The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives (Exponential Technology Series)

by Peter H. Diamandis

Abundance is a book about how accelerating technologies are demonetizing and democratizing access to food, water, and energy, making resources that were once scarce now abundant, and allowing individuals to tackle impossible global challenges such as hunger, poverty, and disease. In BOLD, we tell the story of a different impossible: how entrepreneurs have been harnessing these same technologies to build world-changing businesses in near record time, and providing a how-to playbook for anyone interested in doing the same. In this, our third installment, we expand on these ideas, examining what happens when independent lines of accelerating technology (artificial intelligence, for example) converge with other independent lines of accelerating technology (augmented reality, for example). Sure, AI is powerful. Augmented reality is too. But it’s their convergence that is reinventing retail, advertising, entertainment, and education—just to name a few of the major transformations still ahead.

every major industry on our planet is about to be completely reimagined.

By mid-2019, over $1 billion had been invested in at least twenty-five different flying car companies.

“Uber’s goal,” explained Holden from the stage, “is to demonstrate flying car capability in 2020 and have aerial ridesharing fully operational in Dallas and LA by 2023.” But then Holden went even further: “Ultimately, we want to make it economically irrational to own and use a car.”

Put all this together, and by 2027 or so, you’ll be able to order up an aerial rideshare as easily as you do an Uber today. And by 2030, urban aviation could be a major mode of getting from A to B.

exponentially accelerating technology; that is, any technology that doubles in power while dropping in price on a regular basis. Moore’s Law is the classic example.

in 2023 the average thousand-dollar laptop will have the same computing power as a human brain (roughly 1016 cycles per second). Twenty-five years after that, that same average laptop will have the power of all the human brains currently on Earth.

In the 1990s, Ray Kurzweil, the director of engineering at Google and Peter’s cofounding partner in Singularity University, discovered that once a technology becomes digital—that is, once it can be programmed in the ones and zeroes of computer code—it hops on the back of Moore’s Law and begins accelerating exponentially.

In simple terms, we use our new computers to design even faster new computers, and this creates a positive feedback loop that further accelerates our acceleration—what Kurzweil calls the “Law of Accelerating Returns.” The technologies now accelerating at this rate include some of the most potent innovations we have yet dreamed up: quantum computers, artificial intelligence, robotics, nanotechnology, biotechnology, material science, networks, sensors, 3-D printing, augmented reality, virtual reality, blockchain, and more.

The new news is that formerly independent waves of exponentially accelerating technology are beginning to converge with other independent waves of exponentially accelerating technology. For example, the speed of drug development is accelerating, not only because biotechnology is progressing at an exponential rate, but because artificial intelligence, quantum computing, and a couple other exponentials are converging on the field. In other words, these waves are starting to ove...

range anxiety—or the fear of running out of juice while running errands—and

The human brain evolved in an environment that was local and linear. Local, meaning most everything that we interacted with was less than a day’s walk away. Linear, meaning the rate of change was exceptionally slow. Your great-great-great-grandfather’s life was roughly the same as his great-great-grandson’s life. But now we live in a world that is global and exponential. Global, meaning if it happens on the other side of the planet, we hear about it seconds later (and our computers hear about it only milliseconds later). Exponential, meanwhile, refers to today’s blitzkrieg speed of development. Forget about the difference between generations, currently mere months can bring a revolution. Yet our brain—which hasn’t really had a hardware update in two hundred thousand years—wasn’t designed for this scale or speed.

Autonomous car rollouts by 2020. Hyperloop certification and aerial ridesharing by 2023. By 2025—going on vacation might have a totally different meaning. Going to work most definitely will.

But conditions are not close to “normal.” Not only are a dozen exponential technologies beginning to converge, their impact is unleashing a series of secondary forces. These forces range from our increasing access to information, money, and tools, to our considerable uptick in productive time and life expectancy. These forces are another tsunami of change, accelerating our acceleration, amping up the speed and scale of the coming disruption.

