Tag Archives: interact

#434643 Sensors and Machine Learning Are Giving ...

According to some scientists, humans really do have a sixth sense. There’s nothing supernatural about it: the sense of proprioception tells you about the relative positions of your limbs and the rest of your body. Close your eyes, block out all sound, and you can still use this internal “map” of your external body to locate your muscles and body parts – you have an innate sense of the distances between them, and the perception of how they’re moving, above and beyond your sense of touch.

This sense is invaluable for allowing us to coordinate our movements. In humans, the brain integrates senses including touch, heat, and the tension in muscle spindles to allow us to build up this map.

Replicating this complex sense has posed a great challenge for roboticists. We can imagine simulating the sense of sight with cameras, sound with microphones, or touch with pressure-pads. Robots with chemical sensors could be far more accurate than us in smell and taste, but building in proprioception, the robot’s sense of itself and its body, is far more difficult, and is a large part of why humanoid robots are so tricky to get right.

Simultaneous localization and mapping (SLAM) software allows robots to use their own senses to build up a picture of their surroundings and environment, but they’d need a keen sense of the position of their own bodies to interact with it. If something unexpected happens, or in dark environments where primary senses are not available, robots can struggle to keep track of their own position and orientation. For human-robot interaction, wearable robotics, and delicate applications like surgery, tiny differences can be extremely important.

Piecemeal Solutions
In the case of hard robotics, this is generally solved by using a series of strain and pressure sensors in each joint, which allow the robot to determine how its limbs are positioned. That works fine for rigid robots with a limited number of joints, but for softer, more flexible robots, this information is limited. Roboticists are faced with a dilemma: a vast, complex array of sensors for every degree of freedom in the robot’s movement, or limited skill in proprioception?

New techniques, often involving new arrays of sensory material and machine-learning algorithms to fill in the gaps, are starting to tackle this problem. Take the work of Thomas George Thuruthel and colleagues in Pisa and San Diego, who draw inspiration from the proprioception of humans. In a new paper in Science Robotics, they describe the use of soft sensors distributed through a robotic finger at random. This placement is much like the constant adaptation of sensors in humans and animals, rather than relying on feedback from a limited number of positions.

The sensors allow the soft robot to react to touch and pressure in many different locations, forming a map of itself as it contorts into complicated positions. The machine-learning algorithm serves to interpret the signals from the randomly-distributed sensors: as the finger moves around, it’s observed by a motion capture system. After training the robot’s neural network, it can associate the feedback from the sensors with the position of the finger detected in the motion-capture system, which can then be discarded. The robot observes its own motions to understand the shapes that its soft body can take, and translate them into the language of these soft sensors.

“The advantages of our approach are the ability to predict complex motions and forces that the soft robot experiences (which is difficult with traditional methods) and the fact that it can be applied to multiple types of actuators and sensors,” said Michael Tolley of the University of California San Diego. “Our method also includes redundant sensors, which improves the overall robustness of our predictions.”

The use of machine learning lets the roboticists come up with a reliable model for this complex, non-linear system of motions for the actuators, something difficult to do by directly calculating the expected motion of the soft-bot. It also resembles the human system of proprioception, built on redundant sensors that change and shift in position as we age.

In Search of a Perfect Arm
Another approach to training robots in using their bodies comes from Robert Kwiatkowski and Hod Lipson of Columbia University in New York. In their paper “Task-agnostic self-modeling machines,” also recently published in Science Robotics, they describe a new type of robotic arm.

Robotic arms and hands are getting increasingly dexterous, but training them to grasp a large array of objects and perform many different tasks can be an arduous process. It’s also an extremely valuable skill to get right: Amazon is highly interested in the perfect robot arm. Google hooked together an array of over a dozen robot arms so that they could share information about grasping new objects, in part to cut down on training time.

Individually training a robot arm to perform every individual task takes time and reduces the adaptability of your robot: either you need an ML algorithm with a huge dataset of experiences, or, even worse, you need to hard-code thousands of different motions. Kwiatkowski and Lipson attempt to overcome this by developing a robotic system that has a “strong sense of self”: a model of its own size, shape, and motions.

They do this using deep machine learning. The robot begins with no prior knowledge of its own shape or the underlying physics of its motion. It then repeats a series of a thousand random trajectories, recording the motion of its arm. Kwiatkowski and Lipson compare this to a baby in the first year of life observing the motions of its own hands and limbs, fascinated by picking up and manipulating objects.

Again, once the robot has trained itself to interpret these signals and build up a robust model of its own body, it’s ready for the next stage. Using that deep-learning algorithm, the researchers then ask the robot to design strategies to accomplish simple pick-up and place and handwriting tasks. Rather than laboriously and narrowly training itself for each individual task, limiting its abilities to a very narrow set of circumstances, the robot can now strategize how to use its arm for a much wider range of situations, with no additional task-specific training.

