Fun fact for the fans and followers of GearsNGenes: I love machine learning (in case the title didn’t give it away :D)
In fact, as a sophomore at the Georgia Institute of Technology, I am majoring in CS with a concentration in Intelligence, which focuses on topics in Artificial Intelligence (AI), Machine Learning (ML), natural language processing, and more.
My enamorment with the field of ML started waaaaaay back in the summer before my senior year (summer 2018). I had just accepted an internship at MIT with Professor Pawan Sinha to work on a project involving a particular kind of ML known as a Convolution Neural Network (CNN).
The goal of the project was to see how well a CNN could mimic a human’s ability to identify the face of a person as the images are blurred further and further beyond recognition.
I was, to put it simply, out of my depth with this project. I was drinking from the fire hose, swimming at the deep end. Pick your choice. I had little to no idea what I was doing.
At the time, my only knowledge in coding was with Arduino, yet the project required me to pick up trace amounts of Python on the fly. I also had no prior experience with any of the math needed to understand what was going on inside the CNN. It talked about concepts like convolution, Gaussian blurs, tensors, virtual machines, and so on and so forth.
Never the less, after seeing what my colleagues could do with the CNN once they understood how it worked, I was hooked.
My dad always reflects fondly over one phone call I had with him, where he was comforting me about not knowing everything, to which I responded, “No no, dad. I’m not worried about that. But I am going to murder machine learning! I’ll make sure to get everything I need to practice the field!”
However, not everyone has the opportunity I did to observe and experiment with ML this closely. In fact, observing ML in pop culture, I realize there is a sort of mysticism around the field.
Sometimes its interpreted as the path to “programming people into existence” or as the gateway to the Terminator scenario. Other times it is seen as the next step in automation with self-driving cars. Or some times its associated with the study of “Big Data” and scandals regarding such data, like the relatively recent data distribution scandal from Facebook.
As the significance of AI and ML in our society increases, into more of our daily lives, so does the necessity for public knowledge and easy access to these fields.
One of the biggest goals I have for GearsNGenes is to democratize ML the same way currently I do for physics lab instruments. I started breaking down the intimidating wall of ML for myself in the summer of 2018. Now I plan to lay the path and tools down for everyone to use to explore for themselves.