Technological change is one of the key drivers of economic growth for nations, and of success for individual companies that can harness it. The economic growth it creates has been the fundamental support of the improving quality of life which citizens in developed markets enjoy and those in emerging markets crave. Therefore we view constant surveillance of the tech landscape as one of the key functions of any global macro analysis, and one that’s critical for long-term investment success. Often that can mean focusing on individuals in the tech landscape, especially if their academic and entrepreneurial career suggests that they have a finger on the pulse of the most significant tech trends.
One such figure for us is Sebastian Thrun. Our readers have heard us discuss his career and work several times over the past few years. Thrun is now putting all his weight behind a single, audacious project: to remake the structure of higher education in a way that better serves the ambitions of individual learners and the needs of employers.
Thrun’s Resume—Tracing Tech Revolutions
Sebastian Thrun has spent 20 years in the forefront of cutting-edge developments in tech. Born in Germany in 1967, he got his PhD at the University of Bonn before moving to the United States. To this day, he has a keen sense of the uniqueness of American culture that gives him optimism for the American project:
I think there’s a genuinely innovative element in America that you find in almost no other culture. And I believe it goes back to the founding of this wonderful country, where the people who came over had to be innovative to make their own rules… and build society up from scratch. And I think that… genuinely American gene that is behind the American dream, remains here today, more than in any other place I know of. And it’s a wonderful thing, it makes me very happy to be part of such an amazing group of smart and driven entrepreneurs in Silicon Valley.
He was educated in computer science and statistics, which he would later marry to create his most important technical innovation: probabilistic robotics, the now-prevalent technique of letting robots learn by trial and error within a framework, rather than trying to program them beforehand for every conceivable eventuality. When he first came to the U.S., he taught robotics at Carnegie Mellon and helped run the University’s Robot Learning Laboratory. After sabbatical year at Stanford University he jumped ship to the west coast, where he ran SAIL—the Stanford Artificial Intelligence Laboratory. There, he says, as a new professor with “nothing to do,” decided to attack the DARPA Grand Challenge: an award of a million dollars (later doubled) for a robotic vehicle that could navigate 140 miles of desert roads unassisted, from Barstow, CA to Primm, NV. With a team of 20 Stanford graduate students, he spent months in the desert, and in the second year the Grand Challenge was held, his team won. That was about 10 years ago. (Five cars crossed the finish line, but SAIL’s “Stanley” robotic car came in first.)
It was Thrun’s pioneering kind of artificial intelligence—a car that learns, rather than being exhaustively programmed—that led the team to victory.
On to Google
There was a retiring observer at that year’s Grand Challenge hiding behind his sunglasses—his name was Larry Page, and he was the co-founder of Google (NASDAQ: GOOG). Since the race participants were just watching as the cars battled it out, the two fell into a philosophical conversation about robotics. Their friendship continued to develop after the event, and when the next DARPA robot car challenge came—the Urban Challenge, two years later—Thrun showed Page the work of one of his brilliant graduate students. That work turned into the foundations of Google’s Street View, GOOG’s effort to catalog the world in photographs. Thrun came on board as a Google Fellow in 2007, and ultimately resigned his tenured full-time professorship at Stanford to found Google X, GOOG’s semi-secretive department for “moonshot” projects. There, he was responsible (among other things) for Google Glass, GOOG’s foray into wearables. (That project has quietly died, although judging from the company’s investments in private “augmented reality” firms such as Magic Leap, GOOG has not abandoned the space.)
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The most recent shift in Thrun’s path came in 2012, when he founded an educational company called Udacity. In late 2014, he quietly dropped out of his official Google duties, remaining a consultant, but otherwise focusing all his time on his own “moonshot” rather than Google’s.
Thrun’s career has taken him through the epicenters of advanced robotics and artificial intelligence over the past 20 years—and now he has chosen to focus all of his efforts on a company that’s trying to disrupt the traditional model of education. Why?
