These 7 Disruptive Technologies Could Be Worth Trillions of Dollars

June 29, 2017

Scientists, technologists, engineers, and visionaries are building the future. Amazing things are in the pipeline. It’s a big deal. But you already knew all that. Such speculation is common. What’s less common? Scale.

How big is big?

“Silicon Valley, Silicon Alley, Silicon Dock, all of the Silicons around the world, they are dreaming the dream. They are innovating,” Catherine Wood said at Singularity University’s Exponential Finance in New York. “We are sizing the opportunity. That’s what we do.”

Catherine Wood at Exponential Finance.

Wood is founder and CEO of ARK Investment Management, a research and investment company focused on the growth potential of today’s disruptive technologies. Prior to ARK, she served as CIO of Global Thematic Strategies at AllianceBernstein for 12 years.

“We believe innovation is key to growth,” Wood said. “We are not focused on the past. We are focused on the future. We think there are tremendous opportunities in the public marketplace because this shift towards passive [investing] has created a lot of risk aversion and tremendous inefficiencies.”

In a new research report, released this week, ARK took a look at seven disruptive technologies, and put a number on just how tremendous they are. Here’s what they found.

(Check out ARK’s website and free report, “Big Ideas of 2017,” for more numbers, charts, and detail.)

1. Deep Learning Could Be Worth 35 Amazons

Deep learning is a subcategory of machine learning which is itself a subcategory of artificial intelligence. Deep learning is the source of much of the hype surrounding AI today. (You know you may be in a hype bubble when ads tout AI on Sunday golf commercial breaks.)

Behind the hype, however, big tech companies are pursuing deep learning to do very practical things. And whereas the internet, which unleashed trillions in market value, transformed several industries—news, entertainment, advertising, etc.—deep learning will work its way into even more, Wood said.

As deep learning advances, it should automate and improve technology, transportation, manufacturing, healthcare, finance, and more. And as is often the case with emerging technologies, it may form entirely new businesses we have yet to imagine.

“Bill Gates has said a breakthrough in machine learning would be worth 10 Microsofts. Microsoft is $550 to $600 billion,” Wood said. “We think deep learning is going to be twice that. We think [it] could approach $17 trillion in market cap—which would be 35 Amazons.”

2. Fleets of Autonomous Taxis to Overtake Automakers

Wood didn’t mince words about a future when cars drive themselves.

This is the biggest change that the automotive industry has ever faced,” she said.

Today’s automakers have a global market capitalization of a trillion dollars. Meanwhile, mobility-as-a-service companies as a whole (think ridesharing) are valued around $115 billion. If this number took into account expectations of a driverless future, it’d be higher.

The mobility-as-a-service market, which will slash the cost of “point-to-point” travel, could be worth more than today’s automakers combined, Wood said. Twice as much, in fact. As gross sales grow to something like $10 trillion in the early 2030s, her firm thinks some 20% of that will go to platform providers. It could be a $2 trillion opportunity.

Wood said a handful of companies will dominate the market, and Tesla is well positioned to be one of those companies. They are developing both the hardware, electric cars, and the software, self-driving algorithms. And although analysts tend to look at them as a just an automaker right now, that’s not all they’ll be down the road.

“We think if [Tesla] got even 5% of this global market for autonomous taxi networks, it should be worth another $100 billion today,” Wood said.

3. 3D Printing Goes Big With Finished Products at Scale

3D printing has become part of mainstream consciousness thanks, mostly, to the prospect of desktop printers for consumer prices. But these are imperfect, and the dream of an at-home replicator still eludes us. The manufacturing industry, however, is much closer to using 3D printers at scale.

Not long ago, we wrote about Carbon’s partnership with Adidas to mass-produce shoe midsoles. This is significant because, whereas industrial 3D printing has focused on prototyping to date, improving cost, quality, and speed are making it viable for finished products.

According to ARK, 3D printing may grow into a $41 billion market by 2020, and Wood noted a McKinsey forecast of as much as $490 billion by 2025. “McKinsey will be right if 3D printing actually becomes a part of the industrial production process, so end-use parts,” Wood said.