Damage Control
In a further experiment, the researchers replaced part of the arm with a “deformed” component, intended to simulate what might happen if the robot was damaged. The robot can then detect that something’s up and “reconfigure” itself, reconstructing its self-model by going through the training exercises once again; it was then able to perform the same tasks with only a small reduction in accuracy.

Machine learning techniques are opening up the field of robotics in ways we’ve never seen before. Combining them with our understanding of how humans and other animals are able to sense and interact with the world around us is bringing robotics closer and closer to becoming truly flexible and adaptable, and, eventually, omnipresent.

But before they can get out and shape the world, as these studies show, they will need to understand themselves.

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Posted in Human Robots

#434303 Making Superhumans Through Radical ...

Imagine trying to read War and Peace one letter at a time. The thought alone feels excruciating. But in many ways, this painful idea holds parallels to how human-machine interfaces (HMI) force us to interact with and process data today.

Designed back in the 1970s at Xerox PARC and later refined during the 1980s by Apple, today’s HMI was originally conceived during fundamentally different times, and specifically, before people and machines were generating so much data. Fast forward to 2019, when humans are estimated to produce 44 zettabytes of data—equal to two stacks of books from here to Pluto—and we are still using the same HMI from the 1970s.

These dated interfaces are not equipped to handle today’s exponential rise in data, which has been ushered in by the rapid dematerialization of many physical products into computers and software.

Breakthroughs in perceptual and cognitive computing, especially machine learning algorithms, are enabling technology to process vast volumes of data, and in doing so, they are dramatically amplifying our brain’s abilities. Yet even with these powerful technologies that at times make us feel superhuman, the interfaces are still crippled with poor ergonomics.

Many interfaces are still designed around the concept that human interaction with technology is secondary, not instantaneous. This means that any time someone uses technology, they are inevitably multitasking, because they must simultaneously perform a task and operate the technology.

If our aim, however, is to create technology that truly extends and amplifies our mental abilities so that we can offload important tasks, the technology that helps us must not also overwhelm us in the process. We must reimagine interfaces to work in coherence with how our minds function in the world so that our brains and these tools can work together seamlessly.

Embodied Cognition
Most technology is designed to serve either the mind or the body. It is a problematic divide, because our brains use our entire body to process the world around us. Said differently, our minds and bodies do not operate distinctly. Our minds are embodied.

Studies using MRI scans have shown that when a person feels an emotion in their gut, blood actually moves to that area of the body. The body and the mind are linked in this way, sharing information back and forth continuously.

Current technology presents data to the brain differently from how the brain processes data. Our brains, for example, use sensory data to continually encode and decipher patterns within the neocortex. Our brains do not create a linguistic label for each item, which is how the majority of machine learning systems operate, nor do our brains have an image associated with each of these labels.

Our bodies move information through us instantaneously, in a sense “computing” at the speed of thought. What if our technology could do the same?

Using Cognitive Ergonomics to Design Better Interfaces
Well-designed physical tools, as philosopher Martin Heidegger once meditated on while using the metaphor of a hammer, seem to disappear into the “hand.” They are designed to amplify a human ability and not get in the way during the process.

The aim of physical ergonomics is to understand the mechanical movement of the human body and then adapt a physical system to amplify the human output in accordance. By understanding the movement of the body, physical ergonomics enables ergonomically sound physical affordances—or conditions—so that the mechanical movement of the body and the mechanical movement of the machine can work together harmoniously.

Cognitive ergonomics applied to HMI design uses this same idea of amplifying output, but rather than focusing on physical output, the focus is on mental output. By understanding the raw materials the brain uses to comprehend information and form an output, cognitive ergonomics allows technologists and designers to create technological affordances so that the brain can work seamlessly with interfaces and remove the interruption costs of our current devices. In doing so, the technology itself “disappears,” and a person’s interaction with technology becomes fluid and primary.

By leveraging cognitive ergonomics in HMI design, we can create a generation of interfaces that can process and present data the same way humans process real-world information, meaning through fully-sensory interfaces.

Several brain-machine interfaces are already on the path to achieving this. AlterEgo, a wearable device developed by MIT researchers, uses electrodes to detect and understand nonverbal prompts, which enables the device to read the user’s mind and act as an extension of the user’s cognition.

Another notable example is the BrainGate neural device, created by researchers at Stanford University. Just two months ago, a study was released showing that this brain implant system allowed paralyzed patients to navigate an Android tablet with their thoughts alone.

These are two extraordinary examples of what is possible for the future of HMI, but there is still a long way to go to bring cognitive ergonomics front and center in interface design.

Disruptive Innovation Happens When You Step Outside Your Existing Users
Most of today’s interfaces are designed by a narrow population, made up predominantly of white, non-disabled men who are prolific in the use of technology (you may recall The New York Times viral article from 2016, Artificial Intelligence’s White Guy Problem). If you ask this population if there is a problem with today’s HMIs, most will say no, and this is because the technology has been designed to serve them.

