Tag Archives: automation

#434854 New Lifelike Biomaterial Self-Reproduces ...

Life demands flux.

Every living organism is constantly changing: cells divide and die, proteins build and disintegrate, DNA breaks and heals. Life demands metabolism—the simultaneous builder and destroyer of living materials—to continuously upgrade our bodies. That’s how we heal and grow, how we propagate and survive.

What if we could endow cold, static, lifeless robots with the gift of metabolism?

In a study published this month in Science Robotics, an international team developed a DNA-based method that gives raw biomaterials an artificial metabolism. Dubbed DASH—DNA-based assembly and synthesis of hierarchical materials—the method automatically generates “slime”-like nanobots that dynamically move and navigate their environments.

Like humans, the artificial lifelike material used external energy to constantly change the nanobots’ bodies in pre-programmed ways, recycling their DNA-based parts as both waste and raw material for further use. Some “grew” into the shape of molecular double-helixes; others “wrote” the DNA letters inside micro-chips.

The artificial life forms were also rather “competitive”—in quotes, because these molecular machines are not conscious. Yet when pitted against each other, two DASH bots automatically raced forward, crawling in typical slime-mold fashion at a scale easily seen under the microscope—and with some iterations, with the naked human eye.

“Fundamentally, we may be able to change how we create and use the materials with lifelike characteristics. Typically materials and objects we create in general are basically static… one day, we may be able to ‘grow’ objects like houses and maintain their forms and functions autonomously,” said study author Dr. Shogo Hamada to Singularity Hub.

“This is a great study that combines the versatility of DNA nanotechnology with the dynamics of living materials,” said Dr. Job Boekhoven at the Technical University of Munich, who was not involved in the work.

Dissipative Assembly
The study builds on previous ideas on how to make molecular Lego blocks that essentially assemble—and destroy—themselves.

Although the inspiration came from biological metabolism, scientists have long hoped to cut their reliance on nature. At its core, metabolism is just a bunch of well-coordinated chemical reactions, programmed by eons of evolution. So why build artificial lifelike materials still tethered by evolution when we can use chemistry to engineer completely new forms of artificial life?

Back in 2015, for example, a team led by Boekhoven described a way to mimic how our cells build their internal “structural beams,” aptly called the cytoskeleton. The key here, unlike many processes in nature, isn’t balance or equilibrium; rather, the team engineered an extremely unstable system that automatically builds—and sustains—assemblies from molecular building blocks when given an external source of chemical energy.

Sound familiar? The team basically built molecular devices that “die” without “food.” Thanks to the laws of thermodynamics (hey ya, Newton!), that energy eventually dissipates, and the shapes automatically begin to break down, completing an artificial “circle of life.”

The new study took the system one step further: rather than just mimicking synthesis, they completed the circle by coupling the building process with dissipative assembly.

Here, the “assembling units themselves are also autonomously created from scratch,” said Hamada.

DNA Nanobots
The process of building DNA nanobots starts on a microfluidic chip.

Decades of research have allowed researchers to optimize DNA assembly outside the body. With the help of catalysts, which help “bind” individual molecules together, the team found that they could easily alter the shape of the self-assembling DNA bots—which formed fiber-like shapes—by changing the structure of the microfluidic chambers.

Computer simulations played a role here too: through both digital simulations and observations under the microscope, the team was able to identify a few critical rules that helped them predict how their molecules self-assemble while navigating a maze of blocking “pillars” and channels carved onto the microchips.

This “enabled a general design strategy for the DASH patterns,” they said.

In particular, the whirling motion of the fluids as they coursed through—and bumped into—ridges in the chips seems to help the DNA molecules “entangle into networks,” the team explained.

These insights helped the team further develop the “destroying” part of metabolism. Similar to linking molecules into DNA chains, their destruction also relies on enzymes.

Once the team pumped both “generation” and “degeneration” enzymes into the microchips, along with raw building blocks, the process was completely autonomous. The simultaneous processes were so lifelike that the team used a metric commonly used in robotics, finite-state automation, to measure the behavior of their DNA nanobots from growth to eventual decay.

“The result is a synthetic structure with features associated with life. These behaviors include locomotion, self-regeneration, and spatiotemporal regulation,” said Boekhoven.

Molecular Slime Molds
Just witnessing lifelike molecules grow in place like the dance move running man wasn’t enough.

In their next experiments, the team took inspiration from slugs to program undulating movements into their DNA bots. Here, “movement” is actually a sort of illusion: the machines “moved” because their front ends kept regenerating, whereas their back ends degenerated. In essence, the molecular slime was built from linking multiple individual “DNA robot-like” units together: each unit receives a delayed “decay” signal from the head of the slime in a way that allowed the whole artificial “organism” to crawl forward, against the steam of fluid flow.

