Updated: Jun 13
Yep! This is my *third* week of Google internship. It's the classic 9-6 + coffee = work. I have been mostly occupying the rest of the time with reading (and some videogames).
Before I get into reading, I will share some of what I have been up to this week in terms of the internship. As the internship itself is tailored for frosh + sophomore, it is much more educational in nature. I learned a lot about web app development and code management. We had virtual coffee meetings every 2 days with the entire team, where we shared some life tidbits. There also happens to be an intern meme group, where people post memes about everything from code reviews to Google Cloud Shell (which is the platform my cohort works on). After team meetings with my specific pod, we have these discussions for fun where we talk about our latest stock portfolio and schoolwork. For the next few weeks, we are planning on doing a capstone project related the the Google Assistant.
Over the week, the thought of change and information has crossed my stream of consciousness many times, and I thought given its significance it would do it some justice to share it here. I will reflect on what has changed for me since my starting my internship, and how that has changed how I think about change.
I went into Google thinking that either of two possibilities will happen: I will be taught like in school, or I will be forced to look up knowledge myself. I found neither options appealing, as I disliked being force fed information and not knowing what I don't know.
That was not really what I got. While I didn't really learn any "information" at Google, I learned a lot of concepts. Instead of force feeding me anything, they showed short tutorials showing the concepts and rationale alongside the process. In my imagination, it was kind of what would be covered when an apprentice learns from their master. Instead of being graded on my output, I was allowed to make mistakes and fix them w/ frequent feedback from my managers. This style of conceptual learning + fast iterative adjustment learning has really taught me a lot in a short time frame and showed me the importance in how you learn.
While this has taught me a lot in a short period of time, it also raised the concept of how different styles of learning perform with respect to time. While I want to learn a lot of things, I don't want to learn things that be obsolete in say, 10 years. I think the answer to this is that while information changes over time, their underlying concept tends to remain more or less the same. For example, how humans approach communication has changed over the years, from snail mail to instant messages. However, the underlying concept that people want to stay connected with the lowest communication latency has remained somewhat constant.
In some ways, I call this "change-resistant learning." That is, if you learn the fundamentals, you will begin to see the current skill sets espoused by people as only tools to an objective, and as long as you stay focused on the objective and achieve it, those tools don't matter. For example, people might claim they are really good at math, they work well with people, they are really smart. That's great, but if that cannot be used to achieve any fundamental objective (get as many users to use this product, make this product actually work for the users, lower costs, generate the best research), those tools are pretty useless. In terms of change resistance, as the tools people use to tackle these problems change ("we use XYZ programming language", "we only hire the smartest people", "we want people from big name universities"), the change-resistant learning will teach you to focus on the objective which will be change resistant ("we want a fast database", "we want to use math to accurately depict the situation", "we need a sense of legitimacy in selling our work to others"). This helps keep the learner level-headed and not distracted by all the latest fads in the industry or news.