Artificial Intelligence

Aims and objectives

Artificial Intelligence (AI) has become a term used widely in various topics. This module will provide an introduction to the different types of AI, the implications of AI to society and what AI research is being done at UQ.

This module will:

explore key concepts such as machine learning, deep learning and neural networks.
outline various ethical implications and misconceptions surrounding AI.
explain ways generative AI tools can be used.
outline what AI related research is occurring at UQ and how students can study AI.

After completing this module, you will:

know how to use AI responsibly in your studies.
be aware that information generated by AI tools should be checked with credible sources.

1. What is artificial intelligence

Technical aspect

Artificial intelligence (AI) is machines behaving intelligently by problem solving or completing tasks. It is a very broad subject that involves computer science, cognitive science, mathematics, philosophy, neuroscience, linguistics and possibly many more.

Interested in learning about machine learning, artifical intelligence and deep learning?

Check out these free resources online:

fast.ai
LinkedIn Learning (requires UQ login)
coursera

Neural networks vs Machine learning vs deep learning

Neural networks

Neural networks is the framework of algorithms that allows machine learning to work and piece together complex data inputs. A neural network takes a range of inputs and weighs them against certain values to create an outcome, it then compares this outcome to the set given to decide what action to take. For example, the AI has been told that an image is of a cat if the result is a positive number, so it puts the image through the neural network which tests and evaluates various data points (does it have whiskers etc. to provide a value for the image and decide).

Machine learning

Machine learning is the ability for machines to learn from data by identifying patterns and to make decisions based on that data.

Deep learning

Deep learning is a more in-depth method of machine learning. It requires more data and analysis, but it learns from previous analyses and applies those lessons to new analyses. Deep learning is what powers most human-like artificial intelligence.

But what *is* a Neural Network? | Deep learning, chapter 1 (YouTube, 19m13s) discusses the basics of what a neural network is and how deep learning occurs in machine learning.