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Finding Genius

Page 21

by Kunal Mehta


  Wearables, however, are just one part of our ongoing Quantified Self story. An explosion in data and newly accessible computational techniques are creating a vast array of opportunities for entrepreneurs to build the next breakthrough company. The rapid growth in biological data, such as genomic information, is an ongoing trend creating the foundation for an entirely new generation of companies.

  The Smallest Crevices of Our Lives: The -Omics Revolution

  Genomic information is now accessible to the mass market. At the beginning of the millennium, an entire human genome cost $100 million to sequence. That cost has plummeted to approximately $1,000 representing an improvement that has accelerated faster than the pace of Moore’s Law. Looking at the cost per genome, one will notice that in approximately 2008 the cost began a precipitous decline at a pace significantly faster than the years 2001 to 2007. This is attributed to the transition of Sanger-based chemistries and capillary-based instruments (“first generation” sequencing platforms) to next-generation sequencing (NGS) platforms.

  The implication of this price decline is evidenced by studying the increasing accessibility of popular genetic testing services such as 23andMe. In 2007, the price of a full testing service was $999 and by 2016 the price for the product decreased to $125. On Black Friday, Target sold the autosomal-only service kit for $59 and Amazon sold the full service (ancestry plus health data) for $99. This trend has led to an astounding acceleration in the number of people who have access to personal genetic data. Around one in 25 American adults now have access to this information, with more than 12 million people having tested themselves through a consumer genetics company.9

  Growth in the total sequenced base of individuals in the US has created a plethora of opportunities for entrepreneurs to offer services based on this data. More broadly, the growth in this information has provided a degree of granularity into our own identity that has up until now been unavailable to the average person. This progression will not just stop at genomic information. Companies across the globe are beginning to offer services that provide more granular information beyond the genome, such as our epigenome (modifications on the genetic material of a cell) and proteomics (proteins that are produced or modified in the body).

  However, it is not just the explosion of this new data that is creating new opportunities. Novel ways to make sense of that information, namely modern applications of AI, are creating a new class of companies that will take our understanding of human health and wellness to a new level.

  Accessible AI

  The explosion of digital information in the past decade has coincided with a resurgence and democratization of one of the most promising technological fields of this generation: artificial intelligence (AI). AI is a broad encompassing umbrella that refers to a collection of analytical technologies that enable systems to interpret data, learn from that information, and achieve specific goals and tasks through adaptation.

  Artificial intelligence is not new. The modern field of research stretches back to the mid-20th century when computing giants such as John McCarthy, Marvin Minsky, and Herbert Simon produced programs that were solving real-world problems such as checkers, word problems in algebra, and proving logical theorems. Its progression has been filled with many boom periods and so called ‘winters,’ a prolonged period of reduced funding and interest, following hype cycles similar to many emerging technologies. In a modern context, AI has captured the public’s imagination by surpassing humans in various domains such as Deep Blue’s defeat of Garry Kasparov at Chess in 1997, IBM’s Watson’s defeat of Ken Jennings at Jeopardy in 2011, and AlphaGo’s defeat of Ke Jie at Go in 2017.

  What is new about the field of AI is the ability for a broadening swath of the population to access the technology. Developers no longer need to know advanced mathematics to implement artificial intelligence into their products. Readily available software libraries, such as TensorFlow, make it easier for developers to utilize deep learning models. Since its release in November 2015, TensorFlow has become the dominant software library developers use to apply advanced data analysis to their programs. While the exact number of users is hard to pinpoint, there are a variety of indicators illustrating its popularity, such as the more than 118,000 stars it has received on GitHub and the usage of the software in companies such as Airbnb, eBay, Intel, and Snapchat.

  The accessibility of these tools has opened the floodgates for early stage companies to bring new products and services to market. Banks now utilize modern software to help them better detect fraud and confirm the authenticity of transactions. Physicians use software that helps them detect abnormalities in images such as mammograms. Hospitals are beginning to utilize software to protect their connected medical devices from external cybersecurity threats.

  All of these challenges are being addressed be a proliferation of AI-enabled software, much of which has emerged in the past 5-7 years thanks to advances in this field. The application of this technology in the context of optimizing human health and performance is beginning to take off. This is creating an investing boom, with investors hoping to find generation-defining companies that will fundamentally transform how we care for ourselves.

  Investing in the Future of the Quantified Self

  Our lives are now bathed in data, and with increasingly accessible tools to make sense of that information we can begin to address even more useful questions about ourselves and the lives we lead. However, for investors, general trends only serve as a weather vane, not a signpost. Having confidence in where the world is going doesn’t answer the billion dollar question of which companies will capitalize on that change.

