The first investor in Snapchat thinks bitcoin could realistically be worth $500,000 by 2030
Bitcoin has been the top-performing currency in the world in six of the past seven years, climbing from zero to a value of about $1,190.
But the cryptocurrency isn’t anywhere close to its potential, according to Jeremy Liew, the first investor in Snapchat, and Blockchain CEO and cofounder Peter Smith. In a presentation sent to Business Insider, the duo laid out their case for why it’s reasonable for bitcoin to explode to $500,000 by 2030.
Their argument is based on increased interest in bitcoin, thanks to:
Remittance transfers, or electronic money transfers to foreign countries, have almost doubled over the past 15 years to 0.76% of GDP, data from The World Bank shows.
“Expats sending money home have found in Bitcoin an inexpensive alternative, and we assume that the percentage of Bitcoin-based remittances will sharply increase with greater Bitcoin awareness,” the two say.
Liew and Smith said increased political uncertainty in the UK, US and in developing nations would help elevate the level of interest in bitcoin.
“We believe Bitcoin awareness, high liquidity, ease of transport and continued market outperformance as geopolitical risks mount, will make Bitcoin a strong contender for investment at a consumer and investor level,” the two said.
Liew and Smith believe the percentage of non-cash transactions will climb from 15% to 30% in the next 10 years as the world becomes more connected through smartphones. There’s only a 63% global smartphone penetration and the total number of smartphone users is expected to soar by 1 billion by 2020. GSMA, a trade body that represents the interests of mobile operators worldwide, believes 90% of these users will come from developing countries.
This will make it possible for nearly everyone to have a bank in their pocket, and that should provide a boost for bitcoin as well. Liew and Smith say bitcoin could account for 50% of all of these transactions.
Here are the basic model drivers that Liew and Smith used:
- A bitcoin price of $1,000 in 2017.
- That network users will grow 61x from now until 2030. “Put another way, we need a population of bitcoin users around a quarter of the Chinese population (or 5% of the global population) in 2030 to see bitcoin at $500k,” Liew and Smith told Business Insider. Bitcoin’s user network grew from 120,000 users in 2013 to 6.5 million users in 2017, or about 54x, and this could be just the beginning. Growth of that magnitude would produce 400 million users in 2030.
- The average value of bitcoin held per user hits $25,000. “As institutional investor cash in Bitcoin, sophisticated investors trading Bitcoin, and Bitcoin-based ETFs proliferate, we think the average Bitcoin value held will increase to around $25k per Bitcoin holder,” Liew and Smith said. Currently, with a market cap of $16.4 billion, and 6.5 million user count, the average user holds $2,515 worth of bitcoin.
- Bitcoin’s 2030 market cap is decided by number of bitcoin holders multiplied by average bitcoin value held.
- Bitcoin’s 2030 supply will be about 20 million.
- Bitcoin’s 2030 price and user count total $500,000 and 400 million, respectively. The price is found by taking the $10 trillion market cap and dividing it by the fixed supply of 20 million bitcoin.
It’s important to note that a lot could go wrong, too. News surrounding bitcoin has been rather negative as of a late.
China, which is responsible for nearly 100% of trading in bitcoin, has been cracking down on trading. The three biggest exchanges recently announced a 0.2% fee on all transactions, in addition to blocking withdrawals from trading accounts.
Additionally, the US Securities and Exchange Commission rejected two bitcoin exchange-traded funds, and will make a ruling on another one in the future. It’s not expected to be approved. However, Smith thinks bitcoin is still in its early stages.
“The SEC’s ruling wasn’t a surprise to us,” he told Business Insider. “We know that getting this sort of approval is going to take (a potentially long) time,” Smith said. “In the meantime, bitcoin is already simple to buy and hold and, as the asset continues to mature, we’ll continue to see an increase in the development and deployment of surrounding products.”
And while bitcoin hasn’t been granted regulatory approval here in the US, it is catching on elsewhere. On April 1, the cryptocurrency became a legal payment method in Japan.
Another threat to the future of the cryptocurrency is that developers are threatening to set up a “hard fork,” or alternative marketplace for bitcoin. This would result in the split of bitcoin into bitcoin and bitcoin unlimited. However, Smith says not to worry.
“Bitcoin has strong economic incentives to prevent this,” he said. “If the last two years of healthy contention and debate lead to a conclusion, it’s that Bitcoin is incredibly resilient and stable. In fact, the bitcoin Blockchain has operated for 7+ years with no downtime, a feat no other back-end system operating at this scale can claim.”
Anyone interested in bitcoin should also know that the cryptocurrency sees violent price swings that are uncommon among the more traditional currencies. Bitcoin rallied 20% in the first week of 2017 before crashing 35% on word China was cracking down on trading.
The cryptocurrency has regained those losses, and trades up about 25% so far this year.
Get the latest Bitcoin price here.
