, or carry conversations. For students, you find that GenAI tools will be used to enhance and strengthen your learning experience. There may be appropriate ways for you to use them to assist you with your coursework. Additionally, we anticipate your experience with these tools will better prepare you for your future careers. Please be sure to check with your instructors on how they want you to use these tools in their classes and activities. Learn how to do each of these things using generative AI in our GenAI training library.

How Does GenAI Work?

Generative AI, or GenAI, operates through a model that contains a series of complex algorithms and vast sets of data. The data could be anything from audio clips, text from books, images, or even videos. This data is fed to the model, which then processes and learns from it, understanding patterns, context, and associations.

In the simplest terms, imagine GenAI as a sponge absorbing knowledge. The more data it soaks up, the more it understands. It uses this understanding to create new content similar to what it has learned. For instance, if you input a large number of music files, GenAI could create a completely new melody. If you provided a collection of literary works, it could generate an entirely new story.

It's important to remember that the AI model doesn't truly 'understand' in the way humans do. It isn't creative or imaginative. Instead, it learns patterns and the probability of certain outcomes. It's like the world's most advanced mimic, able to reproduce and combine elements of what it has learned to generate entirely new content.

This learning process is iterative, which means the AI model gets better with each cycle. The more data it is provided, the more refined its output will be. This constant learning and processing is what makes GenAI both exciting and incredibly powerful.

What Are Some Examples of GenAI?

OpenAI’s ChatGPT is a very popular example of GenAI. Other examples include Google’s Gemini, OpenAI’s DALL-E, Adobe Firefly, and many others. GenAI is also starting to be embedded in existing applications like Zoom and Github. Development of GenAI services will continue, and more options for GenAI will continually become available to the public.

Types of GenAI

Text

GenAI services output words after learning or "being trained" from lots of other writing. The services look at how words fit together and use this knowledge of existing patterns to create new text. These services have the ability to modify existing output when users communicate preferences or clarifications through additional prompts.

Code

GenAI services create computer code by learning patterns from existing examples. These services analyze a large dataset of code snippets to understand syntax, structure, and logic. Using this knowledge, the GenAI service generates new code by predicting what would come next based on the input it receives. It uses those predictions to produce functional and contextually relevant code.

Image

GenAI services analyze patterns, colors, and shapes to understand how different elements of images come together. AI platforms combine learned visual aspects to create unique and often realistic images. As users provide feedback and preferences, the service refines its image generation process, adapting to different styles and preferences over time.

Speech & Audio

Speech recognition is a branch within GenAI that focuses on understanding speech and transcribing it into written data. Speech recognition services use algorithms and data to accurately understand voices and conversations. Speech recognition services are already used in many communication platforms. GenAI services are also gaining the ability to mimic or reproduce certain voices. This is done by analyzing vast amounts of recordings to learn how certain voices speak and enunciate language.

Video

GenAI services create videos by anticipating the appropriate transitions between frames and determining the content to be displayed. The services use their acquired knowledge of video sequencing with creative aspects, which was gained from training data. Through user feedback and input, the AI enhances its video generation process, accommodating various styles and preferences.

3D Modeling

GenAI services produce 3D models based on already existing models from the training data. These services analyze shapes, spatial relationships, and structural elements to understand how different components fit together. The services then combine this knowledge with creative input from the user to produce diverse and unique 3D structures. The model is reconfigured as users provide preferences and edits to the generated model.