This lack of diversity means a limited perspective is being brought to interface design, which is problematic if we want HMI to evolve and work seamlessly with the brain. To use cognitive ergonomics in interface design, we must first gain a more holistic understanding of how people with different abilities understand the world and how they interact with technology.

Underserved groups, such as people with physical disabilities, operate on what Clayton Christensen coined in The Innovator’s Dilemma as the fringe segment of a market. Developing solutions that cater to fringe groups can in fact disrupt the larger market by opening a downward, much larger market.

Learning From Underserved Populations
When technology fails to serve a group of people, that group must adapt the technology to meet their needs.

The workarounds created are often ingenious, specifically because they have not been arrived at by preferences, but out of necessity that has forced disadvantaged users to approach the technology from a very different vantage point.

When a designer or technologist begins learning from this new viewpoint and understanding challenges through a different lens, they can bring new perspectives to design—perspectives that otherwise can go unseen.

Designers and technologists can also learn from people with physical disabilities who interact with the world by leveraging other senses that help them compensate for one they may lack. For example, some blind people use echolocation to detect objects in their environments.

The BrainPort device developed by Wicab is an incredible example of technology leveraging one human sense to serve or compliment another. The BrainPort device captures environmental information with a wearable video camera and converts this data into soft electrical stimulation sequences that are sent to a device on the user’s tongue—the most sensitive touch receptor in the body. The user learns how to interpret the patterns felt on their tongue, and in doing so, become able to “see” with their tongue.

Key to the future of HMI design is learning how different user groups navigate the world through senses beyond sight. To make cognitive ergonomics work, we must understand how to leverage the senses so we’re not always solely relying on our visual or verbal interactions.

Radical Inclusion for the Future of HMI
Bringing radical inclusion into HMI design is about gaining a broader lens on technology design at large, so that technology can serve everyone better.

Interestingly, cognitive ergonomics and radical inclusion go hand in hand. We can’t design our interfaces with cognitive ergonomics without bringing radical inclusion into the picture, and we also will not arrive at radical inclusion in technology so long as cognitive ergonomics are not considered.

This new mindset is the only way to usher in an era of technology design that amplifies the collective human ability to create a more inclusive future for all.

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Posted in Human Robots

#434246 How AR and VR Will Shape the Future of ...

How we work and play is about to transform.

After a prolonged technology “winter”—or what I like to call the ‘deceptive growth’ phase of any exponential technology—the hardware and software that power virtual (VR) and augmented reality (AR) applications are accelerating at an extraordinary rate.

Unprecedented new applications in almost every industry are exploding onto the scene.

Both VR and AR, combined with artificial intelligence, will significantly disrupt the “middleman” and make our lives “auto-magical.” The implications will touch every aspect of our lives, from education and real estate to healthcare and manufacturing.

The Future of Work
How and where we work is already changing, thanks to exponential technologies like artificial intelligence and robotics.

But virtual and augmented reality are taking the future workplace to an entirely new level.

Virtual Reality Case Study: eXp Realty

I recently interviewed Glenn Sanford, who founded eXp Realty in 2008 (imagine: a real estate company on the heels of the housing market collapse) and is the CEO of eXp World Holdings.

Ten years later, eXp Realty has an army of 14,000 agents across all 50 US states, three Canadian provinces, and 400 MLS market areas… all without a single traditional staffed office.

In a bid to transition from 2D interfaces to immersive, 3D work experiences, virtual platform VirBELA built out the company’s office space in VR, unlocking indefinite scaling potential and an extraordinary new precedent.

Real estate agents, managers, and even clients gather in a unique virtual campus, replete with a sports field, library, and lobby. It’s all accessible via head-mounted displays, but most agents join with a computer browser. Surprisingly, the campus-style setup enables the same type of water-cooler conversations I see every day at the XPRIZE headquarters.

With this centralized VR campus, eXp Realty has essentially thrown out overhead costs and entered a lucrative market without the same constraints of brick-and-mortar businesses.

Delocalize with VR, and you can now hire anyone with internet access (right next door or on the other side of the planet), redesign your corporate office every month, throw in an ocean-view office or impromptu conference room for client meetings, and forget about guzzled-up hours in traffic.

As a leader, what happens when you can scalably expand and connect your workforce, not to mention your customer base, without the excess overhead of office space and furniture? Your organization can run faster and farther than your competition.

But beyond the indefinite scalability achieved through digitizing your workplace, VR’s implications extend to the lives of your employees and even the future of urban planning:

Home Prices: As virtual headquarters and office branches take hold of the 21st-century workplace, those who work on campuses like eXp Realty’s won’t need to commute to work. As a result, VR has the potential to dramatically influence real estate prices—after all, if you don’t need to drive to an office, your home search isn’t limited to a specific set of neighborhoods anymore.