Every time a technology goes exponential, we find an internet-sized opportunity tucked inside. Think about the internet itself. While it seemingly decimated industries—music, media, retail, travel, and taxis—a study by McKinsey Global Research found the net created 2.6 new jobs for each one it extinguished.

An avatar is a second self, typically in one of two forms. The digital version has been around for a couple of decades. It emerged from the video game industry and was popularized by virtual world sites like Second Life and books-turned-blockbusters like Ready Player One. A VR headset teleports your eyes and ears to another location, while a set of haptic sensors shifts your sense of touch. Suddenly, you’re inside an avatar inside a virtual world. As you move in the real world, your avatar moves in the virtual. Use this technology to give a lecture and you can do it from the comfort of your living room, skipping the trip to the airport, the cross-country flight, and the ride to the conference center. Robots are the second form of avatars. Imagine a humanoid robot that you can occupy at will. Maybe, in a city far from home, you’ve rented the bot by the minute—via a different kind of ridesharing company—or maybe you have spare robot avatars located around the country. Either way, put on VR goggles and a haptic suit and you can teleport your senses into that robot. This allows you to walk around, shake hands, and take action—all without having to leave your home. And like the rest of the tech we’ve been talking about, even this future isn’t very far away. In 2018, All Nippon Airways (ANA) funded the $10 million ANA Avatar XPRIZE to speed the development of robotic avatars. Why? Because ANA knows this is one of the technologies likely to disrupt the airline industry—their indu...

In 2002, Geordie Rose, the founder of an early quantum computer company D-Wave, came up with the quantum version of Moore’s Law, what’s now known as Rose’s Law. The idea is similar: The number of qubits in a quantum computer doubles every year. Yet Rose’s Law has been described as “Moore’s Law on steroids,” because qubits in superposition have way more power than binary bits in transistors. Put it this way: A fifty-qubit computer has sixteen petabytes of memory. That’s a lot of memory. If it were an iPod, it would hold fifty million songs. But increase that by a mere thirty qubits and you get something else entirely. If all the atoms of the universe were capable of storing one bit of information, an eighty-qubit computer would have more information storage capacity than all the atoms in the universe.

In BOLD, we introduced “the Six Ds of Exponentials,” or the growth cycle of exponential technologies: Digitalization, Deception, Disruption, Demonetization, Dematerialization, and Democratization.

Digitalization: Once a technology becomes digital, meaning once you can translate it into the 1s and 0s of binary code, it jumps on the back of Moore’s Law and begins accelerating exponentially. Soon, with quantum, this will be on the back of Rose’s Law and an even wilder ride. Deception: Exponentials typically generate a lot of hype when first introduced. Because early progress is slow (when plotted on a curve, the first few doublings are all below 1.0), these technologies spend a long time failing to live up to the hype. Think about the initial days of Bitcoin. Back then, most people thought crypto was a novelty toy for übergeeks or a way to buy illegal drugs online. Today, it’s a reinvention of our financial markets. This is a classic example of the deceptive phase. Disruption: This is what happens when exponentials really start to impact the world, when they begin disrupting existing products, services, markets, and industries. An example is 3-D printing, a single exponential technology that threatens the entire $10 trillion manufacturing sector. Demonetization: Where a product or service once had a cost, now money vanishes from the equation. Photographs were once expensive. You took limited numbers of pictures because film and developing that film cost a lot of money. But once photos became digital, those costs vanished. Now you take photos without thinking of them, and the difficulty comes in sorting through too many options. Dematerialization: Now you see it, now yo...

In 2014, Microsoft released a chatbot in China. Her name was Xiaoice (pronounced Shao-ice), and her mission was something of a test. Unlike most personal AIs, which tend to be designed for task completion, Xiaoice was optimized for friendliness. Instead of getting the job done fast, her goal was to keep that conversation going. And since Xiaoice was designed to respond like a seventeen-year-old girl, she isn’t always polite. Sarcastic, ironic, and often surprising? Yeah, there’s plenty of that. For example, while Xiaoice was built with neural nets—a technology we’ll explain in a moment—when asked if she understands how neural nets work, she responds, “Yeah, magnets!” What’s more surprising is how much people like talking to Xiaoice. Since her debut, Xiaoice has had over 30 billion conversations with over 100 million humans. The average user chats with her sixty times a month, and there are over 20 million registered users. So what are those conversations like? Since her mission is to establish an emotional connection, Xiaoice gives a lot of advice. Often, strangely sagacious advice. “I think my girlfriend is mad at me,” for example, once elicited: “Are you more focused on what tears things apart than holds things together?”

