Artificial Intelligence, Take 2 : Part 1
“Artificial intelligence is the future.”
“Artificial intelligence is the new cool.”
I’m sure we’ve all heard variations of these statements. Artificial intelligence, popularly referred to as ‘AI,’ is that shiny toy that everyone wants to play with, and it’s understandable. People aren’t overstating things when they claim that AI is the future. It’s already shaping much of the present and will be even more integral in the years to come. It will permeate every facet of our lives, and companies that will be slow to adapt will go the way of the dinosaurs. This makes AI very exciting to many, the prospect of being ahead of the curve is alluring, and it really is cool. Every day, there are countless people googling “How to start learning artificial intelligence”, and in the not too distant past I was one such person.
I’ve always been into science fiction movies so I was introduced to the concept of AI quite early. One such movie, ‘I, Robot’, piqued my intellectual curiosity and made me think about what a future with artificial intelligence could be like. Hal from ‘2001: A Space Odyssey’ kind of scared me, and I fell in love with R2-D2 and C-3PO after watching ‘Star Wars: The Phantom Menace’ (it’s a good movie, and I’m willing to die on this hill). AI has fascinated me ever since.
Growing up, AI was basically synonymous with sentient robots to me. My imagination was rife with thoughts of creating some cool AI that was going to change the world (lol). I just unlocked a high school memory as I was typing this — my friend, Ahenkan, and I were plotting how we’d create an AI that would rival Tony Stark’s J.A.R.V.I.S. We dubbed it art.i (pronounced as ‘arty’. Cool right?). I had a very narrow view of what constitutes AI and naively thought everything would be glamorous. Quora(A question and answer website where people go to find information.) disabused me of that notion when I was finally ready to learn.
The first thing that struck me was that it included a lot of math (facepalm). I felt betrayed and almost decided to shelf my plans then and there. I felt like I did not have a … solid relationship with math. I liked linear algebra and basic statistics well enough, but the thought of going through calculus again was quite unpleasant. I decided to soldier on anyway. I’m sure a lot of people quit when they find out the amount of math involved, and I don’t blame them.
The next thing that struck me was how large the field of AI is. AI encompasses a lot of things. There’s machine learning, natural language processing, computer vision, speech processing, robotics, etc. I wasn’t sure where to start, but I wanted to learn everything.
I decided to get some books to read but I couldn’t stick with any. I dumped them after the introductory chapters. I felt that they were not exciting enough.
After that I queried ‘artificial intelligence tutorials’ on YouTube and somehow ended up watching a machine learning playlist. I planned to watch all the videos in the series, but I ended up skipping some I thought would not be interesting, I also watched the videos passively sometimes. After some time, I found myself watching the videos less regularly. Eventually I quit watching them altogether in favor of another playlist, which was a different field of AI — Deep learning.
It should come as no surprise that I stopped watching that also, this time in favour of looking at and experimenting with code that others had posted online. Through all this, I didn’t really tackle any of my math deficits. I just glossed over them.
So what happened after that? Take a guess.Yeah you guessed right… I stopped doing that as well. I told myself that I would pick up learning AI again imminently but days turned into months, and months turned into a year. I had some guilty pangs every now and then, and it didn’t help that at work, I was surrounded by in-house products that make use of AI. For instance, we have a customer support chatbot that make use of conversational AI and natural language processing, a recommendation engine that establishes trust between users to provide relevant recommendations, and others. So what went wrong? This was something I was really interested in after all.
I’ll say it was down to my haphazard approach to learning. I made a mistake right from the jump, and it ended up putting me off later. I should have put more effort to see what’s out there and chosen a field to focus on. It’s impossible to learn everything.
After identifying my field of interest, I should have taken a good look at the kind of math that would have been required and then proceeded to cover my bases, and after that I should have set an achievable goal and created a plan for it. The next thing would be sticking to the plan and persevering. That way, it would be easy to track my progress and give myself a lift when things got tough.
I’ve decided to start afresh and take another stab at AI, and this is the approach I’m going with. This is a first of a series of posts that will chronicle my journey. Hopefully, the next couple of months will tell a much better story.
May the force be with me, and unlike LL Cool J — call it a comeback.
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