Tag Archives: might

#435023 Inflatable Robot Astronauts and How to ...

Posted on May 1, 2019 by Android

The typical cultural image of a robot—as a steel, chrome, humanoid bucket of bolts—is often far from the reality of cutting-edge robotics research. There are difficulties, both social and technological, in realizing the image of a robot from science fiction—let alone one that can actually help around the house. Often, it’s simply the case that great expense in producing a humanoid robot that can perform dozens of tasks quite badly is less appropriate than producing some other design that’s optimized to a specific situation.

A team of scientists from Brigham Young University has received funding from NASA to investigate an inflatable robot called, improbably, King Louie. The robot was developed by Pneubotics, who have a long track record in the world of soft robotics.

In space, weight is at a premium. The world watched in awe and amusement when Commander Chris Hadfield sang “Space Oddity” from the International Space Station—but launching that guitar into space likely cost around $100,000. A good price for launching payload into outer space is on the order of $10,000 per pound ($22,000/kg).

For that price, it would cost a cool $1.7 million to launch Boston Dynamics’ famous ATLAS robot to the International Space Station, and its bulk would be inconvenient in the cramped living quarters available. By contrast, an inflatable robot like King Louie is substantially lighter and can simply be deflated and folded away when not in use. The robot can be manufactured from cheap, lightweight, and flexible materials, and minor damage is easy to repair.

Inflatable Robots Under Pressure
The concept of inflatable robots is not new: indeed, earlier prototypes of King Louie were exhibited back in 2013 at Google I/O’s After Hours, flailing away at each other in a boxing ring. Sparks might fly in fights between traditional robots, but the aim here was to demonstrate that the robots are passively safe: the soft, inflatable figures won’t accidentally smash delicate items when moving around.

Health and safety regulations form part of the reason why robots don’t work alongside humans more often, but soft robots would be far safer to use in healthcare or around children (whose first instinct, according to BYU’s promotional video, is either to hug or punch King Louie.) It’s also much harder to have nightmarish fantasies about robotic domination with these friendlier softbots: Terminator would’ve been a much shorter franchise if Skynet’s droids were inflatable.

Robotic exoskeletons are increasingly used for physical rehabilitation therapies, as well as for industrial purposes. As countries like Japan seek to care for their aging populations with robots and alleviate the burden on nurses, who suffer from some of the highest rates of back injuries of any profession, soft robots will become increasingly attractive for use in healthcare.

Precision and Proprioception
The main issue is one of control. Rigid, metallic robots may be more expensive and more dangerous, but the simple fact of their rigidity makes it easier to map out and control the precise motions of each of the robot’s limbs, digits, and actuators. Individual motors attached to these rigid robots can allow for a great many degrees of freedom—individual directions in which parts of the robot can move—and precision control.

For example, ATLAS has 28 degrees of freedom, while Shadow’s dexterous robot hand alone has 20. This is much harder to do with an inflatable robot, for precisely the same reasons that make it safer. Without hard and rigid bones, other methods of control must be used.

In the case of King Louie, the robot is made up of many expandable air chambers. An air-compressor changes the pressure levels in these air chambers, allowing them to expand and contract. This harks back to some of the earliest pneumatic automata. Pairs of chambers act antagonistically, like muscles, such that when one chamber “tenses,” another relaxes—allowing King Louie to have, for example, four degrees of freedom in each of its arms.

The robot is also surprisingly strong. Professor Killpack, who works at BYU on the project, estimates that its payload is comparable to other humanoid robots on the market, like Rethink Robotics’ Baxter (RIP).

Proprioception, that sixth sense that allows us to map out and control our own bodies and muscles in fine detail, is being enhanced for a wider range of soft, flexible robots with the use of machine learning algorithms connected to input from a whole host of sensors on the robot’s body.

Part of the reason this is so complicated with soft, flexible robots is that the shape and “map” of the robot’s body can change; that’s the whole point. But this means that every time King Louie is inflated, its body is a slightly different shape; when it becomes deformed, for example due to picking up objects, the shape changes again, and the complex ways in which the fabric can twist and bend are far more difficult to model and sense than the behavior of the rigid metal of King Louie’s hard counterparts. When you’re looking for precision, seemingly-small changes can be the difference between successfully holding an object or dropping it.

Learning to Move
Researchers at BYU are therefore spending a great deal of time on how to control the soft-bot enough to make it comparably useful. One method involves the commercial tracking technology used in the Vive VR system: by moving the game controller, which provides a constant feedback to the robot’s arm, you can control its position. Since the tracking software provides an estimate of the robot’s joint angles and continues to provide feedback until the arm is correctly aligned, this type of feedback method is likely to work regardless of small changes to the robot’s shape.