Here’s the fun part: the team eventually engineered two molecular slime bots and pitted them against each other, Mario Kart-style. In these experiments, the faster moving bot alters the state of its competitor to promote “decay.” This slows down the competitor, allowing the dominant DNA nanoslug to win in a race.

Of course, the end goal isn’t molecular podracing. Rather, the DNA-based bots could easily amplify a given DNA or RNA sequence, making them efficient nano-diagnosticians for viral and other infections.

The lifelike material can basically generate patterns that doctors can directly ‘see’ with their eyes, which makes DNA or RNA molecules from bacteria and viruses extremely easy to detect, the team said.

In the short run, “the detection device with this self-generating material could be applied to many places and help people on site, from farmers to clinics, by providing an easy and accurate way to detect pathogens,” explained Hamaga.

A Futuristic Iron Man Nanosuit?
I’m letting my nerd flag fly here. In Avengers: Infinity Wars, the scientist-engineer-philanthropist-playboy Tony Stark unveiled a nanosuit that grew to his contours when needed and automatically healed when damaged.

DASH may one day realize that vision. For now, the team isn’t focused on using the technology for regenerating armor—rather, the dynamic materials could create new protein assemblies or chemical pathways inside living organisms, for example. The team also envisions adding simple sensing and computing mechanisms into the material, which can then easily be thought of as a robot.

Unlike synthetic biology, the goal isn’t to create artificial life. Rather, the team hopes to give lifelike properties to otherwise static materials.

“We are introducing a brand-new, lifelike material concept powered by its very own artificial metabolism. We are not making something that’s alive, but we are creating materials that are much more lifelike than have ever been seen before,” said lead author Dr. Dan Luo.

“Ultimately, our material may allow the construction of self-reproducing machines… artificial metabolism is an important step toward the creation of ‘artificial’ biological systems with dynamic, lifelike capabilities,” added Hamada. “It could open a new frontier in robotics.”

Image Credit: A timelapse image of DASH, by Jeff Tyson at Cornell University. Continue reading

Posted in Human Robots

#434797 This Week’s Awesome Stories From ...

GENE EDITING
Genome Engineers Made More Than 13,000 Genome Edits in a Single Cell
Antonio Regalado | MIT Technology Review
“The group, led by gene technologist George Church, wants to rewrite genomes at a far larger scale than has currently been possible, something it says could ultimately lead to the ‘radical redesign’ of species—even humans.”

ROBOTICS
Inside Google’s Rebooted Robotics Program
Cade Metz | The New York Times
“Google’s new lab is indicative of a broader effort to bring so-called machine learning to robotics. …Many believe that machine learning—not extravagant new devices—will be the key to developing robotics for manufacturing, warehouse automation, transportation and many other tasks.

VIDEOS
Boston Dynamics Builds the Warehouse Robot of Jeff Bezos’ Dreams
Luke Dormehl | Digital Trends
“…for anyone wondering what the future of warehouse operation is likely to look like, this offers a far more practical glimpse of the years to come than, say, a dancing dog robot. As Boston Dynamics moves toward commercializing its creations for the first time, this could turn out to be a lot closer than you might think.”

TECHNOLOGY
Europe Is Splitting the Internet Into Three
Casey Newton | The Verge
“The internet had previously been divided into two: the open web, which most of the world could access; and the authoritarian web of countries like China, which is parceled out stingily and heavily monitored. As of today, though, the web no longer feels truly worldwide. Instead we now have the American internet, the authoritarian internet, and the European internet. How does the EU Copyright Directive change our understanding of the web?”

VIRTUAL REALITY
No Man’s Sky’s Next Update Will Let You Explore Infinite Space in Virtual Reality
Taylor Hatmaker | TechCrunch
“Assuming the game runs well enough, No Man’s Sky Virtual Reality will be a far cry from gimmicky VR games that lack true depth, offering one of the most expansive—if not the most expansive—VR experiences to date.”

3D PRINTING
3D Metal Printing Tries to Break Into the Manufacturing Mainstream
Mark Anderson | IEEE Spectrum
“It’s been five or so years since 3D printing was at peak hype. Since then, the technology has edged its way into a new class of materials and started to break into more applications. Today, 3D printers are being seriously considered as a means to produce stainless steel 5G smartphones, high-strength alloy gas-turbine blades, and other complex metal parts.”

Image Credit: ale de sun / Shutterstock.com Continue reading

Posted in Human Robots

#434781 What Would It Mean for AI to Become ...

