Generative AI (GenAI) is a general term for artificial intelligence that creates new content by generating new data samples that are similar to the training set. These generative models learn patterns, structures, and features from the input data and can create content with similar characteristics.
GenAI can be used to create text, music, and images that mimic human creation with varying degrees of success. Currently, the most well-known GenAI applications are sophisticated chatbots that have been trained on an enormous collection of text data to develop an understanding of the patterns and structures of human language. The model behind natural language processing chatbots, which rely on that vast collection of text, is called a “large language model” (LLM).
LLMs have been trained on digitized books, articles, websites, and other types of text to learn patterns in natural and written language. In response to prompts from users, AI models such as ChatGPT can generate text that is coherent and convincingly human-like in seconds. It can summarize historical events, write an essay or basic computer code, translate a passage, or even compose poetry and songs. Examples of uses that have already emerged include using it as a research assistant, a proofreader, a brainstorming aid, a calculator, and many more. However, outputs fall short of demonstrating the higher levels of learning needed to succeed in a rigorous college setting. Additionally, it’s also sometimes wrong, and with great confidence. For these reasons, it is important to keep a human-in-the-loop approach and carefully scrutinize all outputs from LLMs.
ITS offers a generative AI platform available to all active U-M faculty, staff, and students on the Ann Arbor, Flint, and Dearborn campuses and Michigan Medicine. These service offerings, which include U-M GPT, U-M Maizey, and U-M GPT Toolkit, are secure, private, equitable, accessible, and free. They support everything from basic consumer usage to advanced research and experimentation.
GenAI In-Depth: The Science and Capabilities of GenAI
Advances in deep learning techniques, specifically transformer architectures, have enabled more powerful and efficient modeling of complex relationships in the data. Learn more...about the science and capabilities of GenAI