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ARK Disrupt Issue 131: Cryptoassets, AI, Fintech, Robots, Autonomous Cars, and Genes

Please enjoy ARK Disrupt Issue 131. This blog series is based on ARK Brainstorming, a weekly discussion between our CEO, Director of Research, thematic analysts, ARK’s theme developers, thought leaders, and investors. It is designed to present you with the most recent innovation takeaways and to keep you engaged in an ongoing discussion on investing in disruptive innovation. To read the previous issue, click here.

1. Media Metrics on Cryptoassets Look Like Those on Internet Stocks at Their Peak, But May Not Be Sending the Same Signal

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Almost everyone in the US has encountered an article or two, or two thousand, describing bitcoin, cryptocurrencies or blockchain technology over the past 6-9 months. Indeed, the number focused on bitcoin/cryptocurrencies spiked with bitcoin’s price during the fourth quarter of 2017, as shown below. Now that the price and press coverage have dropped sharply, we believe many observers are asking, “Was that it?”

ARK Disrupt Issue 131 Graph 1

A comparison of this press coverage to that during the last bubble would suggest that cryptocurrencies were in a bubble, and that it has burst. As shown below, the number of US articles focused on cryptocurrencies peaked at roughly the same percent of all US articles as those during the dot com mania.  In other words, most business news readers probably learned about the investment “opportunity” in bitcoin last year.

ARK Disrupt Issue 131 Graph 2

That conclusion falls short, however, as it does not account for differences in the maturity not only of the capital markets supporting dot com stocks and cryptocurrencies but also of the internet and blockchain technologies. The dot com bubble inflated to 6% of global GDP whereas, at its peak, the value of cryptoassets hit only 0.8%. ARK believes that among the primary reasons capital did not follow prices and media attention in the cryptoasset space was the lack of capital market infrastructure, particularly regulatory and legal, which prevented institutional and other broader market participation. During the dot com boom, equity markets were ready and willing to participate, in hindsight too much and too soon. In contrast, the lags in cryptoasset infrastructure development could accrue to the benefit of this new asset class in the long term.

The convergence between price and the utility value of blockchain technologies also helps to explain differences in media mentions between the internet bubble and the cryptoasset ascent.  Because “dot com” articles encompassed both the equities and the technology, many focused on the technology and explained the internet services and products themselves. In contrast, because the prices of cryptoassets incorporate the future utility value of an underlying technology that is evolving rapidly, articles tend to focus on price movements on crypto exchanges.

Media mentions including the term “internet” peaked just after the Nasdaq in early 2000, dwarfing mentions of cryptocurrencies seen late last year which, in turn, had not been seen in the internet space since 1994. In that year, interestingly, the first web browser had been in development for just a few years with little clarity on how the technology would proliferate, nor how pervasive it would become…perhaps an apt description of where cryptoassets are on the timeline of development today.

ARK Disrupt Issue 131 Graph 3

2. DeepMind Learns to Translate One 2D Image Into a 3D World 

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A key difference between human and machine intelligence is that humans have a rich mental model of the world. When we look at a photo, we don’t see a 2D array of pixels: we imagine the full 3D world, understanding the relationship among objects and making useful inferences. For the most part, artificial intelligence (AI) interprets images at face value with no concept of an underlying world. The lack of a mental model is the key reason why AI seems so fragile and limited today.

DeepMind’sGOOG latest work is enabling machines to build a mental model of the world. Researchers used deep learning to train an agent inside a 3D game engine to navigate and observe the world from different perspectives. The agent learned the structure of the world with a first-person view, much like a toddler crawling around. After extensive training, the agent learned how to build a mental model of the underlying world from one 2D image. Given a completely new 2D image, it recreated the 3D scene without any additional information.

Being able to transform ambiguous 2D images into rich 3D mental models is an important step in bridging the gap between the brittle AI available today and the common sense of a toddler. If AI continues to improve, the safety and capabilities of autonomous cars, drones, and robots will advance meaningfully.

