Growing up, I’d been taught by my environment to optimize. Whether that be in terms of project quality, my study schedule, building a desk for my dad’s office, or even my pizza eating style (My friend from Uganda argues that folding it over like a calzone is more efficient than, you know, the normal way), I have an innate drive to plan aggressively for the most optimal means of getting somewhere. There’s no right or wrong; it’s just how I work. One thing I never gave too much thought in high school, though, was optimizing time.
More specifically, time that my future self would be spending—doing activities either for the love of doing it, or for the sake of being on autopilot in a busy, NYC-esque pool of day-to-day commuters. Maybe it was because from the standpoint of loading up my LinkedIn with truckloads of experiences just to get into college, and not for building actual skills, I was on autopilot. At least that’s what I think of my past. The person I’m about to describe to you disagrees.
Upon arriving at Rice University to pursue Materials Science & Nanoengineering and Entrepreneurship (and unsurprisingly trying to graduate in 3 years because, well, optimization), I began to ruminate those future-life outcomes, thanks to a special person I met through preparing together for Rice’s upcoming Collegiate Cricket Tournament. He’s beyond unique—barely attending his labs, but somehow having the knowledge to tutor kids in senior-level courses and ace the MCAT at 17, or always being available for practice despite cramming for med school. Graduating in 2 and a half years with an educational background in ChatGPT (if you know you know), he is certainly the first ‘hustler’ who made little of working hard. To him, optimization = calculated inertia x mental equanimity.
His philosophy? Work to learn, and walk in with no expectations. You’ll be a go-getter. Stress only where it’s needed. You don’t have to be 20 with dark circles under your eyes already.
We naturally found ourselves getting closer while on the team, sharing the most pressing aspects of our lives and avidly discussing the uncertainty that lies ahead—careers, politics, financial stability, family and lifestyle. But mainly the first.
He asked me one night while we were returning from a Poker game:
Where do you see yourself fitting in the future world—you know, dominated by AI?
I’d been asked that question a lot, and I’d asked others that question even more often. Truth is, as a generation, we’re all scared. We fear for our job security, the prices of real estate, and coping with the breakneck approach towards the intelligence explosion—the age of artificial general intelligence (AGI).
I responded, “I have competing answers. What I know for sure is that I don’t want to settle for something ordinary when I can reach beyond”.
I was never an expert coder. While I do grind simulation software for power electronics and performance synthesis, and know my fair share of MATLAB and Python, engineering computation is really a different landscape from building the next Tensorflow algorithm for a neural network. I was always concerned whether I’d be able to catch the AGI bandwagon once my undergrad was over. I had a preconceived notion that learning new skills ended with getting a degree, and after that, you’re just stuck with the credentials you have. Which is why so many kids these days are Linkedinmaxxing.
My friend and I proceeded to engage in a conversation that mended my paradigm completely.
He said,
“People don’t force their way into a domain because of some intrusive thought telling them AI is gonna eat them up. They do it because they have the mindset to change it for the better. In an age where we can learn what our grandparents took a year to learn in a week, the true survivors aren’t the smart ones. They’re those who are versatile. As an aspiring doctor, I know that whatever I learn outside of med school will have to make me a better fit for anything in life—not a more intelligent doctor.”
“What do you think about diagnosis, imaging and treatment methods—everything you studied to do—being replaced?”
“I would have been long gone from that kinda work by then. Learning doesn’t stop with what you acquire when you’re young. We gotta keep learning till we’re gone. And if we don’t find an opportunity, we gotta create experiences that make us learn faster. That’s why we shouldn’t worry. Information has made us so powerful.”
Dr. GPT (his nickname) learned more from AI than his textbooks.
And on this day, he fired my brain up. I thought,
When this craze shifts from being a job to our entire lifestyle, won’t life evolve along with it? I don’t ever need to abandon my dreams. Because as we transition from credentials to skills, IQ to EQ, GPA to soft power, dreams will only get bigger and brighter through learning. And that never stops. Certainly not after becoming a deep-tech CEO in materials science.
That’s when I decided my answer. Technology is in my blood. It keeps me awake and floods my every synapse. I don’t see myself on the AGI train. I see myself championing the very thing that will run AGI whenever it arrives—what I’ve been trying to pursue since I was a teenager:
Cheap renewable energy.
I see myself bending the energy curve of AI companies, inventing cells and modules that will forever change the way they spend on solutions to the world’s biggest data sustenance problems. I guess I could say that’s what my endless hours of battery projects, my photovoltaic research papers, my career in materials science itself, are for. Not for getting people to view my profile like I previously thought, but for actually structuring my serendipity. Creating my stage for flourishing survival in a world so different from today. But most importantly, I now see myself remaining committed to acquiring new skills and ideas—foodstuff for my brain that will keep me up and running till I hang up my boots. Who knows, maybe that’ll be building the next ChatGPT someday (no shot right now, though).
Sharing my doubts about life and my future with people who are navigating the same journey helped me understand that we’re all just trying to figure life out. Even if we don’t know all the answers, a concrete visualization of our older selves does seem relieving in the middle of an anxious rat-race.
Except now I know my place in the world will be larger, more challenging, and more demanding for skills than what I strive to become during 3 years of college. Maybe that’s the new goal. Maybe that’s what we should all optimize for:
Continuous learning.