When I first heard about the concept of a Career Fair in my freshman year at Caltech, I half-joked to my friends, “I don’t want a career!” I came to college to learn math and science, and was quite honestly disgusted with classmates who would choose their course loads, student groups, or volunteer opportunities for the sole purpose of looking good on a resume.
This didn’t mean that I resisted growing up or planning ahead. I suspected I would want to go to graduate school, so I spent my first two summers doing research in my two favorite fields: math and chemistry. After all, this looked good on a grad school application for precisely the right reason: Experience doing research would prove to both myself and graduate admissions committees that I would thrive there.
During the rest of the year, I tried to learn all the things. I took the more difficult options for physics and biology requirements in addition to numerous advanced math and chemistry classes as a freshman and sophomore. I even sat in on the first few weeks of the main major-specific classes for astronomy and biology my sophomore year before the workload of organic chemistry lab caught up to me.
Over the last couple of weeks, I’ve been fascinated and inspired by an important milestone at the cutting edge of Artificial Intelligence: The first 11 games of StarCraft played between professional StarCraft players and AlphaStar, a team of AI StarCraft agents built by DeepMind, the team behind previous expert-defeating game-players AlphaGo and AlphaZero.
It started with this 5-minute teaser video put out by the DeepMind team a couple of weeks ago:
If you’re as hooked by that teaser as I was, you might enjoy the full demonstration video with famous StarCraft casters Artosis and RotterdaM:
Finally, if you’re more able to read than watch, I’d recommend DeepMind’s write-up. Spoilers coming ahead…
Since starting work in November, my morning routine has become pretty regular. After my alarm goes off for the final time, I turn over and grab my iPad. I check e-mail, Slack, and so on, and then if I have some extra time, I browse Twitter. I set up my Twitter feed in 2016 after the election to hear the latest from two general categories of famous people: political reporters with the inside scoop on the latest from the Trump administration and political figures with similar (vaguely centrist) views to my self.
After reading about the mayhem that the president is subjecting our country to for a few minutes, I close the iPad portion of my mornings by reading a passage of the Bible and jotting down some notes on a Google doc. I do this to set a bit of a tone for the day; it’s then the last thing that I’m thinking about as I shower and head into work.
Lately, we’ve been studying the book of the prophet Jeremiah. Jeremiah is one of those books of the Bible that modern-day American Christians usually skip over, which is exactly why we decided to read it. What message are we missing that our culture doesn’t want us to hear?
Last fall, I participated in a job-seeking fellowship called Insight Data Science. The official program lasts for seven very full weeks, but the job-seeking process continues afterwards for anywhere between a few weeks and a few months.
I was one of the lucky ones to get a job in the month following the program. So based on that fact alone, you might imagine that this will be a glowing review of the program’s success.
I started my 2019 blog reboot last week with retrospective reflections on my life in 2018, and as is common this time of year, I’d like to follow it up with my goals for 2019. In compiling this list, however, I found a unifying thread between the goals: In every case, I hope to replace a mindset focused on maximizing quantity with one focused on maintaining quality.