  Finding and supporting the opportunities that have the greatest chance to find outsized success is the key role of the venture capital investor. Determining the characteristics that define what a ‘good bet’ is will drive consistent, and hopefully optimal, decisions when it comes to investing in early-stage technology companies. When thinking about the Quantified Self, several characteristics come to mind:

  Availability of novel datasets — the company has access to data that is novel, and that others do not have access to

  Application of novel analytical technologies — the company is leveraging an approach to analyzing vast quantities of information in a way that was not possible before and is nontrivial to replicate

  Why now? — the company is capitalizing on fundamental shifts in society, technology, and the economy that create the macro conditions for success

  From fun facts to behavior change — the company is generating insights that not only provide interesting information, but also have the ability to enact meaningful behavior change

  Pervasive penetration — the company’s technology has the potential to touch the lives of a broad swath of the population, not just a small niche of power users

  Smart data management — the company is able to navigate the complexities of managing user data, which includes regulatory considerations, societal attitudes towards data privacy, and security provisions to protect information from being stolen

  Moats — the company has the ability to protect the value they deliver from competitors either through inherent features of their product, aspects of their organizational structure, or other factors

  These characteristics are by no means exhaustive, but they illustrate the types of considerations that early-stage investors explore when identifying areas ripe for investment and assessing companies raising capital. Taking these factors into account, a couple of areas come to mind as territories that may yield the next generation-defining company: making care personal and taking control of our health trajectory.

  Making Care Personal

  We have more data about our health than ever before — from our genome, to our behavior, to our health record. For example, approximately 84% of all non-Federal, acute-care hospitals have adopted a basic electronic health record, which has increased from 9.4% just over 10 years ago. While much of this information is still hard to access
and analyze, entrepreneurs are quickly finding ways to liberate its use for a variety of novel applications. This data will create a more holistic picture than ever before of each individual’s health, and will in turn serve as fuel that drives a more personalized healthcare system. From clinical decision making to more intimate primary care experiences, entrepreneurs are creating products and services that will fundamentally transform the way we think about care.

  Spring Health is a company that embodies this fundamental shift to personalized care. The company is an online mental health clinic that uses clinically-validated techniques to offer personalized wellness recommendations, such as treatment options and exercise regimens. Users complete a dynamic questionnaire that adapts to each respondent based on their responses. The company then takes this dataset and utilizes their matching algorithm, which has been fine-tuned through the analysis of aggregated clinical trials and medical records, to identify personalized care plans.

  This is a fundamental shift in how people access mental health treatment. Nearly one in five Americans struggle with mental illness, yet despite its pervasive reach, the experience of treatment for most patients is antiquated and inefficient. Not only is the company fixing a significant challenge, they are doing so at a time when mental health and wellness is top of mind for our society. By leveraging data that has just come online, and analyzing it in a novel way through the application of modern machine learning, the company has been able to create a platform that has the potential to greatly impact the way our society cares for our collective mental well-being.

  Taking Control of Our Health Trajectory

  We intuitively understand that our health is impacted by a variety of factors. Our daily choices, such as diet and exercise, can dramatically impact the trajectory of our health. Furthermore, all of us are impacted by decisions in different ways based on our genetic code, environmental factors, and more. The impact of these decisions takes years to manifest, and have traditionally been almost impossible to isolate.

  Omada Health is a company empowering millions of users in this way. The company has developed a digital care program that takes a fundamentally novel approach to disease prevention and maintenance. Omada is building what CEO Sean Duffy calls a “21st century provider,” one that is supercharged by digital information and persistent care. The company uses connected devices to surface medical biometrics for each of their users in real time, providing a real-time picture of actions they can take to optimize for better health outcomes. Additionally, they provide users access to online coaches who can intervene when issues arise. While Omada started with diabetes, they are quickly moving into additional indications such as hypertension and high cholesterol.

  Omada is transforming the way in which we care for ourselves. By taking actions earlier on in the progression of a disease, the company is helping millions of patients take more control of their health outcomes. Digital information and telemedicine provide the company with the ability to deliver care at a scale that was impossible a few years ago. As we are all growing more accustomed to wearing devices that surface information about our lives, the company is leveraging that behavior to transform how we view and treat disease.

  Gary Wolf once described the Quantified Self movement as a “macroscope” applied to the individual human. He was describing the growing ability to quantify the individual as the summation of all their “countless moments, behaviors, and locations.”10 Over time, this macroscope has become both more broad and more sharp in focus, as we now have a more holistic and granular understanding of the human condition than ever before.

  In turn, entrepreneurs are now equipped with the resources and tools they need to build innovative products and services that will radically change our understanding of human health and performance. These new products and services will serve as the foundation for a new class of generation-defining companies that will transform how we live our lives.