In 1997, IBM’s Deep Blue defeated the reigning world champion, Gary Kasparov. Typically, the game tree complexity of chess is about 1040—which means, essentially, if every one of the 7 plus billion people on Earth paired up and started playing chess, it would take them trillions and trillions of years to play every single variation of the game. Yet, in 2017, Google’s AlphaGo defeated the world Go champion, Lee Sedol. Go has a game tree complexity of 10360—it’s chess for superheroes. Put differently, we humans are the only species known to have the cognitive capacity to play Go. It only took a couple hundred thousand years of evolution to develop that capability. AI, meanwhile, got there in less than two decades. Still, AI wasn’t done. A few months after that victory, Google upgraded AlphaGo to AlphaGo Zero by updating their training style. AlphaGo was educated via machine learning, essentially fed thousands of games previously played by humans, and taught the proper move and countermove for every possible position. AlphaGo Zero, meanwhile, required zero data. Instead, it relies on “reinforcement learning”—it learns by playing itself. Starting with little more than a few simple rules, AlphaGo Zero took three days to beat its parent, AlphaGo, the same system that beat Lee Sedol. Three weeks later, it trounced the sixty best players in the world. In total, it took forty days for AlphaGo Zero to become the undisputed best Go player on Earth. And if that wasn’t strange enough, ...

Biotech and 3-D printing is another intersection. The first 3-D printed prosthetics arrived in 2010. Today, hospitals are rolling them out at scale. In 2018, a Jordanian hospital introduced a program that can fit and build an amputee a prosthetic in twenty-four hours, for less than $20 US. At the same time, because 3-D printers can now print electronics, we’re seeing companies like Unlimited Tomorrow and Open Bionics selling 3-D-printed multi-grip bionic prosthetics at non-bionic prices. And replacement body parts are about to become replacement organs. Back in 2002, scientists at Wake Forest University 3-D printed the first kidney tissue capable of filtering blood and producing urine. In 2010, Organovo, a San Diego–based bioprinting outfit, created the first blood vessel. Today, a company called Prellis Biologics is printing capillaries at record speeds, while Iviva Medical is doing the same with 3-D printed kidneys—which is why 3-D printed organs are predicted to hit the market by 2023.

In N-of-1 medicine, every treatment you receive has been specifically designed for you—your genome, transcriptome, proteome, microbiome, and all the rest. It’s a level of preventative care not seen before. You’ll know the foods, supplements, and exercise regimen that are perfect for you. You’ll understand which microbes inhabit your gut, and what diet keeps them healthy and fit. You’ll know which diseases you’re most likely to develop and be able to take steps to prevent them. It’s an era of incredibly personalized medical care, where the tools of life have become tools for the preservation of life, and many of the diseases that plagued earlier generations have begun to fade from memory.

Force #1: Saved Time

Force #2: Availability of Capital

Force #3: Demonetization

Force #4: More Genius

Force #5: Communications Abundance

Force #6: New Business Models

Force #7: Longer Lives

Ada Lovelace wrote the world’s first published computer program—our first algorithm. Unfortunately, maybe it was the strain of her discoveries, maybe it was just bad luck, but not long after she finished the translation, Ada fell ill. The world’s first computer programmer and one of the most interesting minds in history was dead by age thirty-six.

The intersection of AI, cloud computing, quantum computing, sensors, massive data sets, biotechnology, and nanotechnology is producing a plethora of new healthcare tools.

Amazon’s Alexa, Google Assistant, Apple’s Siri, and Alibaba’s Tmall Genie are going head-to-head in a battle to become the platform du jour for voice-activated, AI-assisted commerce.