As artificial intelligence systems take on more tasks and solve more problems, it’s hard to say which is rising faster: our interest in them or our fear of them. Futurist Ray Kurzweil famously predicted that “By 2029, computers will have emotional intelligence and be convincing as people.”

We don’t know how accurate this prediction will turn out to be. Even if it takes more than 10 years, though, is it really possible for machines to become conscious? If the machines Kurzweil describes say they’re conscious, does that mean they actually are?

Perhaps a more relevant question at this juncture is: what is consciousness, and how do we replicate it if we don’t understand it?

In a panel discussion at South By Southwest titled “How AI Will Design the Human Future,” experts from academia and industry discussed these questions and more.

Wait, What Is AI?
Most of AI’s recent feats—diagnosing illnesses, participating in debate, writing realistic text—involve machine learning, which uses statistics to find patterns in large datasets then uses those patterns to make predictions. However, “AI” has been used to refer to everything from basic software automation and algorithms to advanced machine learning and deep learning.

“The term ‘artificial intelligence’ is thrown around constantly and often incorrectly,” said Jennifer Strong, a reporter at the Wall Street Journal and host of the podcast “The Future of Everything.” Indeed, one study found that 40 percent of European companies that claim to be working on or using AI don’t actually use it at all.

Dr. Peter Stone, associate chair of computer science at UT Austin, was the study panel chair on the 2016 One Hundred Year Study on Artificial Intelligence (or AI100) report. Based out of Stanford University, AI100 is studying and anticipating how AI will impact our work, our cities, and our lives.

“One of the first things we had to do was define AI,” Stone said. They defined it as a collection of different technologies inspired by the human brain to be able to perceive their surrounding environment and figure out what actions to take given these inputs.

Modeling on the Unknown
Here’s the crazy thing about that definition (and about AI itself): we’re essentially trying to re-create the abilities of the human brain without having anything close to a thorough understanding of how the human brain works.

“We’re starting to pair our brains with computers, but brains don’t understand computers and computers don’t understand brains,” Stone said. Dr. Heather Berlin, cognitive neuroscientist and professor of psychiatry at the Icahn School of Medicine at Mount Sinai, agreed. “It’s still one of the greatest mysteries how this three-pound piece of matter can give us all our subjective experiences, thoughts, and emotions,” she said.

This isn’t to say we’re not making progress; there have been significant neuroscience breakthroughs in recent years. “This has been the stuff of science fiction for a long time, but now there’s active work being done in this area,” said Amir Husain, CEO and founder of Austin-based AI company Spark Cognition.

Advances in brain-machine interfaces show just how much more we understand the brain now than we did even a few years ago. Neural implants are being used to restore communication or movement capabilities in people who’ve been impaired by injury or illness. Scientists have been able to transfer signals from the brain to prosthetic limbs and stimulate specific circuits in the brain to treat conditions like Parkinson’s, PTSD, and depression.

But much of the brain’s inner workings remain a deep, dark mystery—one that will have to be further solved if we’re ever to get from narrow AI, which refers to systems that can perform specific tasks and is where the technology stands today, to artificial general intelligence, or systems that possess the same intelligence level and learning capabilities as humans.

The biggest question that arises here, and one that’s become a popular theme across stories and films, is if machines achieve human-level general intelligence, does that also mean they’d be conscious?

Wait, What Is Consciousness?
As valuable as the knowledge we’ve accumulated about the brain is, it seems like nothing more than a collection of disparate facts when we try to put it all together to understand consciousness.

“If you can replace one neuron with a silicon chip that can do the same function, then replace another neuron, and another—at what point are you still you?” Berlin asked. “These systems will be able to pass the Turing test, so we’re going to need another concept of how to measure consciousness.”

Is consciousness a measurable phenomenon, though? Rather than progressing by degrees or moving through some gray area, isn’t it pretty black and white—a being is either conscious or it isn’t?

This may be an outmoded way of thinking, according to Berlin. “It used to be that only philosophers could study consciousness, but now we can study it from a scientific perspective,” she said. “We can measure changes in neural pathways. It’s subjective, but depends on reportability.”

She described three levels of consciousness: pure subjective experience (“Look, the sky is blue”), awareness of one’s own subjective experience (“Oh, it’s me that’s seeing the blue sky”), and relating one subjective experience to another (“The blue sky reminds me of a blue ocean”).

“These subjective states exist all the way down the animal kingdom. As humans we have a sense of self that gives us another depth to that experience, but it’s not necessary for pure sensation,” Berlin said.

