Don’t know your Supervised from your Unsupervised learning? Do you have your Neural Networks in a not? Fear not, in today's podcast,  Dan and Lee navigate the types of learning that machines can do and how these algorithms work and their application. 

In this episode Dan talks through the machine learning process.  What steps do we need? What data do we collect?  And why does thinking about alcohol make this easier?

Have you ever wondered about what makes a bot tick?  How do you go about setting up a conversational agent in your organisation and what are the benefits to you and your customers/students and staff?  In today's episode we take a look at how to create one and the considerations when doing so.

Microsoft Bot Framework: https://dev.botframework.com/

Microsoft QnA maker:https://www.qnamaker.ai/

The Turing test:  https://en.wikipedia.org/wiki/Turing_test

Chatbot in action: https://news.microsoft.com/en-au/2018/12/03/cloud-and-chatbot-free-up-it-service-desk/

Qbot in education: https://www.cloudcollective.com.au/bots-for-education/

• Microsoft shares their work on a new Super computer in Azure https://blogs.microsoft.com/ai/openai-azure-supercomputer/
• CPU vs GPU explainer -  Mythbusters Demo GPU versus CPU

Keeping the theme of education and learning, this episode will provide a look back, way back in to the human obsession with creating artificial replicas of themselves. When did it start, who started it, what is the AI winter and how did it accelerate so quickly in the last 10 years. 

• Talos: https://greekmythology.wikia.org/wiki/Talos
• Issac Assimov - https://en.wikipedia.org/wiki/Robot_series
• Uncanny Valley -https://en.wikipedia.org/wiki/Uncanny_valley
• Bayes Theorem -  https://en.wikipedia.org/wiki/Bayes%27_theorem
• Rossums Universal Robots -  https://en.wikipedia.org/wiki/R.U.R.
• Alan Turing published a landmark paper  in 1950 to introduce elements of AI
• Enigma and cryptography- https://en.wikipedia.org/wiki/Cryptanalysis_of_the_Enigma
• The Dartmouth Conference of 1956
• The Turing Test was the first serious proposal in the philosophy of artificial intelligence
• The AI Winter - https://en.wikipedia.org/wiki/AI_winter

In this introduction to Season 3 we meet our new co-host Lee Hickin.  We also look at what inspired him to get into technology and also look at some of the topical news around pandemic apps, the sharing of data and even play some tic-tac-toe with a WOPR.

Covid Safe app information - https://www.msn.com/en-au/news/techandscience/experts-explain-why-theyre-not-worried-about-covidsafe/ar-BB13oBVC

Paper on contact tracing - https://arxiv.org/pdf/2004.03544.pdf

Ai for Health - https://blogs.microsoft.com/on-the-issues/2020/04/09/ai-for-health-covid-19/

Dan spends 5 minutes reflecting on the last 14 episodes of series 2, before we take an Easter break.  

Mark Stanley from Literatu meets the podcast in our new online-only studio to talk all things Machine Learning and Artificial Intelligence.  We look at how data generally, and NAPLAN data specifically, is used to predict outcomes and how cutting edge Machine Learning can be used to improve writing skills for students, at any level - from primary school years up to undergraduate level.

For more information on Literatu and Scribo: https://about.literatu.com/

Recorded live during the ISQ Educational Data Symposium in Brisbane, Queensland, this podcast takes a new approach. We talk about data and whether we need standardised testing, and then dive into answering questions from the audience about everything from predicting student progress, to how AI can help in the administration of a school. It's our six month anniversary podcast, and a really deep conversation that takes us back to the Hype versus Hope discussion!

And right at the end, Dan makes it clear that we don't know all the answers, and the podcast has been a journey of discovery for us too

Adrian Tyson is co-founder of Neuranext, a company that is passionate about helping students develop their understanding of AI technology, AI ethics and the implications for us. In Australia they run workshops for teachers and students to explain how AI works with hands-on exercises to help prepare them for the future. We talk about self-driving cars, and what that means for students, and the fact that 'seeing is believing' is no longer true, with the advent of deepfakes. And we examine which careers will be affected by AI - including the future for teachers!

You can find more about Neuranext at https://www.neuranext.ai

It's also history making - it's the first podcast episode where we had to reach for the bleep machine!

During the podcast, we also look at  https://www.thispersondoesnotexist.com/ and https://thishorsedoesnotexist.com/