4. CRISPR Starts With Genetic Therapy, But It Doesn’t End There

According to ARK, the cost of genome editing has fallen 28x to 52x (depending on reagents) in the last four years. CRISPR is the technique leading the genome editing revolution, dramatically cutting time and cost while maintaining editing efficiency. Despite its potential, Wood said she isn’t hearing enough about it from investors yet.

“There are roughly 10,000 monogenic or single-gene diseases. Only 5% are treatable today,” she said. ARK believes treating these diseases is worth an annual $70 billion globally. Other areas of interest include stem cell therapy research, personalized medicine, drug development, agriculture, biofuels, and more.

Still, the big names in this area—Intellia, Editas, and CRISPR—aren’t on the radar.

“You can see if a company in this space has a strong IP position, as Genentech did in 1980, then the growth rates can be enormous,” Wood said. “Again, you don’t hear these names, and that’s quite interesting to me. We think there are very low expectations in that space.”

5. Mobile Transactions Could Grow 15x by 2020

By 2020, 75% of the world will own a smartphone, according to ARK. Amid smartphones’ many uses, mobile payments will be one of the most impactful. Coupled with better security (biometrics) and wider acceptance (NFC and point-of-sale), ARK thinks mobile transactions could grow 15x, from $1 trillion today to upwards of $15 trillion by 2020.

In addition, to making sharing economy transactions more frictionless, they are generally key to financial inclusion in emerging and developed markets, ARK says. And big emerging markets, such as India and China, are at the forefront, thanks to favorable regulations.

“Asia is leading the charge here,” Wood said. “You look at companies like Tencent and Alipay. They are really moving very quickly towards mobile and actually showing us the way.”

6. Robotics and Automation to Liberate $12 Trillion by 2035

Robots aren’t just for auto manufacturers anymore. Driven by continued cost declines and easier programming, more businesses are adopting robots. Amazon’s robot workforce in warehouses has grown from 1,000 to nearly 50,000 since 2014. “And they have never laid off anyone, other than for performance reasons, in their distribution centers,” Wood said.

But she understands fears over lost jobs.

This is only the beginning of a big round of automation driven by cheaper, smarter, safer, and more flexible robots. She agrees there will be a lot of displacement. Still, some commentators overlook associated productivity gains. By 2035, Wood said US GDP could be $12 trillion more than it would have been without robotics and automation—that’s a $40 trillion economy instead of a $28 trillion economy.

“This is the history of technology. Productivity. New products and services. It is our job as investors to figure out where that $12 trillion is,” Wood said. “We can’t even imagine it right now. We couldn’t imagine what the internet was going to do with us in the early ’90s.”

7. Blockchain and Cryptoassets: Speculatively Spectacular

Blockchain-enabled cryptoassets, such as Bitcoin, Ethereum, and Steem, have caused more than a stir in recent years. In addition to Bitcoin, there are now some 700 cryptoassets of various shapes and hues. Bitcoin still rules the roost with a market value of nearly $40 billion, up from just $3 billion two years ago, according to ARK. But it’s only half the total.

“This market is nascent. There are a lot of growing pains taking place right now in the crypto world, but the promise is there,” Wood said. “It’s a very hot space.”

Like all young markets, ARK says, cryptoasset markets are “characterized by enthusiasm, uncertainty, and speculation.” The firm’s blockchain products lead, Chris Burniske, uses Twitter—which is where he says the community congregates—to take the temperature. In a recent Twitter poll, 62% of respondents said they believed the market’s total value would exceed a trillion dollars in 10 years. In a followup, more focused on the trillion-plus crowd, 35% favored $1–$5 trillion, 17% guessed $5–$10 trillion, and 34% chose $10+ trillion.

Looking past the speculation, Wood believes there’s at least one big area blockchain and cryptoassets are poised to break into: the $500-billion, fee-based business of sending money across borders known as remittances.