Husain took this definition a few steps farther. “It’s this self-awareness, this idea that I exist separate from everything else and that I can model myself,” he said. “Human brains have a wonderful simulator. They can propose a course of action virtually, in their minds, and see how things play out. The ability to include yourself as an actor means you’re running a computation on the idea of yourself.”

Most of the decisions we make involve envisioning different outcomes, thinking about how each outcome would affect us, and choosing which outcome we’d most prefer.

“Complex tasks you want to achieve in the world are tied to your ability to foresee the future, at least based on some mental model,” Husain said. “With that view, I as an AI practitioner don’t see a problem implementing that type of consciousness.”

Moving Forward Cautiously (But Not too Cautiously)
To be clear, we’re nowhere near machines achieving artificial general intelligence or consciousness, and whether a “conscious machine” is possible—not to mention necessary or desirable—is still very much up for debate.

As machine intelligence continues to advance, though, we’ll need to walk the line between progress and risk management carefully.

Improving the transparency and explainability of AI systems is one crucial goal AI developers and researchers are zeroing in on. Especially in applications that could mean the difference between life and death, AI shouldn’t advance without people being able to trace how it’s making decisions and reaching conclusions.

Medicine is a prime example. “There are already advances that could save lives, but they’re not being used because they’re not trusted by doctors and nurses,” said Stone. “We need to make sure there’s transparency.” Demanding too much transparency would also be a mistake, though, because it will hinder the development of systems that could at best save lives and at worst improve efficiency and free up doctors to have more face time with patients.

Similarly, self-driving cars have great potential to reduce deaths from traffic fatalities. But even though humans cause thousands of deadly crashes every day, we’re terrified by the idea of self-driving cars that are anything less than perfect. “If we only accept autonomous cars when there’s zero probability of an accident, then we will never accept them,” Stone said. “Yet we give 16-year-olds the chance to take a road test with no idea what’s going on in their brains.”

This brings us back to the fact that, in building tech modeled after the human brain—which has evolved over millions of years—we’re working towards an end whose means we don’t fully comprehend, be it something as basic as choosing when to brake or accelerate or something as complex as measuring consciousness.

“We shouldn’t charge ahead and do things just because we can,” Stone said. “The technology can be very powerful, which is exciting, but we have to consider its implications.”

Image Credit: agsandrew / Shutterstock.com Continue reading

Posted in Human Robots

#434772 Traditional Higher Education Is Losing ...

Should you go to graduate school? If so, why? If not, what are your alternatives? Millions of young adults across the globe—and their parents and mentors—find themselves asking these questions every year.

Earlier this month, I explored how exponential technologies are rising to meet the needs of the rapidly changing workforce.

In this blog, I’ll dive into a highly effective way to build the business acumen and skills needed to make the most significant impact in these exponential times.

To start, let’s dive into the value of graduate school versus apprenticeship—especially during this time of extraordinarily rapid growth, and the micro-diversification of careers.

The True Value of an MBA
All graduate schools are not created equal.

For complex technical trades like medicine, engineering, and law, formal graduate-level training provides a critical foundation for safe, ethical practice (until these trades are fully augmented by artificial intelligence and automation…).

For the purposes of today’s blog, let’s focus on the value of a Master in Business Administration (MBA) degree, compared to acquiring your business acumen through various forms of apprenticeship.

The Waning of Business Degrees
Ironically, business schools are facing a tough business problem. The rapid rate of technological change, a booming job market, and the digitization of education are chipping away at the traditional graduate-level business program.

The data speaks for itself.

The Decline of Graduate School Admissions
Enrollment in two-year, full-time MBA programs in the US fell by more than one-third from 2010 to 2016.

While in previous years, top business schools (e.g. Stanford, Harvard, and Wharton) were safe from the decrease in applications, this year, they also felt the waning interest in MBA programs.

Harvard Business School: 4.5 percent decrease in applications, the school’s biggest drop since 2005.
Wharton: 6.7 percent decrease in applications.
Stanford Graduate School: 4.6 percent decrease in applications.

Another signal of change began unfolding over the past week. You may have read news headlines about an emerging college admissions scam, which implicates highly selective US universities, sports coaches, parents, and students in a conspiracy to game the undergraduate admissions process.

Already, students are filing multibillion-dollar civil lawsuits arguing that the scheme has devalued their degrees or denied them a fair admissions opportunity.

MBA Graduates in the Workforce
To meet today’s business needs, startups and massive companies alike are increasingly hiring technologists, developers, and engineers in place of the MBA graduates they may have preferentially hired in the past.