Transportation: In major cities like Los Angeles and San Francisco, the implications are tremendous. Analysts have revealed that it’s already cheaper to use ride-sharing services like Uber and Lyft than to own a car in many major cities. And once autonomous “Car-as-a-Service” platforms proliferate, associated transportation costs like parking fees, fuel, and auto repairs will no longer fall on the individual, if not entirely disappear.

Augmented Reality: Annotate and Interact with Your Workplace

As I discussed in a recent Spatial Web blog, not only will Web 3.0 and VR advancements allow us to build out virtual worlds, but we’ll soon be able to digitally map our real-world physical offices or entire commercial high-rises.

Enter a professional world electrified by augmented reality.

Our workplaces are practically littered with information. File cabinets abound with archival data and relevant documents, and company databases continue to grow at a breakneck pace. And, as all of us are increasingly aware, cybersecurity and robust data permission systems remain a major concern for CEOs and national security officials alike.

What if we could link that information to specific locations, people, time frames, and even moving objects?

As data gets added and linked to any given employee’s office, conference room, or security system, we might then access online-merge-offline environments and information through augmented reality.

Imagine showing up at your building’s concierge and your AR glasses automatically check you into the building, authenticating your identity and pulling up any reminders you’ve linked to that specific location.

You stop by a friend’s office, and his smart security system lets you know he’ll arrive in an hour. Need to book a public conference room that’s already been scheduled by another firm’s marketing team? Offer to pay them a fee and, once accepted, a smart transaction will automatically deliver a payment to their company account.

With blockchain-verified digital identities, spatially logged data, and virtually manifest information, business logistics take a fraction of the time, operations grow seamless, and corporate data will be safer than ever.

Or better yet, imagine precise and high-dexterity work environments populated with interactive annotations that guide an artisan, surgeon, or engineer through meticulous handiwork.

Take, for instance, AR service 3D4Medical, which annotates virtual anatomy in midair. And as augmented reality hardware continues to advance, we might envision a future wherein surgeons perform operations on annotated organs and magnified incision sites, or one in which quantum computer engineers can magnify and annotate mechanical parts, speeding up reaction times and vastly improving precision.

The Future of Free Time and Play
In Abundance, I wrote about today’s rapidly demonetizing cost of living. In 2011, almost 75 percent of the average American’s income was spent on housing, transportation, food, personal insurance, health, and entertainment. What the headlines don’t mention: this is a dramatic improvement over the last 50 years. We’re spending less on basic necessities and working fewer hours than previous generations.

Chart depicts the average weekly work hours for full-time production employees in non-agricultural activities. Source: Diamandis.com data
Technology continues to change this, continues to take care of us and do our work for us. One phrase that describes this is “technological socialism,” where it’s technology, not the government, that takes care of us.

Extrapolating from the data, I believe we are heading towards a post-scarcity economy. Perhaps we won’t need to work at all, because we’ll own and operate our own fleet of robots or AI systems that do our work for us.

As living expenses demonetize and workplace automation increases, what will we do with this abundance of time? How will our children and grandchildren connect and find their purpose if they don’t have to work for a living?

As I write this on a Saturday afternoon and watch my two seven-year-old boys immersed in Minecraft, building and exploring worlds of their own creation, I can’t help but imagine that this future is about to enter its disruptive phase.

Exponential technologies are enabling a new wave of highly immersive games, virtual worlds, and online communities. We’ve likely all heard of the Oasis from Ready Player One. But far beyond what we know today as ‘gaming,’ VR is fast becoming a home to immersive storytelling, interactive films, and virtual world creation.

Within the virtual world space, let’s take one of today’s greatest precursors, the aforementioned game Minecraft.

For reference, Minecraft is over eight times the size of planet Earth. And in their free time, my kids would rather build in Minecraft than almost any other activity. I think of it as their primary passion: to create worlds, explore worlds, and be challenged in worlds.

And in the near future, we’re all going to become creators of or participants in virtual worlds, each populated with assets and storylines interoperable with other virtual environments.

But while the technological methods are new, this concept has been alive and well for generations. Whether you got lost in the world of Heidi or Harry Potter, grew up reading comic books or watching television, we’ve all been playing in imaginary worlds, with characters and story arcs populating our minds. That’s the nature of childhood.

In the past, however, your ability to edit was limited, especially if a given story came in some form of 2D media. I couldn’t edit where Tom Sawyer was going or change what Iron Man was doing. But as a slew of new software advancements underlying VR and AR allow us to interact with characters and gain (albeit limited) agency (for now), both new and legacy stories will become subjects of our creation and playgrounds for virtual interaction.

