Monday

What is 'AI' and where has it come from?

By the end of this day you should be able to: describe AI to a friend


Introduction

9.30-9.40

Watch this short introductory video by Coldfusion: What is Artificial Intelligence Exactly?

The first thing to understand is that artificial intelligence (AI) does not necessarily refer to robots. This video gives a helpful introduction to help you understand what is covered by the term ‘artificial intelligence’.


Robots

9.40-10.40

Read through this research from the Engineering and Physical Sciences Research Council (EPSRC). And now, on another note, take this TED tutorial by Professor Ken Goldberg at UC Berkeley that introduces the 4 Lessons we can learn from Robots about being Human. Do the questions and read through the discussion.

These resources outline some lessons we can learn from the debates surrounding developments in robotics. In a similar way, this week is about finding out what lessons we can learn from AI about being human, and how we can apply those lessons to our working life.  


Why it matters

10.40-11.20

Read this SAS article about why AI matters. Now watch Chris Anderson’s discussion with Sebastian Thrun (CEO of Udacity and the Thrun Lab, which is working on projects like self-driving cars and cancer recognition) on What AI is - and isn’t.

There has been a lot of hype surrounding artificial intelligence and you’ve probably heard stories about how it will change (if not take over) the world. Even if these fears aren’t all realistic, we are certainly facing a period of vast change in our workplaces and our daily lives.This article and video give a quick outline of why AI is important and how it is actually being used today.


AI, ML & DL?

11.20-11.30

Read this article from Nvidia.

Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are often used interchangeably but there are some key differences between these terms that it’s important to understand. This article gives a good summary of the differences.


What's going on today

11.30-12.00

Read this article by Wait But Why and take a look at infographic of the four types of AI that are being developed.

This article is an approachable, interesting overview of what technologies AI scientists are developing today and where they might head in the future.


Machine learning

12.00-12.20

Have a read through this ‘gentle’ guide to machine learning by Monkey Learn.

This article gives a good overview of machine learning: how it works, and what it can do. As you read, think about how this compares to human learning, and what benefits we might gain from combining our particular capabilities.


Visualise

12.20-12.30

Curious to see what this kind of system might look like? Play around with Google’s interactive visualisation of data in an AI system on their ‘AI Experiments’ game site.

This is a useful tool for understanding the internet tags and similar searches that might direct people to and from your website. Try searching for words from your company’s mission statement, zooming in, and mapping out what other words appear in the clusters nearby.


Lunch break


Doodle

13.30-13.45

Now try out Google’s Quick, Draw game to see a learning system in action, and watch how it interprets each stage of your doodles.

Topical and fun, this AI programme was the talk of 2017, and is a good illustration of how machine learning works in practice. It has learnt from the data supplied by users playing and can now finish doodles that humans have started.


History

13.45-14.30

Browse this timeline of developments in computer history. Now read through this Harvard Review article by Rockwell Anyoha on the History of Artificial Intelligence and explore links at the bottom of the page.

Use these resources to write down an answer to this question: what is the difference between traditional approaches to AI (from the time of Turing) and the machine learning of today?

This website and Anyoha’s article will give you an overview of how scientists have historically approached the challenge of AI, and how this has changed in the last few years. This is important because there has been a huge shift in our approach over the last few years with the advent of machine learning. It’s good to know how we got here.


The Turing Test

14.30-15.00

Watch this TED lesson on The Turing Test, follow the exercises and read through the discussion.

The history of the Turing Test is important because it raises questions about our own definition of intelligence. Can intelligence really be defined by intelligent conversation? Or is it more than that? And what does this mean now, after developments in intelligent assistants such as Siri in our phones and Alexa and Cortana in our homes?


TASK

15.00-15.30

Explore this Quora page on Artificial Intelligence to get a feel for the questions people around the world are asking.

Real world experts in the field respond questions on this site so get involved by asking or finding three questions that are relevant to you. For example, how will AI affect your sector? What is the next big development that could affect you? Pages like this are becoming important centres for discussion and it’s good to get use to treating them seriously.


(Still curious?)

This AI podcast from Nvidia has a great range of talks from leading experts, such as Ian Goodfellow from Google Brain, Andrew Ng from Stanford and Baidu, and top scientists from the Nvidia labs.

If you’d like to learn more about robots, explore the Dig Deeper section of the TED Robot tutorial.

For machine learning, this Quora page has some great leads for you to start exploring the issues machine learning scientists and users are considering. You could also have a go at this online course from Coursera.

 
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