“If you look at the Philippines-to-South Korean corridor, what you’re seeing already is that Bitcoin is 20% of the remittances market,” Wood said. “The migrant workers who are transmitting currency, they don’t know that Bitcoin is what’s enabling such a low-fee transaction. It’s the rails, effectively. They just see the fiat transfer. We think that that’s going to be a very exciting market.”

When Robots Take Over Most Jobs, What Will Be the Purpose of Humans?

September 6, 2014


In March of 2013, four economics researchers from the New York Federal Reserve published a report on job “polarization” — the phenomenon of routine task work disappearing and only the highest and lowest skilled work still available. The authors stated:

An occupation is routine if its main tasks require following explicit instructions and obeying well-defined rules. These tend to be middle-skilled jobs. If the job involves flexibility, problem solving or creativity, it’s considered nonroutine. Job polarization occurs when employment moves to nonroutine occupations, a category that contains the highest- and lowest-skilled jobs.

They based their analysis on data from the U.S. Census Bureau, which demonstrates that around 2005, the U.S. passed a threshold where more than 50 percent of all occupations are non-routine. In fact, extrapolating from the relatively straight line on the graph, at this point we should be over 60 percent nonroutine.

chart 1

These researchers also broke out the four quadrants of the work sphere, with routine versus nonroutine work arrayed against cognitive versus manual work.

routine nonroutine

The central takeaway from this exposition is that routine jobs have been decreasing in both cognitive and manual forms, and nonroutine jobs have been increasing largely in cognitive form. Again, here’s the census data:

chart 3

The indications are fairly stark. The work in routine occupations is trending toward zero. This fall lines up fairly well with the rise of automation of various kinds. For example, computer programs are doing the work of paralegals and x-ray technicians, and factory robots are displacing large numbers of automobile assembly line workers. There are applications that can write sports newspaper articles, based simply on the scoring history in the game.

Of course, for those who consider science fiction as the best oracle for an unknowable future, consider this shot in the dark from Isaac Asimov, who wrote in 1964 about a visit to the World’s Fair of 2014:

The world of A.D. 2014 will have few routine jobs that cannot be done better by some machine than by any human being. Mankind will therefore have become largely a race of machine tenders.

Soon, all that will be left for human beings will be the non-routine, creative work. How many of our occupations will our software overlords steal away from us? Many more than today, according to Carl Benedict Frey and Michael A. Osborne, two researchers at Oxford who looked at 702 current occupations.

“Soon, all that will be left for human beings will be the non-routine, creative work.”

The researchers found that approximately half of current occupations (47 percent) are at risk of going the way of the telephone operator within just a decade or two. These two researchers relied on the same matrix of work as the Federal Reserve team, and examined how quickly robotic dexterity and A.I. cognition would hollow out jobs that seem to be the preserve of humans today:

Our findings could be interpreted as two waves of computerisation, separated by a “technological plateau”. In the first wave, we find that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are likely to be substituted by computer capital.

Note that the “transportation and logistics” sector includes many occupations that will be slammed by autonomous vehicles, like truckers (the number one occupation for men in the U.S. currently), taxi drivers and warehouse workers. Administrative support is the number one job for women in the US, so our robot overlords are equal opportunity, at least.

Frey and Osborne suggest that the second future wave of displacement will come at some later date, when A.I. gains the secrets of creativity and social intelligence. That may take a longer time, but at some future date, lawyers, engineers, brain surgeons and even actors might be displaced by ‘bots. In fact, one venture capital firm, Deep Knowledge Ventures, has already appointed an algorithm to its board of directors.

“Lawyers, engineers, brain surgeons and even actors might be displaced by ‘bots.”

So, we are confronted with the critical question of 2025, as I stated in the recent Pew Internet report, AI, Robotics, and the Future of Jobs:

What are people for in a world that does not need their labor, and where only a minority are needed to guide the ‘bot-based economy?

While it is likely that for the next few decades the educated, creative and inventive will find avenues to gainful employment, that will not be the case for all. How will we organize our world if machines can provide goods and services at lower and lower costs while fewer and fewer have income enough to buy anything?