While 85 percent of US employers expect to hire MBA graduates this year (a decrease from 91 percent in 2017), 52 percent of employers worldwide expect to hire graduates with a master’s in data analytics (an increase from 35 percent last year).

We’re also seeing the waning of MBA degree holders at the CEO level.

For decades, an MBA was the hallmark of upward mobility towards the C-suite of top companies.

But as exponential technologies permeate not only products but every part of the supply chain—from manufacturing and shipping to sales, marketing and customer service—that trend is changing by necessity.

Looking at the Harvard Business Review’s Top 100 CEOs in 2018 list, more CEOs on the list held engineering degrees than MBAs (34 held engineering degrees, while 32 held MBAs).

There’s much more to leading innovative companies than an advanced business degree.

How Are Schools Responding?
With disruption to the advanced business education system already here, some business schools are applying notes from their own innovation classes to brace for change.

Over the past half-decade, we’ve seen schools with smaller MBA programs shut their doors in favor of advanced degrees with more specialization. This directly responds to market demand for skills in data science, supply chain, and manufacturing.

Some degrees resemble the precise skills training of technical trades. Others are very much in line with the apprenticeship models we’ll explore next.

Regardless, this new specialization strategy is working and attracting more new students. Over the past decade (2006 to 2016), enrollment in specialized graduate business programs doubled.

Higher education is also seeing a preference shift toward for-profit trade schools, like coding boot camps. This shift is one of several forces pushing universities to adopt skill-specific advanced degrees.

But some schools are slow to adapt, raising the question: how and when will these legacy programs be disrupted? A survey of over 170 business school deans around the world showed that many programs are operating at a loss.

But if these schools are world-class business institutions, as advertised, why do they keep the doors open even while they lose money? The surveyed deans revealed an important insight: they keep the degree program open because of the program’s prestige.

Why Go to Business School?
Shorthand Credibility, Cognitive Biases, and Prestige
Regardless of what knowledge a person takes away from graduate school, attending one of the world’s most rigorous and elite programs gives grads external validation.

With over 55 percent of MBA applicants applying to just 6 percent of graduate business schools, we have a clear cognitive bias toward the perceived elite status of certain universities.

To the outside world, thanks to the power of cognitive biases, an advanced degree is credibility shorthand for your capabilities.

Simply passing through a top school’s filtration system means that you had some level of abilities and merits.

And startup success statistics tend to back up that perceived enhanced capability. Let’s take, for example, universities with the most startup unicorn founders (see the figure below).

When you consider the 320+ unicorn startups around the world today, these numbers become even more impressive. Stanford’s 18 unicorn companies account for over 5 percent of global unicorns, and Harvard is responsible for producing just under 5 percent.

Combined, just these two universities (out of over 5,000 in the US, and thousands more around the world) account for 1 in 10 of the billion-dollar private companies in the world.

By the numbers, the prestigious reputation of these elite business programs has a firm basis in current innovation success.

While prestige may be inherent to the degree earned by graduates from these business programs, the credibility boost from holding one of these degrees is not a guaranteed path to success in the business world.

For example, you might expect that the Harvard School of Business or Stanford Graduate School of Business would come out on top when tallying up the alma maters of Fortune 500 CEOs.

It turns out that the University of Wisconsin-Madison leads the business school pack with 14 CEOs to Harvard’s 12. Beyond prestige, the success these elite business programs see translates directly into cultivating unmatched networks and relationships.

Relationships
Graduate schools—particularly at the upper echelon—are excellent at attracting sharp students.

At an elite business school, if you meet just five to ten people with extraordinary skill sets, personalities, ideas, or networks, then you have returned your $200,000 education investment.

It’s no coincidence that some 40 percent of Silicon Valley venture capitalists are alumni of either Harvard or Stanford.

From future investors to advisors, friends, and potential business partners, relationships are critical to an entrepreneur’s success.

Apprenticeships
As we saw above, graduate business degree programs are melting away in the current wave of exponential change.

With an increasing $1.5 trillion in student debt, there must be a more impactful alternative to attending graduate school for those starting their careers.

When I think about the most important skills I use today as an entrepreneur, writer, and strategic thinker, they didn’t come from my decade of graduate school at Harvard or MIT… they came from my experiences building real technologies and companies, and working with mentors.

Apprenticeship comes in a variety of forms; here, I’ll cover three top-of-mind approaches:

Real-world business acumen via startup accelerators
A direct apprenticeship model
The 6 D’s of mentorship

Startup Accelerators and Business Practicum
Let’s contrast the shrinking interest in MBA programs with applications to a relatively new model of business education: startup accelerators.