3. Chinese Online Banks Are Expanding Their Footprint

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Digitization is coming to mainstream banking services, with internet companies like ANT Financial and TencentTCEHY leading the way in China.

MyBank, launched by ANT Financial, is an online bank focused on providing inclusive and innovative financial solutions for small and micro enterprises. Since its inception in 2015, MyBank has facilitated loans online to more than 10 million borrowers, capturing 14% of the 73 million SME market in China and giving ANT an early mover advantage in understanding their lending needs and credit profiles.

Thanks to AI technology, MyBank was the first in China to introduce the “310 Model”: a loan application that takes 3 minutes, an approval in 1 minute or less, with 0 human intervention. ANT is opening this AI platform to 1,000 other Chinese financial institutions, extending its credit offerings to an additional 30 million potential customers.

In contrast, Tencent’s WeBank is focusing on personal and auto loans. WeBank has facilitated US $133 billion in loans to ~12 million consumers. It has embedded micro loan products in its WeChat messaging platform, an important customer acquisition channel, allowing it to operate virtually at costs much lower than those of the bricks and mortar competition.

4. Collaborative Robot Roundup: Tailwinds, Jobs, Cost Declines, and Disruption 

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Tailwinds

This week two stories highlighted more tailwinds behind collaborative robots in the hospitality industry. The New York Times reported that as of July 1, the minimum wage in San Francisco will go up to $15 per hour. Restaurants in SF already had been shifting responsibilities to diners, but now an employee at minimum wage will make an annual salary equal to the cost of a low end collaborative robot, giving restaurants another push to automate. In other news supporting the move to automation, the Wall Street Journal reported a record high 844,000 unfilled jobs in the hospitality industry in the U.S.

Jobs

Today in the U.S., more than 6.7 million jobs are unfilled, surpassing the number of unemployed people for the first time in the history of the JOLTS survey and highlighting the growing opportunity for collaborative robots. While many fear the rise of robots, the U.S. is operating at a record high level of automation and yet is reporting the highest number of unfilled jobs in its history.

Cost Declines

ARK has researched and reported on robot cost declines in the past, but this week focused more on the impact of cost declines on unit growth in emerging and mature industries. Wright’s Law states that for every cumulative doubling in units produced, costs decline by a fixed percent. Typically misunderstood is the time it takes for a cumulative doubling of production to occur. In a mature industry, each cumulative doubling will take longer and longer, but in emerging industries the time to double unit production can shrink as lower price points open up new markets and turbocharge sales, creating a virtuous cycle and exponential growth.

Disruption

During periods of disruptive innovation, the metrics of performance in an industry change. In the robotics industry, the metrics are changing from precision and the ability to lift weight to the ease of training a collaborative robot.

5. Various Autonomous Vehicles Will Complement Each Other in the Delivery of Groceries

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This week KrogerKR partnered with Nuro, an autonomous van startup, for last-mile grocery delivery. Co-founded by Google self-driving car project alums, Nuro emerged from stealth mode in January but is not alone as Starship Robotics also aims to offer low cost autonomous grocery delivery. Starship robots will travel on sidewalks at a maximum speed of 4 mph, while Nuro vans will motor along public roads, probably both urban and rural, at a maximum speed of 25 mph. ARK estimates that rolling sidewalk robots could cut the cost of home grocery delivery by 90%. Many autonomous vehicle form factors probably will emerge, with vans and sidewalk robots as complementary solutions in a logistics ecosystem that will include flying delivery drones and autonomous delivery trucks.

6. CRISPR Could Enable Cures for Diseases Now Considered Incurable

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In fewer than five years, Clustered Regularly Interspaced Short Palindromic Repeats, or CRISPR genome-editing technology, has taken the scientific community by storm, not only revolutionizing the pace of biological breakthroughs but also promising medicines that cure diseases now considered incurable.

In the coming weeks, ARK will publish a white paper based on original research exploring the significance of CRISPR and the investment opportunities it will create. Until then, please enjoy a primer to assist in understanding DNA, the human genome, and the rise of CRISPR.


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