The Quest for Artificial Intelligence — and Where It’s Taking Us Next
By Luke Dormehl
275 pp. TarcherPerigee. Paper, $16.
HEART OF THE MACHINE
Our Future in a World of Artificial Emotional Intelligence
By Richard Yonck
312 pp. Arcade Publishing. $25.99.
Books about science and especially computer science often suffer from one of two failure modes. Treatises by scientists sometimes fail to clearly communicate insights. Conversely, the work of journalists and other professional writers may exhibit a weak understanding of the science in the first place.
Luke Dormehl is the rare lay person — a journalist and filmmaker — who actually understands the science (and even the math) and is able to parse it in an edifying and exciting way. He is also a gifted storyteller who interweaves the personal stories with the broad history of artificial intelligence. I found myself turning the pages of “Thinking Machines” to find out what happens, even though I was there for much of it, and often in the very room.
Dormehl starts with the 1964 World’s Fair — held only miles from where I lived as a high school student in Queens — evoking the anticipation of a nation working on sending a man to the moon. He identifies the early examples of artificial intelligence that captured my own excitement at the time, like IBM’s demonstrations of automated handwriting recognition and language translation. He writes as if he had been there.
Dormehl describes the early bifurcation of the field into the Symbolic and Connectionist schools, and he captures key points that many historians miss, such as the uncanny confidence of Frank Rosenblatt, the Cornell professor who pioneered the first popular neural network (he called them “perceptrons”). I visited Rosenblatt in 1962 when I was 14, and he was indeed making fantastic claims for this technology, saying it would eventually perform a very wide range of tasks at human levels, including speech recognition, translation and even language comprehension. As Dormehl recounts, these claims were ridiculed at the time, and indeed the machine Rosenblatt showed me in 1962 couldn’t perform any of these things. In 1969, funding for the neural net field was obliterated for about two decades when Marvin Minsky and his M.I.T. colleague Seymour Papert published the book “Perceptrons,” which proved a theorem that perceptrons could not distinguish a connected figure (in which all parts are connected to each other) from a disconnected figure, something a human can do easily.
What Rosenblatt told me in 1962 was that the key to the perceptron achieving human levels of intelligence in many areas of learning was to stack the perceptrons in layers, with the output of one layer forming the input to the next. As it turns out, the Minsky-Papert perceptron theorem applies only to single-layer perceptrons. As Dormehl recounts, Rosenblatt died in 1971 without having had the chance to respond to Minsky and Papert’s book. It would be decades before multi-layer neural nets proved Rosenblatt’s prescience. Minsky was my mentor for 54 years until his death a year ago, and in recent years he lamented the “success” of his book and had become respectful of the recent gains in neural net technology. As Rosenblatt had predicted, neural nets were indeed providing near human-level (and in some cases superhuman levels) of performance on a wide range of intelligent tasks, from translating languages to driving cars to playing Go.
Dormehl examines the pending social and economic impact of artificial intelligence, for example on employment. He recounts the positive history of automation. In 1900, about 40 percent of American workers were employed on farms and over 20 percent in factories. By 2015, these figures had fallen to 2 percent on farms and 8.7 percent in factories. Yet for every job that was eliminated, we invented several new ones, with the work force growing from 24 million people (31 percent of the population in 1900) to 142 million (44 percent of the population in 2015). The average job today pays 11 times as much per hour in constant dollars as it did a century ago. Many economists are saying that while this may all be true, the future will be different because of the unprecedented acceleration of progress. Although expressing some cautions, Dormehl shares my optimism that we will be able to deploy artificial intelligence in the role of brain extenders to keep ahead of this economic curve. As he writes, “Barring some catastrophic risk, A.I. will represent an overall net positive for humanity when it comes to employment.”
Many observers of A.I. and the other 21st-century exponential technologies like biotechnology and nanotechnology attempt to peer into the continuing accelerating gains and fall off the horse. Dormehl ends his book still in the saddle, discussing the prospect of conscious A.I.s that will demand and/or deserve rights, and the possibility of “uploading” our brains to the cloud. I recommend this book to anyone with a lay scientific background who wants to understand what I would argue is today’s most important revolution, where it came from, how it works and what is on the horizon.
“Heart of the Machine,” the futurist Richard Yonck’s new book, contains its important insight in the title. People often think of feelings as secondary or as a sideshow to intellect, as if the essence of human intelligence is the ability to think logically. If that were true, then machines are already ahead of us. The superiority of human thinking lies in our ability to express a loving sentiment, to create and appreciate music, to get a joke. These are all examples of emotional intelligence, and emotion is at both the bottom and top of our thinking. We still have that old reptilian brain that provides our basic motivations for meeting our physical needs and to which we can trace feelings like anger and jealousy. The neocortex, a layer covering the brain, emerged in mammals two hundred million years ago and is organized as a hierarchy of modules. Two million years ago, we got these big foreheads that house the frontal cortex and enabled us to process language and music.
