As a successful technology entrepreneur, Mick Johnson now leads a startup spanning Sydney and San Francisco's Silicon Valley in tackling one of the hardest problems in natural language processing and artificial intelligence.
Graduate Mick Johnson (BSc(Hons) ’03) is currently the CEO and co-founder of Lexy, a startup with 14 people in Sydney and San Francisco's Silicon Valley, working on one of the hardest problems in natural language processing (NLP) and artificial intelligence (AI).
Mick is an entrepreneur with a track record of success. In 2010 he co-founded Whereoscope, a location-aware smartphone app that helped parents keep tabs on their children, which was sold to Facebook and Zynga.
From 2012 to 2013 Mick led the mobile product team at Facebook across iOS, Android and mobile web. The key improvements to the platform helped grow Facebook's mobile usage from 430M to 945M monthly users using 7000 different types of devices. From here Mick led product development for the Search and Language team where his team grew the daily searches from 750 million to over 1.3 billion across mobile and desktop, and developed Facebook's first products in speech recognition and machine translation.
Where did this success start? Mick graduated with the University Medal in Computer Science from the University of Sydney in 2002, where he was also a recipient of the Chancellor's Industry Scholarship in Engineering. In 2015 he received the Faculty of Engineering and IT’s Alumni Award for International Achievement.
Mick talks to us about his many challenging decisions, from the time he chose to study computer science, to passing up a job at Google to persevere with his startup, even though he'd not had a steady wage for a year.
As a startup founder, the only hard limits on what you do are internal – you and your team can go after anything. I love the challenge of getting up every day, trying to build something that will fundamentally change the world, and knowing that we only have ourselves to blame if we fail.
At the time, I wanted to work in photovoltaics. I got a scholarship (CISE) for electrical engineering and planned to do that, followed by a postgraduate degree in solar cells. However, after two years interning at power companies, I found that AI was what I found most interesting and so I switched to computer science.
The sense of camaraderie and fun within the faculty was pretty great. Many of my closest friends are people I met at that time, and funnily enough many of them are also in Silicon Valley these days.
In 2010 I was trying to decide whether to take a job as a Google Product Manager in Tokyo, or stick with my startup and my co-founder to go through YCombinator [which provides seed funding at the earliest stages of a new venture]. I hadn't had a real salary in a year or so and the Google job looked really fun and interesting. But I couldn't let my co-founder down; I knew that if our startup succeeded the opportunity was far greater than anything I could achieve at Google. The lesson for me was that important decisions are never easy and hard choices always come up. But when you come up against a hard choice, just be thankful you are in a place to make that decision.
Engineering and IT will be as fundamental to human life over the next few decades as the written alphabet has been until now. Knowing how to understand and control software systems will be as normal as driving cars is today – ironically an activity that will itself disappear.
Programming AI technology has always been something that required computer science expertise, but as AI gets more and more mature, there will be a massive opportunity to interact with such agents without that expertise. Imagine being a landscape designer instructing a fleet of small robots on how to reconfigure a garden, or being able to customise a piece of clothing to someone's exact dimensions as they stand in front of you. The platforms to bring together specialised AI and robotic labour, such that anyone in the world can use them, still need to be built – hopefully by you!
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