The other technologies the researchers are looking into for their softbot include arrays of flexible, tactile sensors to place on the softbot’s skin, and minimizing the complex cross-talk between these arrays to get coherent information about the robot’s environment. As with some of the new proprioception research, the project is looking into neural networks as a means of modeling the complicated dynamics—the motion and response to forces—of the softbot. This method relies on large amounts of observational data, mapping how the robot is inflated and how it moves, rather than explicitly understanding and solving the equations that govern its motion—which hopefully means the methods can work even as the robot changes.

There’s still a long way to go before soft and inflatable robots can be controlled sufficiently well to perform all the tasks they might be used for. Ultimately, no one robotic design is likely to be perfect for any situation.

Nevertheless, research like this gives us hope that one day, inflatable robots could be useful tools, or even companions, at which point the advertising slogans write themselves: Don’t let them down, and they won’t let you down!

Image Credit: Brigham Young University. Continue reading →

Posted in Human Robots

#434827 AI and Robotics Are Transforming ...

Posted on April 12, 2019 by Android

During the past 50 years, the frequency of recorded natural disasters has surged nearly five-fold.

In this blog, I’ll be exploring how converging exponential technologies (AI, robotics, drones, sensors, networks) are transforming the future of disaster relief—how we can prevent them in the first place and get help to victims during that first golden hour wherein immediate relief can save lives.

Here are the three areas of greatest impact:

AI, predictive mapping, and the power of the crowd
Next-gen robotics and swarm solutions
Aerial drones and immediate aid supply

Let’s dive in!

Artificial Intelligence and Predictive Mapping
When it comes to immediate and high-precision emergency response, data is gold.

Already, the meteoric rise of space-based networks, stratosphere-hovering balloons, and 5G telecommunications infrastructure is in the process of connecting every last individual on the planet.

Aside from democratizing the world’s information, however, this upsurge in connectivity will soon grant anyone the ability to broadcast detailed geo-tagged data, particularly those most vulnerable to natural disasters.

Armed with the power of data broadcasting and the force of the crowd, disaster victims now play a vital role in emergency response, turning a historically one-way blind rescue operation into a two-way dialogue between connected crowds and smart response systems.

With a skyrocketing abundance of data, however, comes a new paradigm: one in which we no longer face a scarcity of answers. Instead, it will be the quality of our questions that matters most.

This is where AI comes in: our mining mechanism.

In the case of emergency response, what if we could strategically map an almost endless amount of incoming data points? Or predict the dynamics of a flood and identify a tsunami’s most vulnerable targets before it even strikes? Or even amplify critical signals to trigger automatic aid by surveillance drones and immediately alert crowdsourced volunteers?

Already, a number of key players are leveraging AI, crowdsourced intelligence, and cutting-edge visualizations to optimize crisis response and multiply relief speeds.

Take One Concern, for instance. Born out of Stanford under the mentorship of leading AI expert Andrew Ng, One Concern leverages AI through analytical disaster assessment and calculated damage estimates.

Partnering with the cities of Los Angeles, San Francisco, and numerous cities in San Mateo County, the platform assigns verified, unique ‘digital fingerprints’ to every element in a city. Building robust models of each system, One Concern’s AI platform can then monitor site-specific impacts of not only climate change but each individual natural disaster, from sweeping thermal shifts to seismic movement.

This data, combined with that of city infrastructure and former disasters, are then used to predict future damage under a range of disaster scenarios, informing prevention methods and structures in need of reinforcement.

Within just four years, One Concern can now make precise predictions with an 85 percent accuracy rate in under 15 minutes.

And as IoT-connected devices and intelligent hardware continue to boom, a blooming trillion-sensor economy will only serve to amplify AI’s predictive capacity, offering us immediate, preventive strategies long before disaster strikes.

Beyond natural disasters, however, crowdsourced intelligence, predictive crisis mapping, and AI-powered responses are just as formidable a triage in humanitarian disasters.

One extraordinary story is that of Ushahidi. When violence broke out after the 2007 Kenyan elections, one local blogger proposed a simple yet powerful question to the web: “Any techies out there willing to do a mashup of where the violence and destruction is occurring and put it on a map?”

Within days, four ‘techies’ heeded the call, building a platform that crowdsourced first-hand reports via SMS, mined the web for answers, and—with over 40,000 verified reports—sent alerts back to locals on the ground and viewers across the world.

Today, Ushahidi has been used in over 150 countries, reaching a total of 20 million people across 100,000+ deployments. Now an open-source crisis-mapping software, its V3 (or “Ushahidi in the Cloud”) is accessible to anyone, mining millions of Tweets, hundreds of thousands of news articles, and geo-tagged, time-stamped data from countless sources.