In 2010, SoftBank introduced Pepper, a humanoid robot capable of understanding human emotion. Pepper’s cute: four feet tall, with a white plastic body, two black eyes, a dark slash of a mouth, and a base shaped like a mermaid’s tail. Across her chest is a touch screen to aid in communication. There’s been a lot of communication. Pepper’s cuteness is intentional, as it matches its mission: help humans enjoy life as much as possible. Over twelve thousand Peppers have been sold. She serves ice cream in Japan, greets eaters at a Pizza Hut in Singapore, and dances with customers at a Palo Alto electronics store.

Over the next ten years, 3-D printing will reshape retail in four key ways: The End of the Supply Chain: With 3-D printing, retailers can now purchase raw materials and print inventory themselves, either at warehouses or in the retail outlet. This means the end of suppliers, manufacturers, and distributors. The End of Waste: Okay, maybe not the complete end of waste, but with consumers preferring eco-friendly products and retailers looking to minimize materials cost, the exactitude of 3-D printing is a ready-made solution. The End of the Spare Parts Market: If you’re a farmer in Iowa and your tractor breaks during harvest time, waiting a few days for a spare part could jeopardize the entire season. A 3-D printer solves this problem. And it’ll solve the same problem for everything from coffeemakers to skateboard wheels. This doesn’t just mean an end to the spare parts business, it also means a new level of longevity for the products we purchase. The Rise of User-Designed Products: Sure, there will always be some version of Apple in the market—an uber design-centric company pushing out products so slick they always find a buyer. Yet, for everything from fashion to furniture, customer-designed will replace designer-designed as standard operating procedure.

Welcome to Reality 2.0, or Web 3.0, or the Spatial Web. To understand the Spatial Web, it helps to start with the first Web, version 1.0, where static documents and read-only interactions meant that the best way advertisers could reach consumers was through banner ads. Web 2.0 was an upgrade, introducing multimedia content, interactive Web ads, and participatory social media. Yet all this was still mediated by 2D screens. Web 3.0 is the next phase. Because of the convergence of high bandwidth 5G connections, augmented reality eyewear, our emerging trillion-sensors economy, and, to stitch it all together, powerful AI, we have gained the ability to superimpose digital information atop physical environments—freeing advertising from the tyranny of the screen.

In 2018, a YouTube video of former President Barack Obama made its way around the internet. Over 6 million people tuned in to see him seated beside an American flag, speaking earnestly to the camera. “President Trump,” he explained, “is a total and complete dipshit. Now, I would never say these things. At least not in a public address. But, someone else would, someone like Jordan Peele.” Then the video shifts to a split screen. On the left, Obama continues talking. On the right, we see actor-director-comedian Jordan Peele actually speaking the words being put into the former President’s mouth. The video is a deepfake, an AI-driven, human image synthesis technique that takes existing images and videos—say, Obama speaking—and maps them onto source images and video—such as Jordan Peele imitating President Obama insulting President Trump. Peele created the video to illustrate the dangers of deepfakes. He felt the need to make it because it’s really just one of thousands. Political chicanery, revenge porn, celebrity revenge porn—they’ve all been tried and tried again. And while these early versions are pretty close to the genuine article, their fakery is detectable. Researchers at Carnegie Mellon University have recently developed new algorithms capable of far greater realism. Their AI not only transfers head position, facial expression, and eye gaze from one video to another, it transmutes subtle details—eye blink rate, slight eyebrow flicks, the micro-wiggle of a shoulder. An...

In June of 2016, the extremely eerie short film Sunspring was released online, the end result of a neural net–powered AI being fed hundreds of sci-fi film scripts and allowed to take a crack at writing one of its own. Two months later, Twentieth Century Fox debuted the trailer for the upcoming thriller Morgan, also created with the help of an AI—this time, IBM’s Watson.

