Starting to learn AI, an unexpected opportunity during lock-down.

Unless you’ve left the planet, everyone knows that we’ve all experienced a year of unimagined changes to our everyday life.

The most unexpected change has come from my employer.

I was surprised and genuinely touched to learn about the level of investment they are making towards our education.

Everyone in our company is encouraged to learn and make sure that they level-up on their skills.

At the moment, this means the company is giving everyone permission to dedicate an hour each week to learn a new skill or refresh an existing skill set or capability.

What this has meant for me is an opportunity to do the very thing that I am passionate about, to explore and challenge myself to learn and understand more about how marketing and AI have and continue to converge.

I realised that I should start with the basics since much of what I know about artificial intelligence are assumptions. I had been back-filling the missing pieces of information from various sources. I was not truly informed.

So, I have enrolled on two Coursera courses:-

1) Introduction to artificial intelligence

2) Machine learning

The latter, I started in the summer last year as a way of keeping myself busy when there was nothing to do but drift from a working day to another working day.

It was my way of combatting what felt like ground-hog day during lock-down, when everything around us seemed to be horrendous, the news full of doom and gloom.

I got stuck on the Machine learning course as soon as it started to cover mathematics and algebra. I realised that this course was going to be heavy going. Whilst I had managed to pass the graded exam for the first week, I felt sure that I could not continue the rest of the course without a better understanding of some of the concepts.

I almost gave up at this point.

Enter the company directive for employee learning. I could not believe my luck. Here was my opportunity to level-up on the information that interests me in an official capacity.

I signed up for the course called Introduction to artificial intelligence. It is an online course from Coursera. I can pace the learning in my own time. Usually, I can manage about half an hour to an hour. Because any longer and I find my concentration drifts.

Week 1 covered an introduction to Artificial intelligence. What was interesting was the way some of the guest speakers defined artificial intelligence. Its a lot more than just computers and algorithms than I initially assumed.

It turns out, artificial intelligence is machine learning, and by that, there are three types, supervised learning, unsupervised learning and reinforcement learning. In supervised learning, you have to provide the computer with information or data and teach it to perform the task. The desired outcomes are those you have taught the computer. Unsupervised learning is where the computer has been taught the tasks and can derive a new set of results or learn new tasks independently.

I had initially assumed that the term AI covered everything related to computing, not so. Artificial intelligence covers different types of AI. Applied AI can do specific tasks but not learn new ones. I had always assumed that AI meant computers learned to do new things. Strong AI or generalised AI can combine a series of tasks, some that are unrelated, to teach itself new strategies to derive new results.

I also learned how some of the leading proponents of AI are from different backgrounds, ranging from medical science, automotive to the arts. Not what I had initially imagined, an industry full of data scientists doing mathematical calculations, it seems that, is only a small part of the industry and science of AI.

The example from the arts I learned, IBM Watson at the 60th Grammys showed how computers can learn different types of human emotions from the songs entered into the Grammys. Codifying human emotions means it can then be analysed and show us what comprised the winning songs. Composers can then use this information to create music that will resonate more with their audiences.

In the marketing industry, we can look at how music, speech, images, moving or static can affect us, codify it and use the data to inform new content we produce.

In fact, we’re using AI in new ways to create content. Synthesia, is a new platform that allows content creators to use AI to generate video content with synthetically created actors. Once a human’s face has been mapped and sequenced by a computer, it can then be used to mimic a person speaking. Check it out here: https://www.synthesia.io

This type of Artificial Intelligence or Machine learning is in the field of computer vision. In medicine, computer vision is helping to help doctors detect skin cancers, whilst synthetic actors may seem a little over-engineered, there are also life-saving benefits to the technology.

I am looking forward to finding out more about AI. As I learn new concepts, I hope to share them and write about them in a simple way that I hope is easy to digest.

My company has encouraged us to imagine new possibilities through this learning opportunity.

I have always thought about learning as a life long endeavour, but I had always treated it as a personal journey. It is encouraging to see how progressive my employer is being.

It is also forward-thinking because as I learn about AI. Some of the skills and capabilities of our work is going to be carried out by machines. Co-creation was also covered in the introduction, around the idea that Artificial Intelligence isn’t about taking away people’s jobs but enhancing our capabilities to do more.

It means that new and previously unthought of applications for AI will open up new opportunities for people and business.

We owe it to ourselves to learn how to co-create with not just colleagues but with AI. It means we can use our abilities and skillsets in new and exciting ways.