Aggregating one of the longest-running crisis maps to date, Ushahidi’s Syria Tracker has proved invaluable in the crowdsourcing of witness reports. Providing real-time geographic visualizations of all verified data, Syria Tracker has enabled civilians to report everything from missing people and relief supply needs to civilian casualties and disease outbreaks— all while evading the government’s cell network, keeping identities private, and verifying reports prior to publication.

As mobile connectivity and abundant sensors converge with AI-mined crowd intelligence, real-time awareness will only multiply in speed and scale.

Imagining the Future….

Within the next 10 years, spatial web technology might even allow us to tap into mesh networks.

As I’ve explored in a previous blog on the implications of the spatial web, while traditional networks rely on a limited set of wired access points (or wireless hotspots), a wireless mesh network can connect entire cities via hundreds of dispersed nodes that communicate with each other and share a network connection non-hierarchically.

In short, this means that individual mobile users can together establish a local mesh network using nothing but the computing power in their own devices.

Take this a step further, and a local population of strangers could collectively broadcast countless 360-degree feeds across a local mesh network.

Imagine a scenario in which armed attacks break out across disjointed urban districts, each cluster of eye witnesses and at-risk civilians broadcasting an aggregate of 360-degree videos, all fed through photogrammetry AIs that build out a live hologram in real time, giving family members and first responders complete information.

Or take a coastal community in the throes of torrential rainfall and failing infrastructure. Now empowered by a collective live feed, verification of data reports takes a matter of seconds, and richly-layered data informs first responders and AI platforms with unbelievable accuracy and specificity of relief needs.

By linking all the right technological pieces, we might even see the rise of automated drone deliveries. Imagine: crowdsourced intelligence is first cross-referenced with sensor data and verified algorithmically. AI is then leveraged to determine the specific needs and degree of urgency at ultra-precise coordinates. Within minutes, once approved by personnel, swarm robots rush to collect the requisite supplies, equipping size-appropriate drones with the right aid for rapid-fire delivery.

This brings us to a second critical convergence: robots and drones.

While cutting-edge drone technology revolutionizes the way we deliver aid, new breakthroughs in AI-geared robotics are paving the way for superhuman emergency responses in some of today’s most dangerous environments.

Let’s explore a few of the most disruptive examples to reach the testing phase.

First up….

Autonomous Robots and Swarm Solutions
As hardware advancements converge with exploding AI capabilities, disaster relief robots are graduating from assistance roles to fully autonomous responders at a breakneck pace.

Born out of MIT’s Biomimetic Robotics Lab, the Cheetah III is but one of many robots that may form our first line of defense in everything from earthquake search-and-rescue missions to high-risk ops in dangerous radiation zones.

Now capable of running at 6.4 meters per second, Cheetah III can even leap up to a height of 60 centimeters, autonomously determining how to avoid obstacles and jump over hurdles as they arise.

Initially designed to perform spectral inspection tasks in hazardous settings (think: nuclear plants or chemical factories), the Cheetah’s various iterations have focused on increasing its payload capacity, range of motion, and even a gripping function with enhanced dexterity.

Cheetah III and future versions are aimed at saving lives in almost any environment.

And the Cheetah III is not alone. Just this February, Tokyo’s Electric Power Company (TEPCO) has put one of its own robots to the test. For the first time since Japan’s devastating 2011 tsunami, which led to three nuclear meltdowns in the nation’s Fukushima nuclear power plant, a robot has successfully examined the reactor’s fuel.

Broadcasting the process with its built-in camera, the robot was able to retrieve small chunks of radioactive fuel at five of the six test sites, offering tremendous promise for long-term plans to clean up the still-deadly interior.

Also out of Japan, Mitsubishi Heavy Industries (MHi) is even using robots to fight fires with full autonomy. In a remarkable new feat, MHi’s Water Cannon Bot can now put out blazes in difficult-to-access or highly dangerous fire sites.

Delivering foam or water at 4,000 liters per minute and 1 megapascal (MPa) of pressure, the Cannon Bot and its accompanying Hose Extension Bot even form part of a greater AI-geared system to conduct reconnaissance and surveillance on larger transport vehicles.

As wildfires grow ever more untameable, high-volume production of such bots could prove a true lifesaver. Paired with predictive AI forest fire mapping and autonomous hauling vehicles, not only will solutions like MHi’s Cannon Bot save numerous lives, but avoid population displacement and paralyzing damage to our natural environment before disaster has the chance to spread.