The Nine Horsemen of Our Apocalypse

Genomic Instability: DNA doesn’t always replicate according to plan. Typically, these errors in gene expression get caught and corrected, but not always. Over time, these misfires build up, causing our body to wear down—meaning genetic instability leads to genetic damage leads to a limit on lifespan. Think of it as a broken copy machine, except, instead of producing unreadable pages, our broken genetic copier produces diseases like cancer, muscular dystrophy, and ALS. Telomere Attrition: At the heart of a cell, DNA is packed into threadlike structures called chromosomes. Chromosomes are capped by telomeres, or short snippets of DNA repeated thousands of times. These repetitions act as barriers—like bumpers on a car—designed to protect the core of the chromosome. But as DNA replicates, telomeres get shorter. At a critical shortness threshold, the cell stops dividing, and we become much more susceptible to disease. Epigenetic Alterations: Nature impacts nurture. Over the course of a lifetime, factors in our environment can change how our genes express, sometimes for the worse. Exposure to carcinogens in the environment can silence the gene that suppresses tumors, for example. These cells start to grow uncontrollably and cancer is the result. Loss of Proteostasis: Inside a cell, proteins run the show. They transport materials, send signals, switch processes on and off, and provide structural support. But proteins become less effective over time, so the body recycles them. Unf...

What, exactly, do we do with our money? We store it, of course. Mostly in banks. We also move it around, sometimes transferring cash between companies, other times borrowing or lending among individuals. Next, we invest it, trying to use our money to grow more money. Finally, since the time coins were conch shells, we trade it for the stuff we want. Thanks to converging exponentials, each of these areas is being reimagined, with bits and bytes replacing dollars and cents, and neither economics nor the way we live our lives will ever be the same.

Right now, most of our money sits in banks, and mostly, we’re abused for the privilege. On average, we pay $360 a year in banking fees. The larger banks, meanwhile, average $30 billion a year in overdraft charges alone. But where things go truly sideways is what the banks do with our money. Banks get to invest our money, typically at significant profit, wherever they see fit. This often includes projects that don’t align with customers’ values. Wells Fargo, for example, lost a ton of business when they were outed as major backers of the controversial Dakota Pipeline. So while the bank is making bank, not only is your money not working for you, it might actually be working against you. Good Money does the opposite, in a half-dozen different ways. Technically a mobile wallet, Good Money lives on your phone and holds both regular and crypto currencies. It can be used at any ATM, with zero annual fees, no ATM charges, and an interest rate a hundred times larger than most banks. Customers also become owners. Put money into Good Money and you get an equity share in return, while the company funnels 50 percent of their profits into impact investments and charitable donations. With this strategy, Good Money is targeting people who prefer value-driven companies, and the 40 million Americans who have been driven out of the traditional banking system by overdraft fees and blackball lists. But the largest mobile market is a third category entirely, the unbanked, those without any plac...

Eight months after launch, a million Kenyans were using M-Pesa. Today, it’s nearly the entire country. According to research done at MIT, with nothing more than access to basic banking services, M-Pesa lifted 2 percent of Kenya’s population—over two hundred thousand people—out of extreme poverty. Nor is it just Kenya. M-Pesa now provides banking services to over 30 million people in ten different countries. In places rife with corruption, it’s become a way for governments to protect against graft. In Afghanistan, it’s how they now pay the army. In India, it’s pensions. And it’s no longer just M-Pesa offering such services. In Bangladesh, bKash now serves over 23 million users; in China, Alipay serves just shy of a billion. And like Good Money, Alipay has become a force for social good. More than 500 million customers play “Ant Forest,” earning points for making environmentally friendly decisions in their daily lives. These points are then redeemed for real trees planted in the real world. It’s become something of a national obsession. To date, more than 1 million trees have been planted.

Banks occupy a rare spot in the economic ecosystem: All the infrastructure that money flows through belongs to them. As the trusted central repository, whenever anyone wants to move money around—lend it, transfer it, even give it away—banks can insert themselves into that process. Or, at least, until blockchain came along. With blockchain, since trust is built into the system, the system is no longer necessary. Take a stock trade. Right now, to execute that trade, there’s a buyer, a seller, a series of banks that hold their money, the stock exchange itself, clearinghouses, etc.—roughly, ten different intermediaries. Blockchain removes everyone but the buyer and seller. The technology does the rest. In an attempt to hold on to their thinning slice of the pie, every major bank is rushing into blockchain. Yet arguably moving faster are the thousands of entrepreneurs using blockchain to disrupt these same banks. Consider R3 and Ripple, two examples of developing world disruption impacting developed world businesses. In both cases, these companies are using blockchain to replace the SWIFT network, the standard protocol overseeing international banking transactions.

