STM1001: Computer Lab 12B

Data Science Module

Topic 12B: AI and Revision

Welcome to the twelfth and final computer lab for the Data Science module.

Great job getting through the semester! We hope you have enjoyed your time in STM1001, and that the topics covered in the Data Science module have provided you with a taste of the variety of potential pathways one can take as a data scientist.

This computer lab will act mainly as a revision session. However, we will also take a brief look at the wonders of artificial intelligence.

1 Artificial Intelligence

Just as for previous topics such as data visualisation and machine learning, we could have easily spent an entire semester focusing on the ever-evolving world of artificial intelligence.

Artificial intelligence (AI) is a complex and nuanced cutting-edge field of science, with many sub-fields. In general, work in AI focuses on creating systems, or ‘agents’ , that can perceive information in an environment and perform logical actions based on this information (see e.g. Russell (2016)).

A few examples of AI applications include the Google search engine and the Amazon virtual assistant Alexa. In the future, AI robots such as Sophia (who has already been granted Saudi Arabian citizenship) will probably become a ubiquitous part of human life¹. In general though, the future integration and assimilation of AI into every-day activities will probably be less obvious than a physical robot (for better or worse).

Check out this National Geographic article if you would like to learn more about Sophia.

2 AI-generated digital artwork

Developing AIs can involve using advanced statistical algorithms, and therefore is beyond the scope of this subject.

Let’s focus on an interesting application of AI, AI-generated art. Recently, AI-generated art has become a top topic, with AI programs like midjourney and OpenAI’s DALL-E making news headlines (e.g. the midjourney-created digital artwork Théâtre d’Opéra Spatial won the 2022 Colorado State Fair digital art competition).

There are now numerous AI programs for generating digital art. One accessible option is GauGAN2, developed by Nvidia. This AI program can combine text and sketch inputs, along with style specifications and semantic segmentation, to turn a simple sketch into an impressive digital artwork, using Generative Adversarial Networks.

If you would like to try the GauGAN2 program yourself for a bit of fun, click here. You will have to agree to the terms and conditions on the website in order to use the AI. The site is fairly intuitive to use, and also has a tutorial mode.

Figure 2.1 below shows my simplistic drawing (as you can see I didn’t spend very long on it) on the left, and the AI result on the right.

Please note that this website is not an https website. As always, please exercise caution when clicking links. If you are accessing this site on a personal device, please make sure you have up-to-date antivirus software protecting your device.

Figure 2.1: Example images created within Nvidia’s GauGAN2 AI Program.

Give it a shot and see what you can create!

3 Revision

If you would like to spend some of this lab revising material from previous weeks, the links below may be helpful:

Supplementary Material

• Data Visualisation in R supplement

• Foundational Biology for Analyses of Biological Data supplement

• Introduction to Machine Learning in R supplement

Computer Labs

• Computer Lab 1B (Data Visualisation I - Introduction to R)

• Computer Lab 2B (Data Visualisation II - Using plotly)

• Computer Lab 3B (Data Visualisation III - Advanced plotly)

• Computer Lab 4B (Data Visualisation IV - Creating shiny web apps)

• Computer Lab 5B (Simulations in R)

• Computer Lab 6B (Big Data I - Clustering)

• Computer Lab 7B (Big Data II - \(p\)-value adjustments)

• Note Computer Lab 8B was a revision lab

• Computer Lab 9B (Writing R Functions)

• Computer Lab 10B (Machine Learning I - Supervised Learning - Classification)

• Computer Lab 11B (Machine Learning II - Supervised Learning - Advanced Classification)

That’s everything for today!

Thank you for working through all the lab material over the semester. We hope you’ve enjoyed your time learning in this subject.

Please note that there is no solution file for this lab. Make sure to check the LMS for announcements and details regarding assessments.

References

Russell, Stuart. 2016. Artificial Intelligence. 3rd ed..

These notes have been prepared by Rupert Kuveke. The copyright for the material in these notes resides with the author named above, with the Department of Mathematical and Physical Sciences and with La Trobe University. Copyright in this work is vested in La Trobe University including all La Trobe University branding and naming. Unless otherwise stated, material within this work is licensed under a Creative Commons Attribution-Non Commercial-Non Derivatives License BY-NC-ND.

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1. While AI advancements and research may pose ethical concerns, we hopefully won’t have any Terminator or Westworld scenarios to deal with any time soon. I, for one, welcome our new AI overlords. ↩︎