But even in cases where emergency shelter is needed, groundbreaking (literally) robotics solutions are fast to the rescue.

After multiple iterations by Fastbrick Robotics, the Hadrian X end-to-end bricklaying robot can now autonomously build a fully livable, 180-square-meter home in under three days. Using a laser-guided robotic attachment, the all-in-one brick-loaded truck simply drives to a construction site and directs blocks through its robotic arm in accordance with a 3D model.

Meeting verified building standards, Hadrian and similar solutions hold massive promise in the long-term, deployable across post-conflict refugee sites and regions recovering from natural catastrophes.

But what if we need to build emergency shelters from local soil at hand? Marking an extraordinary convergence between robotics and 3D printing, the Institute for Advanced Architecture of Catalonia (IAAC) is already working on a solution.

In a major feat for low-cost construction in remote zones, IAAC has found a way to convert almost any soil into a building material with three times the tensile strength of industrial clay. Offering myriad benefits, including natural insulation, low GHG emissions, fire protection, air circulation, and thermal mediation, IAAC’s new 3D printed native soil can build houses on-site for as little as $1,000.

But while cutting-edge robotics unlock extraordinary new frontiers for low-cost, large-scale emergency construction, novel hardware and computing breakthroughs are also enabling robotic scale at the other extreme of the spectrum.

Again, inspired by biological phenomena, robotics specialists across the US have begun to pilot tiny robotic prototypes for locating trapped individuals and assessing infrastructural damage.

Take RoboBees, tiny Harvard-developed bots that use electrostatic adhesion to ‘perch’ on walls and even ceilings, evaluating structural damage in the aftermath of an earthquake.

Or Carnegie Mellon’s prototyped Snakebot, capable of navigating through entry points that would otherwise be completely inaccessible to human responders. Driven by AI, the Snakebot can maneuver through even the most densely-packed rubble to locate survivors, using cameras and microphones for communication.

But when it comes to fast-paced reconnaissance in inaccessible regions, miniature robot swarms have good company.

Next-Generation Drones for Instantaneous Relief Supplies
Particularly in the case of wildfires and conflict zones, autonomous drone technology is fundamentally revolutionizing the way we identify survivors in need and automate relief supply.

Not only are drones enabling high-resolution imagery for real-time mapping and damage assessment, but preliminary research shows that UAVs far outpace ground-based rescue teams in locating isolated survivors.

As presented by a team of electrical engineers from the University of Science and Technology of China, drones could even build out a mobile wireless broadband network in record time using a “drone-assisted multi-hop device-to-device” program.

And as shown during Houston’s Hurricane Harvey, drones can provide scores of predictive intel on everything from future flooding to damage estimates.

Among multiple others, a team led by Texas A&M computer science professor and director of the university’s Center for Robot-Assisted Search and Rescue Dr. Robin Murphy flew a total of 119 drone missions over the city, from small-scale quadcopters to military-grade unmanned planes. Not only were these critical for monitoring levee infrastructure, but also for identifying those left behind by human rescue teams.

But beyond surveillance, UAVs have begun to provide lifesaving supplies across some of the most remote regions of the globe. One of the most inspiring examples to date is Zipline.

Created in 2014, Zipline has completed 12,352 life-saving drone deliveries to date. While drones are designed, tested, and assembled in California, Zipline primarily operates in Rwanda and Tanzania, hiring local operators and providing over 11 million people with instant access to medical supplies.

Providing everything from vaccines and HIV medications to blood and IV tubes, Zipline’s drones far outpace ground-based supply transport, in many instances providing life-critical blood cells, plasma, and platelets in under an hour.

But drone technology is even beginning to transcend the limited scale of medical supplies and food.

Now developing its drones under contracts with DARPA and the US Marine Corps, Logistic Gliders, Inc. has built autonomously-navigating drones capable of carrying 1,800 pounds of cargo over unprecedented long distances.

Built from plywood, Logistic’s gliders are projected to cost as little as a few hundred dollars each, making them perfect candidates for high-volume remote aid deliveries, whether navigated by a pilot or self-flown in accordance with real-time disaster zone mapping.

As hardware continues to advance, autonomous drone technology coupled with real-time mapping algorithms pose no end of abundant opportunities for aid supply, disaster monitoring, and richly layered intel previously unimaginable for humanitarian relief.

Concluding Thoughts
Perhaps one of the most consequential and impactful applications of converging technologies is their transformation of disaster relief methods.

While AI-driven intel platforms crowdsource firsthand experiential data from those on the ground, mobile connectivity and drone-supplied networks are granting newfound narrative power to those most in need.

