I took this photo at the Valencian Summer School in Machine Learning 2018. That was my second Summer School, but my first one as a BigML intern. My internship had just started few days ago. Since I published this tweet last September things changed a lot, but let me provide a context for it.
What happened between both Summer Schools? I realized that almost all my viewpoints about Machine Learning were wrong.
I belong to the most adaptive and agile generation ever. People call us Millennials. We were born during the dot-com bubble, and we lived through the dot-com crash. We saw the first iPhone keynote and the transformation from taxis to Ubers and hotels to Airbnbs. We know hype well, and we’re starting to learn how to separate hype from real value. It was in my first Valencian Summer School, and more specifically, during the Enrique Dans talk, when I decided to unlearn everything I had been told previously about Machine Learning.
I forgot about killer robots, having machines replacing doctors or trying to build KITT. Instead, I started to think about finding patterns in data that can help doctors making decisions, reduce waste of energy or help to save lives by preventing disasters.
In the same way, I forgot about unaffordable GPUs, tons of hours of programming every single line of every single ML algorithm or the frustration of not being able to find the best hyper-parameters for my model. Instead, I started to focus on the problem, not the tool, and let BigML do the rest for me. After all, why shy away from standing on the shoulders of giants?
And that was my philosophy during this internship. I got certified as a BigML Engineer, worked on multiple real-world use cases and created workflows with WhizzML to perform Feature Selection. And then, I met one of those giants to stand on, Jao, BigML’s CTO. With him, I started working on BigML’s backend, called wintermute.
I discovered the benefits of functional programming with Jao, and he even introduced me to the emacs religion! The experience I gained with WhizzML helped me to move forward and abandon the Algol family of languages. Clojuredocs was my homepage during those days, and it still is.
There is an interesting internal project in which I’ve been involved that I would also like to mention. It’s called Neuromancer. With Neuromancer, we can see how well our resources scale, beyond the Big-O notation. It let us test possible optimizations for all BigML’s models.
Looking back, the journey has been long, but this is only the beginning. Now, as a full-time employee of BigML, I will keep contributing to our mission of democratizing Machine Learning as it penetrates all corners of our globe. Just like a bamboo plant, we’ve planted it a while back on stable ground, and we now see a few new bamboo shoots growing each and every day. But, soon enough, when the roots are fully established underground, it will grow as crazy, positively impacting all Millenial careers for decades to come.