Yonck provides a compelling and thorough history of the interaction between our emotional lives and our technology. He starts with the ability of the early hominids to fashion stone tools, perhaps the earliest example of technology. Remarkably the complex skills required were passed down from one generation to the next for over three million years, despite the fact that for most of this period, language had not yet been invented. Yonck makes a strong case that it was our early ability to communicate through pre-language emotional expressions that enabled the remarkable survival of this skill, and enabled technology to take root.
Yonck describes today’s emerging technologies for understanding our emotions using images of facial expressions, intonation patterns, respiration, galvanic skin response and other signals — and how these instruments might be adopted by the military and interactive augmented reality experiences. And he recounts how all communication technologies from the first books to today’s virtual reality have had significant sexual applications and will enhance sensual experiences in the future.
Yonck is a sure-footed guide and is not without a sense of humor. He imagines, for example, a scenario a few decades from now with a spirited exchange at the dinner table. “No daughter of mine is marrying a robot and that’s final!” a father exclaims.
His daughter angrily replies: “Michael is a cybernetic person with the same rights you and I have! We’re getting married and there’s nothing you can do to change that!” She storms out of the room.
Yonck concludes that we will merge with our technology — a position I agree with — and that we have been doing so for a long time. He argues, as have I, that merging with future superintelligent A.I.s is our best strategy for ensuring a beneficial outcome. Achieving this requires creating technology that can understand and master human emotion. To those who would argue that such a quest is arrogantly playing God, he says simply: “This is what we do.”
The most successful artificial intelligence (AI) systems will be those comprising an emotional intelligence almost indistinguishable from human-to-human interaction, according to Bronwyn van der Merwe, group director at Fjord Australia and New Zealand — Accenture Interactive’s design and innovation arm.
While the concept of AI is not new, in 2017 van der Merwe expects emotional intelligence to emerge as the driving force behind what she called the next generation in AI, as humans will be drawn to human-like interaction.
Speaking with ZDNet, van der Merwe explained that building on the first phase of AI technology, emotional intelligence enhances AI’s ability to understand emotional input, and continually adapt to and learn from information to provide human-like responses in real time.
Currently, 52 percent of consumers globally interact via AI-powered live chats or mobile apps on a monthly basis, Fjord reported, with 62 percent claiming that they are comfortable with an AI-powered assistant responding to their query.
With consumer appetite for AI expected to continue to grow at a rapid pace, van der Merwe predicts emotional intelligence will be the critical differentiator separating the great from the good in AI products, especially given that by 2020 she expects the average person to have more conversations with chat bots than with human staff.
“People are probably going to be more drawn into engaging with chat bots and AI that has personality,” she said. “We’re seeing this already … it’s a companion and it’s something people can engage with.”
Van der Merwe explained that Amazon, Microsoft, and Google are hiring comedians and script writers in a bid to harness the human-like aspect of AI by building personality into their technologies.
With audience engagement somewhat guaranteed out of necessity when it comes to employing AI technology, van der Merwe said companies will have to focus very heavily on transparency and trust, and tell customers when they start speaking with a machine, be careful not to blur the lines.
“Right now, my recommendation to our clients is that we need to experiment with this … and we need to get data to validate our response,” she said.
“My intuition is that it’s better to be completely transparent so that you are building the trust, because I think if you build solutions that don’t have transparency at their core, you risk unintended consequences that could create a media storm and a backlash of a brand.”
An AI capable of human emotion is not a guaranteed win, however, with van der Merwe pointing to the public relations nightmare that was Microsoft’s Tay.
Microsoft announced in March last year that it was testing a new chat bot, Tay.ai, that was aimed primarily at 18- to 24-year-olds in the US. After a brief 16-hour Twitter rampage, Microsoft suspended Tay for spouting inflammatory and racist opinions.
Tay was designed by the tech giant to use a combination of public data and editorial developed by staff, including comedians. But, as an AI bot, Tay also used people’s chats to train it to deliver a personalised response.
“Much to Microsoft’s embarrassment, they had to shut it down very quickly,” van der Merwe said. “There’s a real, big question around ethics and how you build the morality into AI.”
While the debate over machines displacing workers has been discussed at length, van der Merwe is certain AI won’t ever completely replace human beings.
“As human beings, we have contextual understanding and we have empathy, and right now there isn’t a lot of that built into AI. We do believe that in the future, the companies that are going to succeed will be those that can build into their technology that kind of understanding,” she said.
“[Organisations need to] harness the strengths of AI and human beings and deliver those things seamlessly to a user in order to deliver a great customer experience.”
As organisations enter into the new territory that is emotional intelligence, van der Merwe recommends a long and hard think about AI’s impact on society, jobs, and the environment.
How Will Artificial Intelligence Affect Your Life | Jeff Dean | TEDxLA