And as a wave of new hardware advancements gives rise to robotic responders, swarm technology, and aerial drones, we are fast approaching an age of instantaneous and efficiently-distributed responses in the midst of conflict and natural catastrophes alike.

Empowered by these new tools, what might we create when everyone on the planet has the same access to relief supplies and immediate resources? In a new age of prevention and fast recovery, what futures can you envision?

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Image Credit: Arcansel / Shutterstock.com Continue reading →

Posted in Human Robots

#434818 Watch These Robots Do Tasks You Thought ...

Posted on April 9, 2019 by Android

Robots have been masters of manufacturing at speed and precision for decades, but give them a seemingly simple task like stacking shelves, and they quickly get stuck. That’s changing, though, as engineers build systems that can take on the deceptively tricky tasks most humans can do with their eyes closed.

Boston Dynamics is famous for dramatic reveals of robots performing mind-blowing feats that also leave you scratching your head as to what the market is—think the bipedal Atlas doing backflips or Spot the galloping robot dog.

Last week, the company released a video of a robot called Handle that looks like an ostrich on wheels carrying out the seemingly mundane task of stacking boxes in a warehouse.

It might seem like a step backward, but this is exactly the kind of practical task robots have long struggled with. While the speed and precision of industrial robots has seen them take over many functions in modern factories, they’re generally limited to highly prescribed tasks carried out in meticulously-controlled environments.

That’s because despite their mechanical sophistication, most are still surprisingly dumb. They can carry out precision welding on a car or rapidly assemble electronics, but only by rigidly following a prescribed set of motions. Moving cardboard boxes around a warehouse might seem simple to a human, but it actually involves a variety of tasks machines still find pretty difficult—perceiving your surroundings, navigating, and interacting with objects in a dynamic environment.

But the release of this video suggests Boston Dynamics thinks these kinds of applications are close to prime time. Last week the company doubled down by announcing the acquisition of start-up Kinema Systems, which builds computer vision systems for robots working in warehouses.

It’s not the only company making strides in this area. On the same day the video went live, Google unveiled a robot arm called TossingBot that can pick random objects from a box and quickly toss them into another container beyond its reach, which could prove very useful for sorting items in a warehouse. The machine can train on new objects in just an hour or two, and can pick and toss up to 500 items an hour with better accuracy than any of the humans who tried the task.

And an apple-picking robot built by Abundant Robotics is currently on New Zealand farms navigating between rows of apple trees using LIDAR and computer vision to single out ripe apples before using a vacuum tube to suck them off the tree.

In most cases, advances in machine learning and computer vision brought about by the recent AI boom are the keys to these rapidly improving capabilities. Robots have historically had to be painstakingly programmed by humans to solve each new task, but deep learning is making it possible for them to quickly train themselves on a variety of perception, navigation, and dexterity tasks.

It’s not been simple, though, and the application of deep learning in robotics has lagged behind other areas. A major limitation is that the process typically requires huge amounts of training data. That’s fine when you’re dealing with image classification, but when that data needs to be generated by real-world robots it can make the approach impractical. Simulations offer the possibility to run this training faster than real time, but it’s proved difficult to translate policies learned in virtual environments into the real world.

Recent years have seen significant progress on these fronts, though, and the increasing integration of modern machine learning with robotics. In October, OpenAI imbued a robotic hand with human-level dexterity by training an algorithm in a simulation using reinforcement learning before transferring it to the real-world device. The key to ensuring the translation went smoothly was injecting random noise into the simulation to mimic some of the unpredictability of the real world.

And just a couple of weeks ago, MIT researchers demonstrated a new technique that let a robot arm learn to manipulate new objects with far less training data than is usually required. By getting the algorithm to focus on a few key points on the object necessary for picking it up, the system could learn to pick up a previously unseen object after seeing only a few dozen examples (rather than the hundreds or thousands typically required).

How quickly these innovations will trickle down to practical applications remains to be seen, but a number of startups as well as logistics behemoth Amazon are developing robots designed to flexibly pick and place the wide variety of items found in your average warehouse.

Whether the economics of using robots to replace humans at these kinds of menial tasks makes sense yet is still unclear. The collapse of collaborative robotics pioneer Rethink Robotics last year suggests there are still plenty of challenges.

But at the same time, the number of robotic warehouses is expected to leap from 4,000 today to 50,000 by 2025. It may not be long until robots are muscling in on tasks we’ve long assumed only humans could do.

Image Credit: Visual Generation / Shutterstock.com Continue reading →

Posted in Human Robots

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

Posted on March 30, 2019 by Android

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

#434772 Traditional Higher Education Is Losing ...

Posted on March 22, 2019 by Android

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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