Startup accelerators are short-term (typically three to six months), cohort-based programs focusing on providing startup founders with the resources (capital, mentorship, relationships, and education) needed to refine their entrepreneurial acumen.

While graduate business programs have been condensing, startup accelerators are alive, well, and expanding rapidly.

In the 10 years from 2005 (when Paul Graham founded Y Combinator) through 2015, the number of startup accelerators in the US increased by more than tenfold.

The increase in startup accelerator activity hints at a larger trend: our best and brightest business minds are opting to invest their time and efforts in obtaining hands-on experience, creating tangible value for themselves and others, rather than diving into the theory often taught in business school classrooms.

The “Strike Force” Model
The Strike Force is my elite team of young entrepreneurs who work directly with me across all of my companies, travel by my side, sit in on every meeting with me, and help build businesses that change the world.

Previous Strike Force members have gone on to launch successful companies, including Bold Capital Partners, my $250 million venture capital firm.

Strike Force is an apprenticeship for the next generation of exponential entrepreneurs.

To paraphrase my good friend Tony Robbins: If you want to short-circuit the video game, find someone who’s been there and done that and is now doing something you want to one day do.

Every year, over 500,000 apprentices in the US follow this precise template. These apprentices are learning a craft they wish to master, under the mentorship of experts (skilled metal workers, bricklayers, medical technicians, electricians, and more) who have already achieved the desired result.

What if we more readily applied this model to young adults with aspirations of creating massive value through the vehicles of entrepreneurship and innovation?

For the established entrepreneur: How can you bring young entrepreneurs into your organization to create more value for your company, while also passing on your ethos and lessons learned to the next generation?

For the young, driven millennial: How can you find your mentor and convince him or her to take you on as an apprentice? What value can you create for this person in exchange for their guidance and investment in your professional development?

The 6 D’s of Mentorship
In my last blog on education, I shared how mobile device and internet penetration will transform adult literacy and basic education. Mobile phones and connectivity already create extraordinary value for entrepreneurs and young professionals looking to take their business acumen and skill set to the next level.

For all of human history up until the last decade or so, if you wanted to learn from the best and brightest in business, leadership, or strategy, you either needed to search for a dated book that they wrote at the local library or bookstore, or you had to be lucky enough to meet that person for a live conversation.

Now you can access the mentorship of just about any thought leader on the planet, at any time, for free.

Thanks to the power of the internet, mentorship has digitized, demonetized, dematerialized, and democratized.

What do you want to learn about?

Investing? Leadership? Technology? Marketing? Project management?

You can access a near-infinite stream of cutting-edge tools, tactics, and lessons from thousands of top performers from nearly every field—instantaneously, and for free.

For example, every one of Warren Buffett’s letters to his Berkshire Hathaway investors over the past 40 years is available for free on a device that fits in your pocket.

The rise of audio—particularly podcasts and audiobooks—is another underestimated driving force away from traditional graduate business programs and toward apprenticeships.

Over 28 million podcast episodes are available for free. Once you identify the strong signals in the noise, you’re still left with thousands of hours of long-form podcast conversation from which to learn valuable lessons.

Whenever and wherever you want, you can learn from the world’s best. In the future, mentorship and apprenticeship will only become more personalized. Imagine accessing a high-fidelity, AI-powered avatar of Bill Gates, Richard Branson, or Arthur C. Clarke (one of my early mentors) to help guide you through your career.

Virtual mentorship and coaching are powerful education forces that are here to stay.

Bringing It All Together
The education system is rapidly changing. Traditional master’s programs for business are ebbing away in the tides of exponential technologies. Apprenticeship models are reemerging as an effective way to train tomorrow’s leaders.

In a future blog, I’ll revisit the concept of apprenticeships and other effective business school alternatives.

If you are a young, ambitious entrepreneur (or the parent of one), remember that you live in the most abundant time ever in human history to refine your craft.

Right now, you have access to world-class mentorship and cutting-edge best-practices—literally in the palm of your hand. What will you do with this extraordinary power?

Join Me
Abundance-Digital Online Community: I’ve created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is my ‘onramp’ for exponential entrepreneurs – those who want to get involved and play at a higher level. Click here to learn more.

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Posted in Human Robots

#434753 Top Takeaways From The Economist ...

Over the past few years, the word ‘innovation’ has degenerated into something of a buzzword. In fact, according to Vijay Vaitheeswaran, US business editor at The Economist, it’s one of the most abused words in the English language.

The word is over-used precisely because we’re living in a great age of invention. But the pace at which those inventions are changing our lives is fast, new, and scary.