Take VR/AR storytelling startup Fable Studio’s Wolves in the Walls film. Debuting at the 2018 Sundance Film Festival, Fable’s immersive story is adapted from Neil Gaiman’s book and tracks the protagonist, Lucy, whose programming allows her to respond differently based on what her viewers do.

And while Lucy can merely hand virtual cameras to her viewers among other limited tasks, Fable Studio’s founder Edward Saatchi sees this project as just the beginning.

Imagine a virtual character—either in augmented or virtual reality—geared with AI capabilities, that now can not only participate in a fictional storyline but interact and dialogue directly with you in a host of virtual and digitally overlayed environments.

Or imagine engaging with a less-structured environment, like the Star Wars cantina, populated with strangers and friends to provide an entirely novel social media experience.

Already, we’ve seen characters like that of Pokémon brought into the real world with Pokémon Go, populating cities and real spaces with holograms and tasks. And just as augmented reality has the power to turn our physical environments into digital gaming platforms, advanced AR could bring on a new era of in-home entertainment.

Imagine transforming your home into a narrative environment for your kids or overlaying your office interior design with Picasso paintings and gothic architecture. As computer vision rapidly grows capable of identifying objects and mapping virtual overlays atop them, we might also one day be able to project home theaters or live sports within our homes, broadcasting full holograms that allow us to zoom into the action and place ourselves within it.

Increasingly honed and commercialized, augmented and virtual reality are on the cusp of revolutionizing the way we play, tell stories, create worlds, and interact with both fictional characters and each other.

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Posted in Human Robots

#433911 Thanksgiving Food for Thought: The Tech ...

With the Thanksgiving holiday upon us, it’s a great time to reflect on the future of food. Over the last few years, we have seen a dramatic rise in exponential technologies transforming the food industry from seed to plate. Food is important in many ways—too little or too much of it can kill us, and it is often at the heart of family, culture, our daily routines, and our biggest celebrations. The agriculture and food industries are also two of the world’s biggest employers. Let’s take a look to see what is in store for the future.

Robotic Farms
Over the last few years, we have seen a number of new companies emerge in the robotic farming industry. This includes new types of farming equipment used in arable fields, as well as indoor robotic vertical farms. In November 2017, Hands Free Hectare became the first in the world to remotely grow an arable crop. They used autonomous tractors to sow and spray crops, small rovers to take soil samples, drones to monitor crop growth, and an unmanned combine harvester to collect the crops. Since then, they’ve also grown and harvested a field of winter wheat, and have been adding additional technologies and capabilities to their arsenal of robotic farming equipment.

Indoor vertical farming is also rapidly expanding. As Engadget reported in October 2018, a number of startups are now growing crops like leafy greens, tomatoes, flowers, and herbs. These farms can grow food in urban areas, reducing transport, water, and fertilizer costs, and often don’t need pesticides since they are indoors. IronOx, which is using robots to grow plants with navigation technology used by self-driving cars, can grow 30 times more food per acre of land using 90 percent less water than traditional farmers. Vertical farming company Plenty was recently funded by Softbank’s Vision Fund, Jeff Bezos, and others to build 300 vertical farms in China.

These startups are not only succeeding in wealthy countries. Hello Tractor, an “uberized” tractor, has worked with 250,000 smallholder farms in Africa, creating both food security and tech-infused agriculture jobs. The World Food Progam’s Innovation Accelerator (an impact partner of Singularity University) works with hundreds of startups aimed at creating zero hunger. One project is focused on supporting refugees in developing “food computers” in refugee camps—computerized devices that grow food while also adjusting to the conditions around them. As exponential trends drive down the costs of robotics, sensors, software, and energy, we should see robotic farming scaling around the world and becoming the main way farming takes place.

Cultured Meat
Exponential technologies are not only revolutionizing how we grow vegetables and grains, but also how we generate protein and meat. The new cultured meat industry is rapidly expanding, led by startups such as Memphis Meats, Mosa Meats, JUST Meat, Inc. and Finless Foods, and backed by heavyweight investors including DFJ, Bill Gates, Richard Branson, Cargill, and Tyson Foods.

Cultured meat is grown in a bioreactor using cells from an animal, a scaffold, and a culture. The process is humane and, potentially, scientists can make the meat healthier by adding vitamins, removing fat, or customizing it to an individual’s diet and health concerns. Another benefit is that cultured meats, if grown at scale, would dramatically reduce environmental destruction, pollution, and climate change caused by the livestock and fishing industries. Similar to vertical farms, cultured meat is produced using technology and can be grown anywhere, on-demand and in a decentralized way.

Similar to robotic farming equipment, bioreactors will also follow exponential trends, rapidly falling in cost. In fact, the first cultured meat hamburger (created by Singularity University faculty Member Mark Post of Mosa Meats in 2013) cost $350,000 dollars. In 2018, Fast Company reported the cost was now about $11 per burger, and the Israeli startup Future Meat Technologies predicted they will produce beef at about $2 per pound in 2020, which will be competitive with existing prices. For those who have turkey on their mind, one can read about New Harvest’s work (one of the leading think tanks and research centers for the cultured meat and cellular agriculture industry) in funding efforts to generate a nugget of cultured turkey meat.