  Sources & Resources

  1. https://techcrunch.com/2016/11/01/mobile-internet-use-passes-desktop-for-the-first-time-study-finds/

  2. https://www.comscore.com/Insights/Blog/Number-of-Mobile-Only-Internet-Users-Now-Exceeds-Desktop-Only-in-the-U.S

  3. https://searchengineland.com/its-official-google-says-more-searches-now-on-mobile-than-on-desktop-220369

  4. http://www.pewresearch.org/fact-tank/2018/03/14/about-a-quarter-of-americans-report-going-online-almost-constantly/

  5. https://www.theverge.com/2011/11/6/2541783/jawbone-up-review

  6. https://vimeo.com/155594490

  7. https://www.gartner.com/en/newsroom/press-releases/2018-11-29-gartner-says-worldwide-wearable-device-sales-to-grow-

  8. https://www.gartner.com/smarterwithgartner/wearables-hold-the-key-to-connected-health-monitoring/

  9. https://www.technologyreview.com/s/610233/2017-was-the-year-consumer-dna-testing-blew-up/

  10. https://www.webcitation.org/66TEHdz4d?url=http://aether.com/quantifiedself

  BRIAN YORMAK

  STORY VENTURES

  Rayfe Gaspar-Asaoka and Andrew Kangpan shared their perspectives on artificial intelligence and its impact on industrial automation and human-to-computer interaction. As revealed through their experience, the applications of AI are so far-reaching that it will eventually touch every aspect of our lives. One such application — for the future of mobility and transportation — has absorbed the largest volume of venture dollars. The study of autonomous driving dates back to the early 1920s and automobiles are ‘smarter’ today than they have ever been. Modern vehicles come with automatic parking, emergency braking, detection of hazards on the road, and can even keep a car within its lane. While these are all intelligent functions that have been developed through millions of dollars of funding and partnerships with the automobile industry, the players within this ecosystem are eagerly chasing one end goal: Level 5 autonomy or complete driverless cars.

  Brian Yormak of Story Ventures began his career in the center of mobility at Fontinalis Partners, a well-regarded venture fund focused on technologies that relate to the automotive industry. For this role, as part of a fellowship with Venture for America, Brian relocated to Detroit, the heart of the American automotive industry, where he developed a unique perspective on mobility startups and the data systems important for complete automation, especially as it relates to the future of transportation. These experiences led Brian to found Story Ventures, a venture fund based in New York, with his brother Jacob. Together, they are focused on investing in sensory systems, data infrastructure, and intelligent software: all building blocks for an autonomous future.

  While Brian has a thorough understanding of how cities, states, and governments can grow ‘smarter’ by leveraging the data created within their ecosystems, in this thesis chapter, Brian focuses exclusively on the future of mobility. Just as automation will impact the jobs of those in factories, autonomous driving will impact over 3 million truck drivers. At the same time, it will provide unique access for those who are hearing or visually impaired and have trouble with transportation. Brian discusses the factors necessary to make driverless cars a reality, and shares what he believes are good investment opportunities as the industry continues to mature.

  Earlier in the book, I discussed how the cost of starting a business has gone down dramatically. In the automotive industry, technology has improved, and the cost of sensors has declined, creating more opportunities for entrepreneurs who want to build applications for the driverless future. While many focus on the negative aspects of automation, Brian is wise to point out that the $80 billion invested between 2014-2017 into a future of autonomous vehicles is likely to have a positive impact: over 1.2 million deaths annually are caused by automobile accidents, 93% of which are caused by human error. In this chapter, Brian shares the perspectives of investors on both sides of the table: those who believe that Level 5 autonomy is within reach and those who believe that we are still decades away from this becoming a reality. These differing perspectives help establish a
foundation from which entrepreneurs and investors can find unique opportunities.

  NEXT GENERATION TRANSPORTATION AND MOBILITY

  Brian Yormak, Story Ventures

  In Greek mythology, Hephaestus was the blacksmith for the gods. He crafted the armor of Achilles and the arrows of Cupid. However, even as a god, Hephaestus recognized that being the sole source of labor created production limitations. To keep up with the gods’ demand for crafted steel, he built automatons: self-operating machines that followed a predetermined sequence of operations. Together, they built tools worthy of Olympus.

  The story of Hephaestus and his golden automatons served as one of the earliest inspirations for the concept of intelligent physical machines, and their potential to complement — or even replace — human labor. Today, the expected impact of automating labor via intelligent machines is commonly disputed. Some foresee machines replacing workers en masse. They worry for the fates of blue collar laborers (e.g. truck drivers, assembly line workers, cashiers), and envision accountants, lawyers, and investors joining them soon thereafter. These concerns are supported through analyses by leading academics and economists — a 2017 McKinsey report suggests that anywhere from 39 million to 73 million US jobs are at risk of being replaced by the year 2030.

  Proponents of automation are eager to dismiss these concerns as unnecessarily pessimistic. In their view, our robot future will ultimately benefit society by enabling people to focus on work that is safer and more rewarding. In 1970, approximately 11 out of 1,000 workers were killed on the job in the US. Nearly 40 years later, following the passage of the Occupational Safety and Health Act (OSHA) and subsequent regulations, the worker fatality rate had dropped to 3.6 workers per 100, a 67% decrease.

 

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