So what strategies do companies need to adopt to make sure technology leads to growth that’s not only profitable, but positive? How can business and government best collaborate? Can policymakers regulate the market without suppressing innovation? Which technologies will impact us most, and how soon?

At The Economist Innovation Summit in Chicago last week, entrepreneurs, thought leaders, policymakers, and academics shared their insights on the current state of exponential technologies, and the steps companies and individuals should be taking to ensure a tech-positive future. Here’s their expert take on the tech and trends shaping the future.

Blockchain
There’s been a lot of hype around blockchain; apparently it can be used for everything from distributing aid to refugees to voting. However, it’s too often conflated with cryptocurrencies like Bitcoin, and we haven’t heard of many use cases. Where does the technology currently stand?

Julie Sweet, chief executive of Accenture North America, emphasized that the technology is still in its infancy. “Everything we see today are pilots,” she said. The most promising of these pilots are taking place across three different areas: supply chain, identity, and financial services.

When you buy something from outside the US, Sweet explained, it goes through about 80 different parties. 70 percent of the relevant data is replicated and is prone to error, with paper-based documents often to blame. Blockchain is providing a secure way to eliminate paper in supply chains, upping accuracy and cutting costs in the process.

One of the most prominent use cases in the US is Walmart—the company has mandated that all suppliers in its leafy greens segment be on a blockchain, and its food safety has improved as a result.

Beth Devin, head of Citi Ventures’ innovation network, added “Blockchain is an infrastructure technology. It can be leveraged in a lot of ways. There’s so much opportunity to create new types of assets and securities that aren’t accessible to people today. But there’s a lot to figure out around governance.”

Open Source Technology
Are the days of proprietary technology numbered? More and more companies and individuals are making their source code publicly available, and its benefits are thus more widespread than ever before. But what are the limitations and challenges of open source tech, and where might it go in the near future?

Bob Lord, senior VP of cognitive applications at IBM, is a believer. “Open-sourcing technology helps innovation occur, and it’s a fundamental basis for creating great technology solutions for the world,” he said. However, the biggest challenge for open source right now is that companies are taking out more than they’re contributing back to the open-source world. Lord pointed out that IBM has a rule about how many lines of code employees take out relative to how many lines they put in.

Another challenge area is open governance; blockchain by its very nature should be transparent and decentralized, with multiple parties making decisions and being held accountable. “We have to embrace open governance at the same time that we’re contributing,” Lord said. He advocated for a hybrid-cloud environment where people can access public and private data and bring it together.

Augmented and Virtual Reality
Augmented and virtual reality aren’t just for fun and games anymore, and they’ll be even less so in the near future. According to Pearly Chen, vice president at HTC, they’ll also go from being two different things to being one and the same. “AR overlays digital information on top of the real world, and VR transports you to a different world,” she said. “In the near future we will not need to delineate between these two activities; AR and VR will come together naturally, and will change everything we do as we know it today.”

For that to happen, we’ll need a more ergonomically friendly device than we have today for interacting with this technology. “Whenever we use tech today, we’re multitasking,” said product designer and futurist Jody Medich. “When you’re using GPS, you’re trying to navigate in the real world and also manage this screen. Constant task-switching is killing our brain’s ability to think.” Augmented and virtual reality, she believes, will allow us to adapt technology to match our brain’s functionality.

This all sounds like a lot of fun for uses like gaming and entertainment, but what about practical applications? “Ultimately what we care about is how this technology will improve lives,” Chen said.

A few ways that could happen? Extended reality will be used to simulate hazardous real-life scenarios, reduce the time and resources needed to bring a product to market, train healthcare professionals (such as surgeons), or provide therapies for patients—not to mention education. “Think about the possibilities for children to learn about history, science, or math in ways they can’t today,” Chen said.

Quantum Computing
If there’s one technology that’s truly baffling, it’s quantum computing. Qubits, entanglement, quantum states—it’s hard to wrap our heads around these concepts, but they hold great promise. Where is the tech right now?

Mandy Birch, head of engineering strategy at Rigetti Computing, thinks quantum development is starting slowly but will accelerate quickly. “We’re at the innovation stage right now, trying to match this capability to useful applications,” she said. “Can we solve problems cheaper, better, and faster than classical computers can do?” She believes quantum’s first breakthrough will happen in two to five years, and that is highest potential is in applications like routing, supply chain, and risk optimization, followed by quantum chemistry (for materials science and medicine) and machine learning.

David Awschalom, director of the Chicago Quantum Exchange and senior scientist at Argonne National Laboratory, believes quantum communication and quantum sensing will become a reality in three to seven years. “We’ll use states of matter to encrypt information in ways that are completely secure,” he said. A quantum voting system, currently being prototyped, is one application.

