What’s AI, if not just another Software/App?

Someone not from a tech background asked me this question. They, like many others, think that AI is just an app, like ChatGPT, or like many other apps they have been making lately. They think AI is just software that will drive their cars someday, talk to them when they have work to do, or write emails for them by copying from the internet. And I get it—looking at the current appearance of the AI field, it’s easy to think that AI is just another software that will make life better. Maybe it will end up being just another software; who knows? But there’s more to AI than just solving things like many software do.

The person who asked me this question is not alone. They know how passionate I, like many others, am about AI (machine learning) but don’t understand why I do what I do (other than just getting a job and making money). This is my response, which was on the spot, and I thought it was worth sharing. It’s just a reminder to myself of why I love this field and what I want from it in the future. This is for those who want to know why we do what we do…

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Let’s unpack it. Machine learning, in simple terms, is like tapping into the brain’s potential. Imagine scientists creating a vast neural network, feeding it a ton of data, and crossing their fingers for something valuable in return. At first glance, it might seem too basic, almost too simplistic to be considered “science.” But in reality, it’s precisely not that straightforward.

Consider the tools we rely on daily, like ChatGPT or Google Maps, even anything “Google” related—they’re cutting-edge AI. The folks who’ve toiled on these models understand their potential and, to some extent, their limitations.

Yet, despite its seeming simplicity, machine learning is a marvel. Unravel these models, and you’ll uncover layers upon layers of intricate mathematics at play. Even those with just a smidge of mathematical intuition find themselves captivated.

Take this: a machine that breathes, learns, explores, stumbles, perseveres, and occasionally falls flat—all through millions of mathematical equations. And when it completes its journey, it births this colossal equation that’s beyond human comprehension, let alone replication.

We witness its breath, not with our eyes, but through the lens of mathematics. I’m not exaggerating; this is genuinely exhilarating. Think about it—wouldn’t you be thrilled if I offered you a glimpse of Jupiter’s moons through a powerful telescope? It’s a similar sensation.

So, it’s not merely about “selecting a good model.” It’s about unraveling the intricacies of our world, akin to peering through a telescope at distant stars. It’s not just about using an app that performs tasks; it’s a meticulously trained, multi-dimensional, data-eating, multiprocessing, trailblazing, door-blowing brain that is poised to decipher the universe on behalf of us, humans!

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