Fast Five with Alex Mirrington

Before joining Rokt as a Machine Learning Engineer, Alex Mirrington worked as a software engineer and computer science tutor after studying a Bachelor of IT and Computer Science at the University of Sydney. We put these Fast Five questions to Alex to discover why he pursued a study and career path that involves AI.

What appealed to you most about a career in AI?

The thing that appealed to me most about a career in AI was the opportunity to work on complex problems that have no exact solutions. Where we have exact answers to problems like “What’s the fastest way to sort my bookshelf?” or “What’s the shortest path from A to B?”, questions like “What’s the most relevant thing to show to someone right now?” don’t always have perfect answers and need AI to answer them effectively.

What aspect of AI are you most interested in or passionate about?

I’m most passionate about the interpretability and observability of AI in production. There’s no point having a model that is being used to make recommendations about what to show to people if you have no idea how the model is arriving at its final decision – we need AI to be interpretable. In order to be sure that our AI is doing its job, we have to have insights into the latency or accuracy of our productionised models in real-time.

In your daily life, what are the positive impacts of AI that you see playing out in our society?
Over the last decade, we’ve seen AI become a part of our daily lives, whether we’ve realised it or not. From helping us with small daily tasks like decluttering our email inboxes or recommending new shows to watch, to predicting protein structures from amino acid sequences – it’s exciting to think about the benefits that AI will bring to our society in the future.

 

Why do you think it is important to empower young Australians with access to AI education?
In my opinion, it’s important that people have a high-level understanding of the capabilities and limitations of AI, in the same way that they have an understanding of mathematics, language or science. Just like not everyone will be a mathematician, author or scientist, not everyone will necessarily work in AI – but I believe that a fundamental understanding of AI will help people in a multitude of professions do their job better and make more informed decisions in the same way that mathematics, language or science skills do now.


What advice would you give young Australians who want to learn more about and eventually work in AI?

The most important skills you can build if you want to learn about and work in AI are problem-solving, mathematics, and programming. You need to be able to problem-solve to be able to understand the ins and outs of the questions you want to answer, and know whether AI is appropriate to answer them. If AI is a good fit for a problem you’re trying to solve, then you need mathematics skills to be able to create a model architecture that works well for your task at hand. Finally, you need programming skills to be able to implement your model, and make it available for others to use.

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