One outstanding question is whether cultured meat is safe to eat and how it will interact with the overall food supply chain. In the US, regulators like the Food and Drug Administration (FDA) and the US Department of Agriculture (USDA) are working out their roles in this process, with the FDA overseeing the cellular process and the FDA overseeing production and labeling.

Food Processing
Tech companies are also making great headway in streamlining food processing. Norwegian company Tomra Foods was an early leader in using imaging recognition, sensors, artificial intelligence, and analytics to more efficiently sort food based on shape, composition of fat, protein, and moisture, and other food safety and quality indicators. Their technologies have improved food yield by 5-10 percent, which is significant given they own 25 percent of their market.

These advances are also not limited to large food companies. In 2016 Google reported how a small family farm in Japan built a world-class cucumber sorting device using their open-source machine learning tool TensorFlow. SU startup Impact Vision uses hyper-spectral imaging to analyze food quality, which increases revenues and reduces food waste and product recalls from contamination.

These examples point to a question many have on their mind: will we live in a future where a few large companies use advanced technologies to grow the majority of food on the planet, or will the falling costs of these technologies allow family farms, startups, and smaller players to take part in creating a decentralized system? Currently, the future could flow either way, but it is important for smaller companies to take advantage of the most cutting-edge technology in order to stay competitive.

Food Purchasing and Delivery
In the last year, we have also seen a number of new developments in technology improving access to food. Amazon Go is opening grocery stores in Seattle, San Francisco, and Chicago where customers use an app that allows them to pick up their products and pay without going through cashier lines. Sam’s Club is not far behind, with an app that also allows a customer to purchase goods in-store.

The market for food delivery is also growing. In 2017, Morgan Stanley estimated that the online food delivery market from restaurants could grow to $32 billion by 2021, from $12 billion in 2017. Companies like Zume are pioneering robot-powered pizza making and delivery. In addition to using robotics to create affordable high-end gourmet pizzas in their shop, they also have a pizza delivery truck that can assemble and cook pizzas while driving. Their system combines predictive analytics using past customer data to prepare pizzas for certain neighborhoods before the orders even come in. In early November 2018, the Wall Street Journal estimated that Zume is valued at up to $2.25 billion.

Looking Ahead
While each of these developments is promising on its own, it’s also important to note that since all these technologies are in some way digitized and connected to the internet, the various food tech players can collaborate. In theory, self-driving delivery restaurants could share data on what they are selling to their automated farm equipment, facilitating coordination of future crops. There is a tremendous opportunity to improve efficiency, lower costs, and create an abundance of healthy, sustainable food for all.

On the other hand, these technologies are also deeply disruptive. According to the Food and Agricultural Organization of the United Nations, in 2010 about one billion people, or a third of the world’s workforce, worked in the farming and agricultural industries. We need to ensure these farmers are linked to new job opportunities, as well as facilitate collaboration between existing farming companies and technologists so that the industries can continue to grow and lead rather than be displaced.

Just as importantly, each of us might think about how these changes in the food industry might impact our own ways of life and culture. Thanksgiving celebrates community and sharing of food during a time of scarcity. Technology will help create an abundance of food and less need for communities to depend on one another. What are the ways that you will create community, sharing, and culture in this new world?

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Posted in Human Robots

#433892 The Spatial Web Will Map Our 3D ...

The boundaries between digital and physical space are disappearing at a breakneck pace. What was once static and boring is becoming dynamic and magical.

For all of human history, looking at the world through our eyes was the same experience for everyone. Beyond the bounds of an over-active imagination, what you see is the same as what I see.

But all of this is about to change. Over the next two to five years, the world around us is about to light up with layer upon layer of rich, fun, meaningful, engaging, and dynamic data. Data you can see and interact with.

This magical future ahead is called the Spatial Web and will transform every aspect of our lives, from retail and advertising, to work and education, to entertainment and social interaction.

Massive change is underway as a result of a series of converging technologies, from 5G global networks and ubiquitous artificial intelligence, to 30+ billion connected devices (known as the IoT), each of which will generate scores of real-world data every second, everywhere.

The current AI explosion will make everything smart, autonomous, and self-programming. Blockchain and cloud-enabled services will support a secure data layer, putting data back in the hands of users and allowing us to build complex rule-based infrastructure in tomorrow’s virtual worlds.

And with the rise of online-merge-offline (OMO) environments, two-dimensional screens will no longer serve as our exclusive portal to the web. Instead, virtual and augmented reality eyewear will allow us to interface with a digitally-mapped world, richly layered with visual data.

