Artificial intelligence (AI) is a rapidly evolving technology spreading across the medical education landscape, health care landscape and beyond. As such, WVSOM initiatives are exploding at a brisk rate. To support this movement, we are working to develop and provide extensive resources for students, faculty and staff as well as focusing on projects in multiple areas across campus such as academics (e.g. admissions, teaching, assessment, evaluation), human resources, business/finance, community relations, marketing, clinical, etc. Resources can be accessed clicking the following icons.
AI For Students
AI for Employees
WVSOM has been working diligently to create the infrastructure, foundation, training materials, and resources for employees and students. The current initiatives (as of July 17, 2025) happening as part of strategic planning and the AI taskforce are:
Artificial Intelligence (AI) is a branch of computer science and refers to any sort of intelligence exhibited by an artificial system, like a computer or machine, as opposed to a living being. AI can encompass anything from a pocket calculator to an intelligent artificial agent. AI systems use hardware, algorithms, and data to create “intelligence” to do things like make decisions, discover patterns, and perform some sort of action. AI is a general term and there are more specific terms used in the field of AI. AI systems can be built in different ways. Two of the primary ways are: (1) through the use of rules provided by a human (rule-based systems); or (2) with machine learning algorithms. Many newer AI systems use machine learning.
Citation: Fusco, J. (2020). Book Review: You Look Like a Thing and I Love You. CIRCLEducators Blog. Retrieved from https://circleducators.org/review-you-look-like-a-thing/. Used under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
Most uses fall under the concept of Generative AI - a specific type of artificial intelligence system that generates new text, images, or other media in response to prompts. Notable generative AI systems include ChatGPT, Microsoft 365 Copilot, and Google Gemini.
It is a broad area of computer science focused on creating systems that can perform tasks that typically require human intelligence. This includes things like recognizing speech, making decisions, understanding languages, and recognizing patterns or objects.
From simple tasks like recommending a product on eBay to complex ones like driving a car (eg: Tesla), doing human-like activities like walking, jumping and navigating (eg: Atlas robot by Boston Dynamics) and understanding or generating human-like text (eg: ChatGPT). AI is reshaping how we live and work, aiming to perform tasks better and faster than humans in some areas.
Generative AI, or GenAI, refers to AI models that can create content, it can be text (eg: ChatGPT), images (eg: DALL-E), music (eg: MusicLM), design (eg: Uizard), etc.
Generative AI uses generative models in order to produce outputs similar to the input data they were trained on. For instance, after studying a set of photographs, a generative model can begin to produce new photographs that look as if they could belong to the original dataset, even though they are entirely new creations.
Machine Learning is a subset of AI where machines learn to perform tasks by analyzing and learning from data. Unlike traditional programming, where rules are explicitly coded, machine learning allows the system to learn and improve from experience based on reward function (eg: in the chess-playing model the training reward function would be win/loss). It’s like teaching a child to ride a bike; instead of instructing every movement, the child learns through practice.
Type of AI in the text generation area. You can think of it as text generators that were trained to produce text and fine-tune it to be able to answer your questions. It involves teaching a computer model to understand, predict, and generate human language by feeding it a large amount of text data. This process enables the model to understand context, nuance, and even the subtleties of different languages.
In addition, Natural Language Processing (NLP) – Natural Language Processing is a field of Linguistics and Computer Science that also overlaps with AI. NLP uses an understanding of the structure, grammar, and meaning of words to help computers “understand and comprehend” language. NLP requires a large corpus of text (usually half a million words). NLP technologies help in many situations that include scanning texts to turn them into editable text (optical character recognition), speech to text, voice-based computer help systems, grammatical correction (like auto-correct or grammarly), summarizing texts, and others.
GPT is like a highly intelligent machine that has read a vast amount of text. It’s a type of AI that can understand and generate human-like text based on the input it receives. Imagine it as a super-smart assistant who has read everything on the internet and can help you write and analyze emails, articles, documents, and others!
ChatGPT is a specific application of the GPT model, designed primarily to communicate with humans. Think of it as a chatbot on steroids. It’s not just about answering questions – ChatGPT can hold a conversation, provide explanations, and even showcase a sense of humor, making interactions smoother and more natural.
AGI is the holy grail of AI research. While current AI specializes in specific tasks, AGI aims to create models with the ability to understand, learn, and apply knowledge in a way that’s similar or even better than human intelligence. It’s like comparing a calculator (which excels in math) to a genius who can excel in everything.
The timeline for achieving AGI is highly uncertain and a subject of much debate among experts. Predictions vary widely, with some experts suggesting it could be decades or even centuries away, while others believe the breakthroughs necessary for AGI could occur much sooner.
Text-to-image generation is an exciting AI capability where the model converts written descriptions into visual images. Imagine describing a sunset over the ocean in words, and an AI creates a beautiful image of that scene. It’s a blend of creativity and technology, opening new possibilities in art, design, and communication. Examples of AI-based tools that offer text-to-image generations are DALL-E, Midjournay and Leonardo AI.
Copilot in AI refers to systems designed to assist and augment human abilities rather than replace them. It’s like having a co-pilot in a plane who can handle tasks, provide recommendations and ensure a smooth journey. In software, GitHub Copilot, for example, assists programmers by suggesting code and snippets based on the context of the work.
In the end, these terms represent the tip of the iceberg in the vast and deep ocean of AI. As AI continues to evolve and integrate into various aspects of business and daily life, understanding these basic concepts is a step toward harnessing its potential for innovation, efficiency and growth.
A prompt is an instruction you give to a model. An example of a text-to-text model like GPT is: “What is LLM?” AI generates a response to such a question.
Prompts can range from simple, like asking a question, to complex, requiring the model to generate creative stories, solve problems or even emulate a particular writing style.
AI models learn from data, and if that data has biases, the AI’s decisions and responses can also be biased. It’s like learning from a history book that only tells one side of the story. “Hallucinations” in AI occur when the model generates information that’s not grounded in reality, similar to a person confidently stating facts that are actually untrue. It’s crucial for AI developers to recognize and address these issues to ensure AI behaves as intended.
Many skeptics use AI hallucinations to oppose the new trend but don’t see the big picture where AI tools, such as ChatGPT, are exponentially better with every new version. Also, AI is not at the stage where it replaces people but supports them.
Citation: Radek Grebski, February 2, 2024, 12 Essential AI Terms You Should Know About, Stepwise AI Consulting & Strategy. Retrieved from https://stepwise.pl/2024/02/12/12-essential-ai-terms-you-should-know/