Earlier this year, Bill Gates was asked, “If you were 20 years old now, what would you do? Which area?” Gates responded, “When it comes to technology, there are four areas where I think a lot of exciting things will happen in the coming decades: big data, machine learning, genomics, and ubiquitous computing. So, if I were 20 years old today, I’d be looking into one of those fields.” Bill Gates doesn”t have many regrets about dropping out; we can all agree that things worked out pretty well for him. However, not spending time looking into these world-changing fields is his “one big regret from the time I spent in college.” Mr. Gates alludes to how academic institutions can afford students the opportunity to explore such world-transforming fields. While no one doubts that college dropouts are often successful, I believe that those who aspire to truly revolutionize cutting-edge computing could best develop the foundations needed to do so in an academic setting.
While there is much to be said for application-based, self-taught learning, some skills are best developed in an academic setting. Even for the nerdiest of us, proof-based linear algebra can be incredibly dry. More importantly, learning it alone is all but impossible. “Here, let me close Codecademy, take a break from my Backbone app, and crack open a linear algebra textbook to re-prove things that we already know to be true,” says no hacker ever. Coders chose practical over abstract every chance they get. But that is exactly what school, grades and tests are for: school is an opportunity for students to learn things they otherwise wouldn’t. While many people in school lament the time they’re forced to learn proof techniques and abstract mathematics, it is generally safe to admit that we never would have learnt these topics without being forced to. Schools don’t need to teach HTML or baseball statistics; students have an excess of internal motivation to study those topics. How many students out there claim to hate math or not be good with numbers but know a ton about the analytics of baseball? School is an opportunity to learn these complex, dry concepts that you might never approach without the assistance of a teaching staff and the motivation of a letter grade.
But even once you get past the dry fundamentals, the development of cutting-edge technology is still incredibly challenging. However, an academic environment can lower the barriers to explore such complex areas that might not be accessible via “messing around” by oneself. While most freshman do not enter college with an understanding of big data, machine learning, genomics, or ubiquitous computing, they are afforded access to thought-leaders in these fields in the classroom everyday. We sometimes forget that cutting-edge tech is often developed by bearded professors and PhD students.
The most prominent example of this is Larry Page and Sergey Brin’s famed thesis that proposed what would become Google’s PageRank and would eventually lead to one of the world’s most successful startups. These startup success stories out of academic still happen today. Take a company like Ayasdi out of Stanford’s Math department, casino for example. Ayasdi has created an incredibly robust and flexible tool by using properties of topology to visualize and analyze data. I remember my internal reaction when my middle school Math teacher first taught topology, “When the hell am I ever going to use this stuff?” Little did I know that I would later intern at a company that was using topology to change how we look at and gain insights from data. Technologies such as Ayasdi’s and Google’s involved years of research and development and would have been nearly impossible to develop outside the cradle of academia. Furthermore, it would have been entirely impossible to build develop these solutions without having the foundational mathematical, statistical, and systems knowledge that is acquired in school.
However, in recent years, individuals such as Peter Thiel have argued that entrepreneurs should leave school and are even incentivizing entrepreneurs to drop out. And it’s not difficult to see why. Recent college dropouts include Mark Zuckerberg, David Karp (Tumblr), and historical ones include Steve Jobs and Bill Gates. Just looking at the data, it seems like it takes a lack of a college degree to found a billion-dollar tech company. When I started at Stanford, my vision of entrepreneurship was based on those assumptions. I aspired to create a web or mobile app, and even admitted to my parents the possibility that I would drop out if the right opportunity arose. I quickly realized, however, how low these aspirations were: building an app is simple. With Stack Overflow, great documentation, and a plethora of tutorials to copy and paste from, building an app as a programmer has become a greatly reduced challenge. Building a company or creating new technology, however, remains incredibly difficult and it requires broader learning and exposure to topics sometime not easily identifiable as pertinent in the short-term. So while a college-dropout programmer has the potential to achieve short-term success, or perhaps even become the ‘next Zuckerberg,’ once you leave school, you severely stem your opportunities for academic exploration.
At the same time, while dropping out can stunt a programmer’s intellectual potential, staying in school can expose a programmer to fields he never would have dreamt of studying. Over the past two school years, I began centering my coursework around data analytics and machine learning. In order to do so, I had to put off my immediate interests in software development to focus on my indirect interests, taking classes that developed my mathematical maturity. While these courses did not pique my current interests, they’ve since unlocked applications in machine learning and data analytics that I now find incredibly exciting. Without the resources and structure of a university, developing the pertinent foundations for such areas would’ve been impossible for me. I believe formal learning will increase a student’s eventual capability and thus increase the probability that they create breakthrough innovations in such fields as compared to the less prepared dropout.
Student entrepreneurs working in cutting-edge computing can unlock entirely new realms of innovations. Luckily, being a student can play to ones advantage in order to learn today’s state-of-the-art. However, it is herein that lies the perennial battle of the engineer: do I cash out early or invest in my education? Neither answer is universally right: we need Mark Zuckerbergs and we need Larry Pages. But one thing’s for sure: if you can fight the allure of building the next Facebook today, you could develop the technology that enables the Facebooks of tomorrow.