Who should be driving quantum tech development? The panelists emphasized that no one entity will get very far alone. “Advancing quantum tech will require collaboration not only between business, academia, and government, but between nations,” said Linda Sapochak, division director of materials research at the National Science Foundation. She added that this doesn’t just go for the technology itself—setting up the infrastructure for quantum will be a big challenge as well.

Space
Space has always been the final frontier, and it still is—but it’s not quite as far-removed from our daily lives now as it was when Neil Armstrong walked on the moon in 1969.

The space industry has always been funded by governments and private defense contractors. But in 2009, SpaceX launched its first commercial satellite, and in subsequent years have drastically cut the cost of spaceflight. More importantly, they published their pricing, which brought transparency to a market that hadn’t seen it before.

Entrepreneurs around the world started putting together business plans, and there are now over 400 privately-funded space companies, many with consumer applications.

Chad Anderson, CEO of Space Angels and managing partner of Space Capital, pointed out that the technology floating around in space was, until recently, archaic. “A few NASA engineers saw they had more computing power in their phone than there was in satellites,” he said. “So they thought, ‘why don’t we just fly an iPhone?’” They did—and it worked.

Now companies have networks of satellites monitoring the whole planet, producing a huge amount of data that’s valuable for countless applications like agriculture, shipping, and observation. “A lot of people underestimate space,” Anderson said. “It’s already enabling our modern global marketplace.”

Next up in the space realm, he predicts, are mining and tourism.

Artificial Intelligence and the Future of Work
From the US to Europe to Asia, alarms are sounding about AI taking our jobs. What will be left for humans to do once machines can do everything—and do it better?

These fears may be unfounded, though, and are certainly exaggerated. It’s undeniable that AI and automation are changing the employment landscape (not to mention the way companies do business and the way we live our lives), but if we build these tools the right way, they’ll bring more good than harm, and more productivity than obsolescence.

Accenture’s Julie Sweet emphasized that AI alone is not what’s disrupting business and employment. Rather, it’s what she called the “triple A”: automation, analytics, and artificial intelligence. But even this fear-inducing trifecta of terms doesn’t spell doom, for workers or for companies. Accenture has automated 40,000 jobs—and hasn’t fired anyone in the process. Instead, they’ve trained and up-skilled people. The most important drivers to scale this, Sweet said, are a commitment by companies and government support (such as tax credits).

Imbuing AI with the best of human values will also be critical to its impact on our future. Tracy Frey, Google Cloud AI’s director of strategy, cited the company’s set of seven AI principles. “What’s important is the governance process that’s put in place to support those principles,” she said. “You can’t make macro decisions when you have technology that can be applied in many different ways.”

High Risks, High Stakes
This year, Vaitheeswaran said, 50 percent of the world’s population will have internet access (he added that he’s disappointed that percentage isn’t higher given the proliferation of smartphones). As technology becomes more widely available to people around the world and its influence grows even more, what are the biggest risks we should be monitoring and controlling?

Information integrity—being able to tell what’s real from what’s fake—is a crucial one. “We’re increasingly operating in siloed realities,” said Renee DiResta, director of research at New Knowledge and head of policy at Data for Democracy. “Inadvertent algorithmic amplification on social media elevates certain perspectives—what does that do to us as a society?”

Algorithms have also already been proven to perpetuate the bias of the people who create it—and those people are often wealthy, white, and male. Ensuring that technology doesn’t propagate unfair bias will be crucial to its ability to serve a diverse population, and to keep societies from becoming further polarized and inequitable. The polarization of experience that results from pronounced inequalities within countries, Vaitheeswaran pointed out, can end up undermining democracy.

We’ll also need to walk the line between privacy and utility very carefully. As Dan Wagner, founder of Civis Analytics put it, “We want to ensure privacy as much as possible, but open access to information helps us achieve important social good.” Medicine in the US has been hampered by privacy laws; if, for example, we had more data about biomarkers around cancer, we could provide more accurate predictions and ultimately better healthcare.

But going the Chinese way—a total lack of privacy—is likely not the answer, either. “We have to be very careful about the way we bake rights and freedom into our technology,” said Alex Gladstein, chief strategy officer at Human Rights Foundation.

Technology’s risks are clearly as fraught as its potential is promising. As Gary Shapiro, chief executive of the Consumer Technology Association, put it, “Everything we’ve talked about today is simply a tool, and can be used for good or bad.”

The decisions we’re making now, at every level—from the engineers writing algorithms, to the legislators writing laws, to the teenagers writing clever Instagram captions—will determine where on the spectrum we end up.

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