This workshop will provide an introduction to the basics of what an AI (Artificial Intelligence) is and what common uses AI has today. The session will be broken up into two parts:
- A slideshow and discussion section where we will discuss AI
- A "play" section where we will explore some popular free online AI tools like chatGPT and Dream.ai.
No prior experience with this topic is needed for this workshop.
Estimated length of workshop: 1.5 hours
In preparation for this workshop you may optionally create accounts on any of the tools below that you might want to try during the play portion of the session. This can also be done during the session.
- Algorithm - A set of commands or rules that must be followed for a computer to perform calculations or other problem-solving operations. This can be as simple as a decision tree (like a flowchart) or as complex as a set of instructions on how to parse and learn from data.
- Artificial Intelligence - The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
- Computer Vision - Computer Vision refers to methods by which computers can recognize, analyze, and produce descriptions of digital images.
- Data - Data is information that is used for analysis or decision making.
- Big Data - Big Data is a term used for large or complex datasets that are too large to analyze or process via traditional means. This type of data is often continually growing, adding to the complexity of working with it.
- Training Data - Training Data is any data that is used to train a machine learning model or an algorithm. The type, quantity, and quality of the training data determines what outputs the model or algorithm will be capable of producing.
- Generative AI - Generative AI is the term used for deep learning models that create new content as its output. ChatGPT and Dream.ai are both tools that can be described as Generative AI.
- Machine Learning - A type of AI focused on algorithms that allow computers to learn from data to the point that they can make assumptions or "generalizations". This allows computers to perform more complex tasks without explicit instructions or data.
- Deep Learning - Deep Learning is a method of Machine Learning focused on identifying complex patterns from multiple data sources to train neural networks, make predictions, and identify trends across all data sources.
- Neural Network - Neural Networks are a type of Machine Learning modeled after the human brain. This method focuses on creating nodes with pathways connecting them to create vast networks of interconnected data allowing for "intelligent" decision making.
- Large Language Model - Large Language Models (often referred to as LLM's) are tools that are able to process large datasets of text (generally "Big Data" datasets) to generate text based results. Often the output of LLM's is in the form of human-sounding responses or ideas.
- Natural Language Processing - Natural Language Processing (often reffered to as NLP) is a general term to describe AI algorithms and models that give computers the ability to understand human language.
- Sentiment Analysis - Sentiment Analysis (sometimes called "Opinion Mining") is a type of text analysis that uses AI models to identify the "mood" of a piece of text. This process generally results in a determination of Positive, Neutral, or Negative being assigned to pieces of text.
- Token - In AI, a token refers to a single piece or "unit" of data that is processed by an algorithm. Many AI tools use a process called "tokenization" to break apart data into tokens before performing analysis or running algorithms.
Now that you have a basic understanding of AI and the tools that use it, the next step is to explore a variety of options to discover what tools will best support you in what you want to do. Some places that you can start are listed below!
Ithika.org's list of AI tools used by post secondary students and researchers.
This workshop is brought to you by the Brock University Digital Scholarship Lab. For a listing of our upcoming workshops go to Experience BU if you are a Brock affiliate or Eventbrite page for external attendees.