Welcome to The Art of Computing!
As part of a general overview to the course, let’s discuss a piece of recent computing news – a summary of breakthroughs in artificial intelligence by MIT Technology Review – in the context of what you will learn this semester.
First and foremost, the article focused on a few particular breakthroughs in machine learning, “a scientific discipline that explores the construction and study of algorithms that can learn from data”. The particular breakthroughs are in understanding unstructured content, such as text and images. For thousands of years, written communication has been the means for ideas and knowledge to transcend space and time. It is also been known that human vision accounts for 70% of the data flowing into the central nerous system[1]. Automated understanding of pictures and langauge has been long-standing challenges in artificial intelligence, that they have been dubbed “AI-complete” – and making strides in such difficult problem is why these breakthroughs are exciting.
In week 4 of this class, you will learn a method to perform sentiment analysis, i.e., automatically deciding the (positive or negative) emotion expressed by a piece of text. In week6 of this class, you will learn the principles of machine learning, as well as one particular algoirthm called decision trees.
In addition, the article mentioned emerging applications in analyzing genetic databases, and choosing personalized treatment plans. In week 5 of this class, we will cover the basics of analyzing genome sequences, and in week 6, the computer learns to diagnose a disease from medical test results.
Last but not least, the article mentioned new design of computer chips that mimic human brain functions. In weeks 12-15, we will remove the ‘magic’ behind the physical complexity of a computing for you, by teaching you how to build one from scratch : )
Finally, we hope this discussion has given you a fair understanding about how different parts of the class, and the idea of computational thinking, connects to everyday life and the forefront of computing research.
For those who are still curious, here are some pointers to related work in and around ANU for you to explore further.
Research on the methods and applications of machine learning.
Resarch on optimization, decision making and planning.
Research on computer Vision and Robotics.
Analyzing text in legal claims and new machine learning methods for text representations.
Machine learning for genome and medical data.
Machine learning for social media and online photos and video.
Other cool applications of AI and machine learning, including traffic and transportation, looking over water pipes, predicting solar power, or designing energy systems, increasing social resilience, optimizing logistics and supply chains.
We wish you a fun and rewarding semester 1!
[1] Encyclopedia of Optical Engineering, Volume 2, edited by Ronald G. Driggers