Can we educate our way out of this mess, or will people be forced into a return to the land, tending 40 acres with the help of several mechanical mules? Can we legislate a Luddite future, where the new levels of automation are made illegal? Or will the techno utopians be vindicated by new sorts of work — as yet unseen — emerge to engage the surplus workers now being displaced?

The end state is uncertain, but we are headed toward a disruption of our society on the same order of magnitude as the rise of agriculture and industrialism, but in a much more compressed time frame: decades, not generations or centuries. And that question — what are people for? — will taunt us because it’s unclear if there is an answer or whether it is just an irresolvable dilemma.

Scientists create circuit board modeled on the human brain

April 29, 2014


Human brain and circuits illustration (stock image). Stanford scientists have developed faster, more energy-efficient microchips based on the human brain — 9,000 times faster and using significantly less power than a typical PC. Credit: © agsandrew / Fotolia

Boahen and his team have developed Neurogrid, a circuit board consisting of 16 custom-designed “Neurocore” chips. Together these 16 chips can simulate 1 million neurons and billions of synaptic connections. The team designed these chips with power efficiency in mind. Their strategy was to enable certain synapses to share hardware circuits. The result was Neurogrid — a device about the size of an iPad that can simulate orders of magnitude more neurons and synapses than other brain mimics on the power it takes to run a tablet computer.

Stanford scientists have developed faster, more energy-efficient microchips based on the human brain — 9,000 times faster and using significantly less power than a typical PC. This offers greater possibilities for advances in robotics and a new way of understanding the brain. For instance, a chip as fast and efficient as the human brain could drive prosthetic limbs with the speed and complexity of our own actions.

Stanford scientists have developed a new circuit board modeled on the human brain, possibly opening up new frontiers in robotics and computing.

For all their sophistication, computers pale in comparison to the brain. The modest cortex of the mouse, for instance, operates 9,000 times faster than a personal computer simulation of its functions.

Not only is the PC slower, it takes 40,000 times more power to run, writes Kwabena Boahen, associate professor of bioengineering at Stanford, in an article for the Proceedings of the IEEE.

“From a pure energy perspective, the brain is hard to match,” says Boahen, whose article surveys how “neuromorphic” researchers in the United States and Europe are using silicon and software to build electronic systems that mimic neurons and synapses.

Boahen and his team have developed Neurogrid, a circuit board consisting of 16 custom-designed “Neurocore” chips. Together these 16 chips can simulate 1 million neurons and billions of synaptic connections. The team designed these chips with power efficiency in mind. Their strategy was to enable certain synapses to share hardware circuits. The result was Neurogrid — a device about the size of an iPad that can simulate orders of magnitude more neurons and synapses than other brain mimics on the power it takes to run a tablet computer.

The National Institutes of Health funded development of this million-neuron prototype with a five-year Pioneer Award. Now Boahen stands ready for the next steps — lowering costs and creating compiler software that would enable engineers and computer scientists with no knowledge of neuroscience to solve problems — such as controlling a humanoid robot — using Neurogrid.

Its speed and low power characteristics make Neurogrid ideal for more than just modeling the human brain. Boahen is working with other Stanford scientists to develop prosthetic limbs for paralyzed people that would be controlled by a Neurocore-like chip.

“Right now, you have to know how the brain works to program one of these,” said Boahen, gesturing at the $40,000 prototype board on the desk of his Stanford office. “We want to create a neurocompiler so that you would not need to know anything about synapses and neurons to able to use one of these.”

Brain ferment

In his article, Boahen notes the larger context of neuromorphic research, including the European Union’s Human Brain Project, which aims to simulate a human brain on a supercomputer. By contrast, the U.S. BRAIN Project — short for Brain Research through Advancing Innovative Neurotechnologies — has taken a tool-building approach by challenging scientists, including many at Stanford, to develop new kinds of tools that can read out the activity of thousands or even millions of neurons in the brain as well as write in complex patterns of activity.

Zooming from the big picture, Boahen’s article focuses on two projects comparable to Neurogrid that attempt to model brain functions in silicon and/or software.

