Uber for VR Blockchain — Disruptive ICO Coming Soon!!
“Okay, but can we add machine learning to it?”
By: Will Morgus (M&T ‘21)
It’s a wonderful time for people with big ideas and the passion to execute them. The US Bureau of Labor Statistics and the Kauffman Index of Entrepreneurship (“an in-depth measure of the people and businesses that contribute to America’s overall economic dynamism”) both show that startups are thriving. With this overall market idealism and the encouraging progression of tech innovations that change the way we approach problems of all natures, hopes are high for tech to keep revolutionizing our world.
It’s tempting for aspiring entrepreneurs to try to apply emerging technologies to problems where a full-frontal tech-trend assault may not be the best solution. For an example of where this could go wrong, look at important inventions like duct tape: an amazing multipurpose tool, but not for absolutely everything (duct tape wallet startup? Not your best call. ) In the current startup climate, we’ve seen an increasing trend of duct-tape-for-everything mentality applied to emerging business models and technologies that you’ve definitely heard of: Uber for X, machine learning, and blockchain. That’s not to say all of these are fads: each, when applied properly, holds a lot of entrepreneurial value. Let’s look at each tech advance, and explain where and where not to use them.
UBER FOR X
Have you heard about Uber for cars? It’s called Uber. What about Uber for Uber? It’s called Lyft. The poster child of successful (for the most part) startups, Uber has defied many expectations to grow into the world’s highest valued startup. With its ostensibly simple model, Uber has occupied a hefty portion of an extremely broad market by noticing a situation where tech can bridge the gap between virtual accessibility and real services. Inspired by this, entrepreneurs have tried to bring the convenience of Uber to many other industries: as NYU Stern School of Business professor Amy Webb explains in her book The Signals Are Talking, “‘Uber for X’ has become a kind of shorthand for convenience — a technological solution for any of life’s frustrating, dull tasks, one that either makes them more convenient or automates them completely.”
What others have importantly disregarded in copying the Uber model is the series of other factors that made it possible to become the unicorn of the century. Founded in the wake of a recession that left many white-collar workers (with cars) unable to find a job but still saw an increase in mobile phone sales, Uber took a broken and inefficient taxi system and simplified it unlike anyone had thought to before. Can startups identify faults in systems and capitalize on ever-increasing accessibility to tech? Of course, but heed Einstein’s words of wisdom:
“Everything should be made as simple as possible, but not simpler.”
No, machine learning doesn’t mean the robots are taking over. No, machine learning can’t see the future. No, machine learning doesn’t need to be in every startup. A field of computer science study dedicated to giving the computers the ability to learn without being programmed (as opposed to being given a set of rules to follow,) machine learning has showcased its ability to create and improve on algorithms in huge areas like navigation and collision-detection systems for autonomous cars, or even in simpler applications like the spam filter on your Gmail inbox. With seemingly endless applications, where does machine learning reach its limits?
As Wharton statistics and marketing Professor Peter Fader explains, machine learning is best used as a classification tool more so than a future-predictor. In the case of computer vision, for example, deep learning neural nets are unparalleled in their performance. However, in Professor Fader’s line of work, predicting lifetime value of customers, traditional behavioral statistical models have proven considerably more effective. Does that mean that machine learning has no use outside of self-driving cars or moving around emails? Absolutely not. The point stands though that any business looking to implement it should make sure that it serves a legitimate and deliberate purpose.
From company valuations skyrocketing from simply changing their names to the Harvard Business Review categorizing it as a “foundational technology,” the influence of the blockchain (or distributed ledger) is undeniable. But what is it, and why does everyone care so much? At its core, the blockchain is a remarkably simple idea. By distributing a ledger across a network of computers, the transactions that are tracked by that ledger become indisputable and therefore can be trusted. This is majorly important when it comes to fiat transactions, how most monetary systems are set up. Blockchain implementations also reach far beyond financial transactions: Walmart and IBM are trying to reshape how food safety is approached by using a single ledger to keep secure and easily traceable records of where food comes from, allowing any necessary recalls to be swift and effective.
This sounds pretty great, and it’s easy to see why there’s a lot of hype, but when don’t you need it? More often than not, information storage can be easily and most properly managed with traditional relational databases like SQL. Distributed ledgers have (for the time being) very niche uses, and the benefits of setting up a blockchain are outweighed by the lack of utility received from it. Blockchain certainly has the potential to change how society works, but can unnecessarily weigh down a startup who doesn’t truly need it. When in doubt, always focus on the needs of the customer and if they absolutely require being filled by using the functionality of a blockchain.
So what’s next?
While startups can tend to misapply technology, entrepreneurs should never be discouraged from pursuing the idea they feel most passionate about. Think you can make Uber for VR duct tape wallets? Follow your dreams, anything really is possible. Just be wary of the decisions you make, and evaluate the tools available to you. But don’t just take it from me, take it from Leonardo da Vinci:
Simplicity is the ultimate sophistication.
Will Morgus is a Project Manager for the Innovation Fund and he studies Computer Science, Finance, and Management. Having worked with a failed “Uber for everything” startup, he’s taken a particular interest in learning how not failing-startups work. His hobbies include app development, reading “The Onion,” and obsessively making playlists on Spotify. Feel free to reach out for a chat at firstname.lastname@example.org!
Weiss Tech House Innovation Fund is dedicated to funding, promoting, cultivating, and supporting student entrepreneurship in the UPenn community. Working on a startup and want to apply? Fill out our application here. Interested in partnering? Want to get involved? Drop us a line at apply.innovationfund at gmail.com.