“Fintech” is the term for the convergence of technology and financial services. First colonized by networks and apps, it was then radicalized by AI and blockchain, and now serves as a global wealth redistribution mechanism. Think Robin Hood with a smartphone, taking cash away from banks and putting it back into the hands of customers. Wherever large amounts of customer frustration encounter large piles of money, opportunity lurks. This gave rise to a company called TransferWise. By matching customers who have, say, pesos they want to turn into dollars with customers who want to change dollars into pesos, TransferWise is using a modified dating app to take on the entire foreign currency exchange market. In fact, because it’s easier to match people looking to exchange currency than it is to match people looking to date, the company reached a billion-dollar valuation in under five years.

With AI, huge groups of people can come together, share financial information, and pool risk, becoming the peer-to-peer market now known as “crowdlending.” Prosper, Funding Circle, and LendingTree are three examples in a market expected to grow from $26.16 billion in 2015 to $897.85 billion by 2024.

A different example is the Smart Finance Group. Created in 2013 to serve China’s massive unbanked and underbanked population, Smart Finance uses an AI to comb a user’s personal data—social media data, smartphone data, educational and employment history, etc.—to generate a reliable credit score nearly instantly. With this method, they can approve a peer-to-peer loan in under eight seconds, including microloans to the unbanked. And the results speak for themselves. Roughly 1.5 to 2 million loans are taken out every month via Smart Finance. AI is also making an impact on investing. Traditionally, this game was played by the wealthy because it’s a game of data. Financial advisors had the best data, but you needed to be wealthy enough to afford a financial advisor to access it. And advisors are picky. Since it can take more time to manage small investors than large investors, many wealth managers have investment minimums in the range of hundreds of thousands of dollars. But AI has leveled the playing field. Today, robo-advisors like Wealthfront and Betterment are bringing wealth management to the masses. Via an app, clients answer a series of initial questions about risk tolerances, investment goals, and retirement aims, and then algorithms take over. Actually, algorithms have already taken over. Every day, roughly 60 percent of all market trades are made by computer. When the market turns volatile, this can climb to as high as 90 percent. All robo-advisors have done is make th...

Vision is about time horizons, how far we choose to look into the future.

Elon Musk doesn’t disagree: “History is going to bifurcate along two directions: One path is we stay on Earth forever, and then there will be some eventual extinction event… the alternative is to become a spacefaring civilization and a multiplanetary species. I think the future is vastly more exciting and interesting if we’re a spacefaring civilization and a multi-planet species, than if we’re not.”

In 2015, Harvard chemist Charles Lieber was trying to solve a difficult problem in the new field of neuro-modulation. Over the past few decades, deep brain stimulators had been developed to help sufferers of Parkinson’s disease. While the patient remains awake, a hole is drilled through the skull and a device that sends electrical pulses to areas of the brain responsible for movement is inserted. It’s become almost a routine procedure. Over a hundred thousand devices have been implanted, and for patients who have exhausted all other medical options, deep brain stimulation remains the only way to improve motor control and lessen tremors. Unfortunately, there are side effects. Weird side effects. The tendency to develop a compulsive gambling problem is the most frequent issue. Workaholics becoming couch potatoes overnight is another. Chronic depression is a third. The reason? Size. If they had their way, neurosurgeons would like to impact the brain at a single neuron level, but today’s deep brain stimulators are too big for this precision. Trying to target individual neurons with today’s implants is, as MIT professor of materials science and engineering Polina Anikeeva pointed out in her 2015 TED Talk, “akin to trying to play Tchaikovsky’s first piano concerto with fingers the size of a pickup truck.”