One of these efforts is IBM’s SyNAPSE Project — short for Systems of Neuromorphic Adaptive Plastic Scalable Electronics. As the name implies, SyNAPSE involves a bid to redesign chips, code-named Golden Gate, to emulate the ability of neurons to make a great many synaptic connections — a feature that helps the brain solve problems on the fly. At present a Golden Gate chip consists of 256 digital neurons each equipped with 1,024 digital synaptic circuits, with IBM on track to greatly increase the numbers of neurons in the system.

Heidelberg University’s BrainScales project has the ambitious goal of developing analog chips to mimic the behaviors of neurons and synapses. Their HICANN chip — short for High Input Count Analog Neural Network — would be the core of a system designed to accelerate brain simulations, to enable researchers to model drug interactions that might take months to play out in a compressed time frame. At present, the HICANN system can emulate 512 neurons each equipped with 224 synaptic circuits, with a roadmap to greatly expand that hardware base.

Each of these research teams has made different technical choices, such as whether to dedicate each hardware circuit to modeling a single neural element (e.g., a single synapse) or several (e.g., by activating the hardware circuit twice to model the effect of two active synapses). These choices have resulted in different trade-offs in terms of capability and performance.

In his analysis, Boahen creates a single metric to account for total system cost — including the size of the chip, how many neurons it simulates and the power it consumes.

Neurogrid was by far the most cost-effective way to simulate neurons, in keeping with Boahen’s goal of creating a system affordable enough to be widely used in research.

Speed and efficiency

But much work lies ahead. Each of the current million-neuron Neurogrid circuit boards cost about $40,000. Boahen believes dramatic cost reductions are possible. Neurogrid is based on 16 Neurocores, each of which supports 65,536 neurons. Those chips were made using 15-year-old fabrication technologies.

By switching to modern manufacturing processes and fabricating the chips in large volumes, he could cut a Neurocore’s cost 100-fold — suggesting a million-neuron board for $400 a copy. With that cheaper hardware and compiler software to make it easy to configure, these neuromorphic systems could find numerous applications.

For instance, a chip as fast and efficient as the human brain could drive prosthetic limbs with the speed and complexity of our own actions — but without being tethered to a power source. Krishna Shenoy, an electrical engineering professor at Stanford and Boahen’s neighbor at the interdisciplinary Bio-X center, is developing ways of reading brain signals to understand movement. Boahen envisions a Neurocore-like chip that could be implanted in a paralyzed person’s brain, interpreting those intended movements and translating them to commands for prosthetic limbs without overheating the brain.

A small prosthetic arm in Boahen’s lab is currently controlled by Neurogrid to execute movement commands in real time. For now it doesn’t look like much, but its simple levers and joints hold hope for robotic limbs of the future.

Of course, all of these neuromorphic efforts are beggared by the complexity and efficiency of the human brain.

In his article, Boahen notes that Neurogrid is about 100,000 times more energy efficient than a personal computer simulation of 1 million neurons. Yet it is an energy hog compared to our biological CPU.

“The human brain, with 80,000 times more neurons than Neurogrid, consumes only three times as much power,” Boahen writes. “Achieving this level of energy efficiency while offering greater configurability and scale is the ultimate challenge neuromorphic engineers face.”

Story Source:

The above story is based on materials provided by Stanford University. The original article was written by Tom Abate. Note: Materials may be edited for content and length.

Journal Reference:

  1. Ben Varkey Benjamin, Peiran Gao, Emmett McQuinn, Swadesh Choudhary, Anand R. Chandrasekaran, Jean-Marie Bussat, Rodrigo Alvarez-Icaza, John V. Arthur, Paul A. Merolla, Kwabena Boahen. Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations. Proceedings of the IEEE, 2014; 1 DOI: 10.1109/JPROC.2014.2313565

The new technologies that will change human civilization as we know it

April 29, 2014


Where are technologies heading in the next 30 years ? How will they affect our lifestyle and human society ?