Thrun may be first and foremost a scholar and practitioner of AI and robotics, but his motivations are humane. His enthusiasm for driverless cars is rooted, according to interviews, in the traffic deaths of two close friends and colleagues. He also has broader desires for new technological innovations to render human life easier, more pleasant, and more efficient. He points out the amount of capital sunk in cars and car infrastructure, observing that by his own estimate he uses his own car about three percent of the time—a real waste. He got to imagining a world where, (1) cars were robotic, and safer than unreliable human drivers, and (2) car ownership was obsolete, because a car could deliver itself to you whenever you needed it. Thanks to his work at GOOG, and thanks to the “sharing revolution” exemplified by companies such as Uber and Airbnb, both of these apparently utopian dreams are not far from becoming reality.
It is these humane motivations that allow us to make sense of Thrun’s founding of Udacity and his setting aside of his moonshot command at GOOG. He says, “I believe online education can make a difference in the world, more so than almost anything I’ve done in my life.”
He sees broad statistics. First, higher education is too expensive. Its delivery is also flawed, with most students in a four year program failing to complete it even after six years. Rather than rethink the structure and delivery of education in a data-driven way, institutions of higher learning are simply clinging to a model that’s basically a millennium old.
That model is increasingly irrelevant, Thrun believes, for several reasons. The “cohort” model of learning doesn’t take into account learners’ different paces and styles of learning. Students who learn one-on-one with a tutor have better outcomes, but when they are put in a group, the slower learners get left behind and the quicker learners get bored. Both outcomes put the successful completion of a learning path in jeopardy.
Second, the rapid pace of technological change means that in most disciplines, the material you learned during the discrete “educational” phase of your life will become outdated within 5 to 10 years. That means the model of childhood-education-work needs to be fundamentally revised in favor of lifelong learning.
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Third, the model in which one learns for a job that one will then hold for life has broken down. The average job is now held for just over four years, and radical career shifts are more common than ever. So once again, a static, one-and-done approach towards learning and credentials is obsolete, in Thrun’s view.
And fourth, as a result of these problems, there is an increasingly sharp disconnect between the skills workers need, and the skills they have. According to analysts, by 2020, the world will have 95 million more low-skilled workers than it needs, and 85 million too few high-skilled workers (with the definition of low and high skill varying according to a country’s level of development).
Thrun views Udacity, the education venture to which he’s now exclusively devoting his professional life, as providing a solution to these problems. Unlike most massive open online courses (MOOCs), Udacity charges a modest fee (about $150 a month) and offers “nanodegrees”—concentrated courses that a learner can work through at their own pace, usually in 4 to 12 months. They’re experientially based, and structured in such a way that problems are posed before solutions are given, so that learning emerges organically. And they have major corporate sponsorship, so employers are helping build an educational system that will deliver the skills workers actually need. They result in a meaningful and specific credential—at the moment, mostly in programming, app development, and related disciplines.
Bringing the Silicon Valley Ethos to Education
Really, what Thrun is doing is bringing pragmatic Silicon Valley ethos to bear on education. Failure isn’t bad; failure is a learning opportunity. We learn best by doing. We learn best when we are engaged in a process in which we’re invested, which is relevant, and which genuinely excites us. Thrun says his ultimate goal is to make learning as addictive as a video game—and with his out-of-the-box approach, we think he may do it.
Investment implications: The driver of real American exceptionalism is the open, experimental, experiential, non-judgmental, data-driven approach that Thrun appreciates so much about Silicon Valley entrepreneurial culture. While pundits suggest various top-down fixes for America’s troubled and fractured educational system, visionaries and entrepreneurs like Sebastian Thrun are actually creating effective solutions without waiting for that top-down policy intervention. Thrun is tremendously optimistic about future improvements in America’s quality of life—and so are we. His example encourages us to continue to be optimistic as we search out the transformative, emerging technologies that will drive the success of the next generation of great growth companies. The end is not nigh.
For more commentary or information on Guild Investment Management, please go to guildinvestment.com.