Welcome to the Spatial Web. Over the next few months, I’ll be doing a deep dive into the Spatial Web (a.k.a. Web 3.0), covering what it is, how it works, and its vast implications across industries, from real estate and healthcare to entertainment and the future of work. In this blog, I’ll discuss the what, how, and why of Web 3.0—humanity’s first major foray into our virtual-physical hybrid selves (BTW, this year at Abundance360, we’ll be doing a deep dive into the Spatial Web with the leaders of HTC, Magic Leap, and High-Fidelity).

Let’s dive in.

What is the Spatial Web?
While we humans exist in three dimensions, our web today is flat.

The web was designed for shared information, absorbed through a flat screen. But as proliferating sensors, ubiquitous AI, and interconnected networks blur the lines between our physical and online worlds, we need a spatial web to help us digitally map a three-dimensional world.

To put Web 3.0 in context, let’s take a trip down memory lane. In the late 1980s, the newly-birthed world wide web consisted of static web pages and one-way information—a monumental system of publishing and linking information unlike any unified data system before it. To connect, we had to dial up through unstable modems and struggle through insufferably slow connection speeds.

But emerging from this revolutionary (albeit non-interactive) infodump, Web 2.0 has connected the planet more in one decade than empires did in millennia.

Granting democratized participation through newly interactive sites and applications, today’s web era has turbocharged information-sharing and created ripple effects of scientific discovery, economic growth, and technological progress on an unprecedented scale.

We’ve seen the explosion of social networking sites, wikis, and online collaboration platforms. Consumers have become creators; physically isolated users have been handed a global microphone; and entrepreneurs can now access billions of potential customers.

But if Web 2.0 took the world by storm, the Spatial Web emerging today will leave it in the dust.

While there’s no clear consensus about its definition, the Spatial Web refers to a computing environment that exists in three-dimensional space—a twinning of real and virtual realities—enabled via billions of connected devices and accessed through the interfaces of virtual and augmented reality.

In this way, the Spatial Web will enable us to both build a twin of our physical reality in the virtual realm and bring the digital into our real environments.

It’s the next era of web-like technologies:

Spatial computing technologies, like augmented and virtual reality;
Physical computing technologies, like IoT and robotic sensors;
And decentralized computing: both blockchain—which enables greater security and data authentication—and edge computing, which pushes computing power to where it’s most needed, speeding everything up.

Geared with natural language search, data mining, machine learning, and AI recommendation agents, the Spatial Web is a growing expanse of services and information, navigable with the use of ever-more-sophisticated AI assistants and revolutionary new interfaces.

Where Web 1.0 consisted of static documents and read-only data, Web 2.0 introduced multimedia content, interactive web applications, and social media on two-dimensional screens. But converging technologies are quickly transcending the laptop, and will even disrupt the smartphone in the next decade.

With the rise of wearables, smart glasses, AR / VR interfaces, and the IoT, the Spatial Web will integrate seamlessly into our physical environment, overlaying every conversation, every road, every object, conference room, and classroom with intuitively-presented data and AI-aided interaction.

Think: the Oasis in Ready Player One, where anyone can create digital personas, build and invest in smart assets, do business, complete effortless peer-to-peer transactions, and collect real estate in a virtual world.

Or imagine a virtual replica or “digital twin” of your office, each conference room authenticated on the blockchain, requiring a cryptographic key for entry.

As I’ve discussed with my good friend and “VR guru” Philip Rosedale, I’m absolutely clear that in the not-too-distant future, every physical element of every building in the world is going to be fully digitized, existing as a virtual incarnation or even as N number of these. “Meet me at the top of the Empire State Building?” “Sure, which one?”

This digitization of life means that suddenly every piece of information can become spatial, every environment can be smarter by virtue of AI, and every data point about me and my assets—both virtual and physical—can be reliably stored, secured, enhanced, and monetized.

In essence, the Spatial Web lets us interface with digitally-enhanced versions of our physical environment and build out entirely fictional virtual worlds—capable of running simulations, supporting entire economies, and even birthing new political systems.

But while I’ll get into the weeds of different use cases next week, let’s first concretize.

How Does It Work?
Let’s start with the stack. In the PC days, we had a database accompanied by a program that could ingest that data and present it to us as digestible information on a screen.

Then, in the early days of the web, data migrated to servers. Information was fed through a website, with which you would interface via a browser—whether Mosaic or Mozilla.

And then came the cloud.

Resident at either the edge of the cloud or on your phone, today’s rapidly proliferating apps now allow us to interact with previously read-only data, interfacing through a smartphone. But as Siri and Alexa have brought us verbal interfaces, AI-geared phone cameras can now determine your identity, and sensors are beginning to read our gestures.

And now we’re not only looking at our screens but through them, as the convergence of AI and AR begins to digitally populate our physical worlds.