Most adults alive today grew up without the Internet or mobile phones, let alone smartphones and tablets with voice commands and apps for everything. These new technologies have altered our lifestyle in a way few of us could have imagined a few decades ago. But have we reached the end of the line ? What else could turn up that could make our lives so much more different ? Faster computers ? More gadgets ? It is in fact so much more than that. Technologies have embarked on an exponential growth curve and we are just getting started. In 10 years we will look back on our life today and wonder how we could have lived with such primitive technology. The gap will be bigger than between today and the 1980’s. Get ready because you are in for a rough ride.

Artificial Intelligence (AI), Supercomputers & Robotics

Ray Kurzweil, Google’s director of engineering, predicts that by 2029 computer will exhibit intelligent behaviour equivalent to that of a human, and that by 2045 computers will be a billion times more powerful than all of the human brains on Earth. Once computers can fully simulate a human brain and surpass it, it will cause an “intelligence explosion” that will radically change civilization. The rate of innovation will progress exponentially, so much that it will become impossible to foresee the future course of human history. This point in time is called the singularity. Experts believe that it will happen in the middle of the 21st century, perhaps as early as 2030, but the median value of predictions is 2040.

Let’s start with cognitive computing. IBM’s Watson computer is already capable of reading a million books a second and answering questions posed in natural language. In 2011 Watson easily defeated former champions Brad Rutter and Ken Jennings at the TV game show Jeopardy!, reputedly one of the most difficult quiz competitions in the world. Watson’s abilities are not merely limited to finding the relevant facts and answers. It can also make jokes and clever puns. Most remarkably, Watson can provide better medical diagnostics than any human medical doctor, give financial advice, as well as generate or evaluate all kinds of scientific hypotheses based on a huge amount of data. Computer power increases in average 100 fold every 10 years, which means 10,000 fold after 20 years, and 1 million fold after 30 years. Imagine what computers will be able to do by then.

The X Prize Foundation, chaired by Peter Diamandis, co-founder of Singularity University in the Silicon Valley, manages incentivized competitions to bring about radical breakthroughs for the benefit of humanity. One of the current competitions, the Nokia Sensing XCHALLENGE, aims at developing a smartphone-like device that can test vitals like cholesterol, blood pressure, heart rate or allergies, analyse your DNA for genetic risks, diagnose medical conditions, and predict potential diseases or the likelihood of a stroke. All this without seeing a doctor. The device could be used by you or your relatives anywhere, anytime. All this is possible thanks to highly sensitive electronic sensors and powerful AI.

Google is working on an AI that will be able to read and understand any document, and learn the content of all books in the world. It will be able to answer any question asked by any user. This omniscient AI will eventually become people’s first source of knowledge, replacing schools, books and even human interactions. Just wonder about anything and the computer will provide you with the answer and explain it to you in a way you can easily understand, based on your current knowledge.

Once AI reaches the same level of intelligence as a human brain, or exceeds it, intelligent robots will be able to do a majority of human jobs. Robots already manufacture most products. Soon they will also build roads and houses, replace human staff in supermarkets and shops, serve and perhaps even cook food in restaurants, take care of the sick and the elderly. The best doctors, even surgeons, will be robots.

It might still be a decade or two before human-like androids start walking the streets among us and working for us. But driverless cars, pioneered by Google and Tesla, could be introduced as early as 2016, and could become the dominant form of vehicles in developed countries by 2025. The advantages of autonomous cars are so overwhelming (less stress and exhaustion, fewer accidents, smoother traffic) that very few people will want to keep traditional cars. That is why the transition could happen as fast as, if not faster than the shift from analog phones to smartphones. Robo-Taxis are coming soon and could in time replace human taxi drivers. All cars and trains will eventually be entirely driven by computers.

AI will translate documents, answer customer support questions, complete administrative tasks, and teach kids and adults alike. It is estimated that 40 to 50% of service jobs will be done by AI in 2025. Creative jobs aren’t immune either, as computers will soon surpass humans in creativity too. There could still be human artists, but artistic value will drop to zero when any design or art can be produced on demand and on measure by AI in a few seconds.

