What is AI?

What exactly is artificial intelligence (AI)? According to the movies, it is either a sentient system, an intelligent machine that can build realities and trap humans, or some other form of advanced humanoid that eventually develops feelings. While these examples are works of fiction (and extreme), AI is something you don't have to be afraid of. Once you have completed this course, you will realize that AI is just a multi-purpose tool in your toolbox (albeit a very powerful one) that can help you succeed throughout your time here at Wayne State. 

So, let's start off by defining AI. According to Google, AI is a technology that enables computers to perform a variety of advanced functions. It can translate languages, analyze data, make recommendations, and much more. AI's actual definition is "a field of science concerned with building computers and machines that can reason, learn, and act in such a way that would normally require human intelligence or that involves data whose scale exceeds what humans can analyze."

Commonly used terms

You will hear a lot of different commonly used technical terms when talking about AI. So, it will be good to keep these definitions in mind:

• Automation: Making a process or system operate automatically - independently, without requiring human input.
• Algorithm: A finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation.
• Bias: Assumptions made by an AI system in order to simplify the process of learning and performing the task(s) it was designed for.
• Deep Learning: A subset of machine learning methods based on neural networks with representation learning.
• Deepfake: A piece of media created by deep learning or other AI technology to misrepresent reality.
• Large Language Model: A neural network with a large number (usually billions) of parameters, with large amounts of text used as its training data. 
• Machine Learning: A field of research focused on how machines can "learn" (i.e., become capable of more and more advanced tasks).
• Natural Language Processing: The study of AI systems can be used to process and generate human language.
• Neural Networks: In machine learning, these are computational models inspired by the structure and function of biological neural networks in the brain.
• Parameter: A variable within an AI system that is used to make predictions.
• Prompt: The user input that a generative AI model responds to.