While Pokémon Go sent millions of mobile game-players on virtual treasure hunts, IKEA is just one of the many companies letting you map virtual furniture within your physical home—simulating everything from cabinets to entire kitchens. No longer the one-sided recipients, we’re beginning to see through sensors, creatively inserting digital content in our everyday environments.

Let’s take a look at how the latest incarnation might work. In this new Web 3.0 stack, my personal AI would act as an intermediary, accessing public or privately-authorized data through the blockchain on my behalf, and then feed it through an interface layer composed of everything from my VR headset, to numerous wearables, to my smart environment (IoT-connected devices or even in-home robots).

But as we attempt to build a smart world with smart infrastructure, smart supply chains and smart everything else, we need a set of basic standards with addresses for people, places, and things. Just like our web today relies on the Internet Protocol (TCP/IP) and other infrastructure, by which your computer is addressed and data packets are transferred, we need infrastructure for the Spatial Web.

And a select group of players is already stepping in to fill this void. Proposing new structural designs for Web 3.0, some are attempting to evolve today’s web model from text-based web pages in 2D to three-dimensional AR and VR web experiences located in both digitally-mapped physical worlds and newly-created virtual ones.

With a spatial programming language analogous to HTML, imagine building a linkable address for any physical or virtual space, granting it a format that then makes it interchangeable and interoperable with all other spaces.

But it doesn’t stop there.

As soon as we populate a virtual room with content, we then need to encode who sees it, who can buy it, who can move it…

And the Spatial Web’s eventual governing system (for posting content on a centralized grid) would allow us to address everything from the room you’re sitting in, to the chair on the other side of the table, to the building across the street.

Just as we have a DNS for the web and the purchasing of web domains, once we give addresses to spaces (akin to granting URLs), we then have the ability to identify and visit addressable locations, physical objects, individuals, or pieces of digital content in cyberspace.

And these not only apply to virtual worlds, but to the real world itself. As new mapping technologies emerge, we can now map rooms, objects, and large-scale environments into virtual space with increasing accuracy.

We might then dictate who gets to move your coffee mug in a virtual conference room, or when a team gets to use the room itself. Rules and permissions would be set in the grid, decentralized governance systems, or in the application layer.

Taken one step further, imagine then monetizing smart spaces and smart assets. If you have booked the virtual conference room, perhaps you’ll let me pay you 0.25 BTC to let me use it instead?

But given the Spatial Web’s enormous technological complexity, what’s allowing it to emerge now?

Why Is It Happening Now?
While countless entrepreneurs have already started harnessing blockchain technologies to build decentralized apps (or dApps), two major developments are allowing today’s birth of Web 3.0:

High-resolution wireless VR/AR headsets are finally catapulting virtual and augmented reality out of a prolonged winter.

The International Data Corporation (IDC) predicts the VR and AR headset market will reach 65.9 million units by 2022. Already in the next 18 months, 2 billion devices will be enabled with AR. And tech giants across the board have long begun investing heavy sums.

In early 2019, HTC is releasing the VIVE Focus, a wireless self-contained VR headset. At the same time, Facebook is charging ahead with its Project Santa Cruz—the Oculus division’s next-generation standalone, wireless VR headset. And Magic Leap has finally rolled out its long-awaited Magic Leap One mixed reality headset.

Mass deployment of 5G will drive 10 to 100-gigabit connection speeds in the next 6 years, matching hardware progress with the needed speed to create virtual worlds.

We’ve already seen tremendous leaps in display technology. But as connectivity speeds converge with accelerating GPUs, we’ll start to experience seamless VR and AR interfaces with ever-expanding virtual worlds.

And with such democratizing speeds, every user will be able to develop in VR.

But accompanying these two catalysts is also an important shift towards the decentralized web and a demand for user-controlled data.

Converging technologies, from immutable ledgers and blockchain to machine learning, are now enabling the more direct, decentralized use of web applications and creation of user content. With no central point of control, middlemen are removed from the equation and anyone can create an address, independently interacting with the network.

Enabled by a permission-less blockchain, any user—regardless of birthplace, gender, ethnicity, wealth, or citizenship—would thus be able to establish digital assets and transfer them seamlessly, granting us a more democratized Internet.

And with data stored on distributed nodes, this also means no single point of failure. One could have multiple backups, accessible only with digital authorization, leaving users immune to any single server failure.

Implications Abound–What’s Next…
With a newly-built stack and an interface built from numerous converging technologies, the Spatial Web will transform every facet of our everyday lives—from the way we organize and access our data, to our social and business interactions, to the way we train employees and educate our children.

We’re about to start spending more time in the virtual world than ever before. Beyond entertainment or gameplay, our livelihoods, work, and even personal decisions are already becoming mediated by a web electrified with AI and newly-emerging interfaces.

In our next blog on the Spatial Web, I’ll do a deep dive into the myriad industry implications of Web 3.0, offering tangible use cases across sectors.

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