Once computer graphics and AI simulation of human behaviours become so realistic that we can’t tell if a person in a video is real or not, Hollywood won’t need to use real actors anymore, but will be able to create movie stars that don’t exist – and the crazy thing is no one will notice the difference !

3-D Printing

3D printers are the biggest upheaval in manufacturing since the industrial revolution. Not only can we print objects in three dimensions, they can now be printed in practically any material, not just plastics, but also metals, concrete, fabrics, and even food. Better still, they can be printed in multiple materials at once. High-quality 3D printers can copy electronic chips in the tiniest detail and have a functional chip. High-tech vehicles like the Koenigsegg’s One:1 (the world’s fastest car) or EDAG’s Genesis are already being made by 3D Printing. Even houses will be 3D-printed, for a fraction of the costs of traditional construction.

In a near future we won’t need to go shopping to buy new products. We will just select them online, perhaps tweak a bit their design, size or colour to our tastes and needs, then we will just 3D print them at home. More jobs going down the drain ? Not really. Retail jobs were already going to be taken by intelligent robots anyway. The good news is that it will considerably reduce our carbon footprint by cutting unnecessary transport from distant factories in China or other parts of the world. Everything will be “home-made”, literally. Since any material can be re-used, or ‘recycled’ in a 3D printer, it will also dramatically reduce waste.

3D printing is also good news for medicine. Doctors can now make customized prosthetics, joint replacements, dental work and hearing aids.


The other advances in robotics, AI, 3-D printing and nanotechnologies all converge in the field of bioengineering. Human cyborgs aren’t science-fiction anymore. It’s already happening.

  • There are artificial hand with real feeling controlled directly by the brain thanks to a nerve interface converting electric impulses in the nervous system into electronic signals for the robotic prosthesis. From that point on, any improvement is possible, like this drummer who got an extra bionic arm.
  • Electronic membranes can keep the heart beating forever.
  • Microchips implanted into the brain can restore vision in blind people and hearing in deaf people. Soon such chips will allow bionic humans to see and hear better than humans in their natural state. Equipped with one of these, humans will be able to see ultraviolets and infrareds, hear ultrasounds like dogs, echolocate like bats, and perhaps even eventually understand animal languages, including the whale vocalization. The potential for improvements is unlimited.
  • We are on the verge of developing telepathic abilities. Placing microchips on the brains of two individuals, then connecting them with one another through the internet, one person can hear what the other hears directly in their brains. Studies with rats went further. Microchips implanted in their motor cortices effectively caused one rat to remotely control the movements of the another rat in a separate room.
  • Neural prostheses have been used to repair a damaged hippocampus inside a monkey’s brain, and could be used in a near future to repair various types of brain damages in human beings too.
  • Robotic exoskeletons like Iron Man will augment our physical capacities tremendously. The advantage of these exoskeletons is that they can be easily removed and don’t require permanent changes to our body. Researchers at Stanford University are currently working on Stickybot, a gecko robot capable of climbing smooth surfaces, such as glass, acrylic and whiteboard using directional adhesive. It’s only a matter of time (years, not decades) before a gecko suit enables humans to climb buildings like Spiderman. And what next ?

Stem cells & Bioprinting

Regenerative medicine offers even more promises than artificial limbs and body parts. What if instead of having a robotic arm, you could regrow completely your original arm ? Sounds impossible ? It isn’t. Lizard regrow their tails. Axolotls regrow severed legs. We now understand how they do it: stem cells. These pluripotent undifferentiated cells have the power to repair any body part. Using organ culture, stem cells can regrow any organ as fresh as new through. In the future it will be possible to regrow limbs or organs directly on a person, as if the body was simply healing itself.

Combing 3-D printing and stem cell regeneration paves the way to the printing of human organs, a field known as bioprinting (read articles on the topic in New Scientist and The Economist).


Genetics has progressed tremendously too over the last 15 years. From the sequencing of the first full human genome in 2003, we have now entered the era of personal genomics, gene therapy and synthetic life, and could be approaching the age of genetically enhanced humans.

Gene therapy is perhaps the most revolutionary of all the medical advances, as it will effectively allow to fix any disease-causing gene and to engineer humans that are better adapated to the modern nutrition, life rythmn, and technology-dominated lifestyle. Not only will all diseases and neuropsychological problems with a genetic cause disappear, but humans will also become more resistant to stress, fatigue and allergens, and could choose to boost their potential mental faculties and physical abilities, creating “superhumans”. This is known as transhumanism.

Gene therapy also permits genetic modifications for purely cosmetic reasons, such as changing one’s skin, hair or eye pigmentation. Gene therapy can be done over and over again, switching back or refining earlier modifications if necessary, just as one would edit text on a computer. Once the human genome is fully understood, we could even imagine applications that let people customize their physical appearance of a virtual avatar of themselves, then transcribe these changes to their DNA. This is the age of customizable humans, or rather the age of customizable life forms.

Vertical farming

Ecologist Dickson Despommier of Columbia University came up with the idea of using skyscrapers in New York for agricultural production, eventually founding the Vertical Farm Project. The virtues of vertical farming are manifold. Food can be produced in optimal conditions inside purposely-built skyscrapers, maximizing the amount of sunlight for photosynthesis. By controlling the inside temperature, and the amount of water and nutrients each plant receives, indoor farming can produce crops year-round ultiplying by a factor from 4 to 6 the productivity compared to traditional farming. What’s more all this is possible without using pesticides since skyscrapers are a closed ecosystem of their own, free of insects or rodents. Additionally, vertical farms free up agricultural land, which in turn prevents deforestation and allows for reforestation and the safeguard of the environment.

The end of the capitalist economy

Ironically it is the extreme success of the capitalist economy that will lead to its demise. The very nature of competitive markets that drives productivity up and brings marginal costs down, eventually to near zero, will make goods and services nearly free much sooner than we think. Accelerating factors include Moore’s law of exponential growth in digital technologies and the fast development of 3-D printing. The Internet alone has already had a huge impact in providing billions of people around the world with an amazing range of free services, including for example online higher education such as Khan Academy.


The first step is providing free ultrafast Internet to all the world. Google and Facebook are both working on different ways of achieving this, starting with developing countries where Internet connections are extremely sparse today, notably in Africa. Google’s Project Loon plans to acheive this by launching high-altitude balloons into the stratosphere, while Facebook wants to build flying drones and satellites to beam Internet around the world. 5G mobile networks (coming around 2020) will be so fast (downloading a full HD movie in one second) that cable Internet connections will disappear. The merger that is under way between TV, computers, tablets, smartphones and game consoles will very soon result in a single universal type of device being used everywhere, all connected via 5G networks. In other words, telephone, cable TV and Internet Service Providers will all go out of business, as all TVs and phones will be connected through free mobile networks.

By 2035, humanity is likely to have achieved free electricity for all the world, mostly thanks to the exponential efficiency and decreasing prices to harness solar energy, but also thanks to 4th generation nuclear reactors and later fusion power.

The Internet of Things will connect all the electric and electronic devices in the world and optimally manage energy supply through a smart-grid known as the Enernet, expected to become a reality around 2030.

Over the coming decades the economy is going to be transformed by the rise of the Collaborative Commons, i.e. peer production coordinated (usually with the aid of the Internet) into large, meaningful projects mostly without traditional hierarchical organization. Almost any consumer product will be downloadable online and 3-D printed at extremely low cost at home, which ultimately will lead to the end of capitalism and the start of an unprecedented era of abundance, as Peter Diamandis of Singularity University convincingly explains in his remarkable book.

Toward the Singularity

As amazing as all this seems, keep in mind that all these advances in bioengineering, genetics, robotics and 3-D printing are barely the what is being developed now and will become available to us within the next decade (horizon 2025). This isn’t the singularity yet. Once the singularity has been reached, in 25 to 40 years, this is when everything will change beyond our wildest dreams (or nightmares).

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