Tag Archives: applications

#433954 The Next Great Leap Forward? Combining ...

The Internet of Things is a popular vision of objects with internet connections sending information back and forth to make our lives easier and more comfortable. It’s emerging in our homes, through everything from voice-controlled speakers to smart temperature sensors. To improve our fitness, smart watches and Fitbits are telling online apps how much we’re moving around. And across entire cities, interconnected devices are doing everything from increasing the efficiency of transport to flood detection.

In parallel, robots are steadily moving outside the confines of factory lines. They’re starting to appear as guides in shopping malls and cruise ships, for instance. As prices fall and the artificial intelligence (AI) and mechanical technology continues to improve, we will get more and more used to them making independent decisions in our homes, streets and workplaces.

Here lies a major opportunity. Robots become considerably more capable with internet connections. There is a growing view that the next evolution of the Internet of Things will be to incorporate them into the network, opening up thrilling possibilities along the way.

Home Improvements
Even simple robots become useful when connected to the internet—getting updates about their environment from sensors, say, or learning about their users’ whereabouts and the status of appliances in the vicinity. This lets them lend their bodies, eyes, and ears to give an otherwise impersonal smart environment a user-friendly persona. This can be particularly helpful for people at home who are older or have disabilities.

We recently unveiled a futuristic apartment at Heriot-Watt University to work on such possibilities. One of a few such test sites around the EU, our whole focus is around people with special needs—and how robots can help them by interacting with connected devices in a smart home.

Suppose a doorbell rings that has smart video features. A robot could find the person in the home by accessing their location via sensors, then tell them who is at the door and why. Or it could help make video calls to family members or a professional carer—including allowing them to make virtual visits by acting as a telepresence platform.

Equally, it could offer protection. It could inform them the oven has been left on, for example—phones or tablets are less reliable for such tasks because they can be misplaced or not heard.

Similarly, the robot could raise the alarm if its user appears to be in difficulty.Of course, voice-assistant devices like Alexa or Google Home can offer some of the same services. But robots are far better at moving, sensing and interacting with their environment. They can also engage their users by pointing at objects or acting more naturally, using gestures or facial expressions. These “social abilities” create bonds which are crucially important for making users more accepting of the support and making it more effective.

To help incentivize the various EU test sites, our apartment also hosts the likes of the European Robotic League Service Robot Competition—a sort of Champions League for robots geared to special needs in the home. This brought academics from around Europe to our laboratory for the first time in January this year. Their robots were tested in tasks like welcoming visitors to the home, turning the oven off, and fetching objects for their users; and a German team from Koblenz University won with a robot called Lisa.

Robots Offshore
There are comparable opportunities in the business world. Oil and gas companies are looking at the Internet of Things, for example; experimenting with wireless sensors to collect information such as temperature, pressure, and corrosion levels to detect and possibly predict faults in their offshore equipment.

In the future, robots could be alerted to problem areas by sensors to go and check the integrity of pipes and wells, and to make sure they are operating as efficiently and safely as possible. Or they could place sensors in parts of offshore equipment that are hard to reach, or help to calibrate them or replace their batteries.

The likes of the ORCA Hub, a £36m project led by the Edinburgh Centre for Robotics, bringing together leading experts and over 30 industry partners, is developing such systems. The aim is to reduce the costs and the risks of humans working in remote hazardous locations.

ORCA tests a drone robot. ORCA
Working underwater is particularly challenging, since radio waves don’t move well under the sea. Underwater autonomous vehicles and sensors usually communicate using acoustic waves, which are many times slower (1,500 meters a second vs. 300m meters a second for radio waves). Acoustic communication devices are also much more expensive than those used above the water.

This academic project is developing a new generation of low-cost acoustic communication devices, and trying to make underwater sensor networks more efficient. It should help sensors and underwater autonomous vehicles to do more together in future—repair and maintenance work similar to what is already possible above the water, plus other benefits such as helping vehicles to communicate with one another over longer distances and tracking their location.

Beyond oil and gas, there is similar potential in sector after sector. There are equivalents in nuclear power, for instance, and in cleaning and maintaining the likes of bridges and buildings. My colleagues and I are also looking at possibilities in areas such as farming, manufacturing, logistics, and waste.

First, however, the research sectors around the Internet of Things and robotics need to properly share their knowledge and expertise. They are often isolated from one another in different academic fields. There needs to be more effort to create a joint community, such as the dedicated workshops for such collaboration that we organized at the European Robotics Forum and the IoT Week in 2017.

To the same end, industry and universities need to look at setting up joint research projects. It is particularly important to address safety and security issues—hackers taking control of a robot and using it to spy or cause damage, for example. Such issues could make customers wary and ruin a market opportunity.

We also need systems that can work together, rather than in isolated applications. That way, new and more useful services can be quickly and effectively introduced with no disruption to existing ones. If we can solve such problems and unite robotics and the Internet of Things, it genuinely has the potential to change the world.

Mauro Dragone, Assistant Professor, Cognitive Robotics, Multiagent systems, Internet of Things, Heriot-Watt University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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#433950 How the Spatial Web Will Transform Every ...

What is the future of work? Is our future one of ‘technological socialism’ (where technology is taking care of our needs)? Or is our future workplace completely virtualized, whereby we hang out at home in our PJs while walking about our virtual corporate headquarters?

This blog will look at the future of work during the age of Web 3.0… Examining scenarios in which AI, VR, and the spatial web converge to transform every element of our careers, from training to execution to free time.

Three weeks ago, I explored the vast implications of Web 3.0 on news, media, smart advertising, and personalized retail. And to offer a quick recap on what the Spatial Web is and how it works, let’s cover some brief history.

A Quick Recap on Web 3.0
While Web 1.0 consisted of static documents and read-only data (static web pages), Web 2.0 introduced multimedia content, interactive web applications, and participatory social media, all of these mediated by two-dimensional screens.

But over the next two to five years, the convergence of 5G, artificial intelligence, VR/AR, and a trillion-sensor economy will enable us to both map our physical world into virtual space and superimpose a digital data layer onto our physical environments.

Suddenly, all our information will be manipulated, stored, understood, and experienced in spatial ways.

In this third installment of the Web 3.0 series, I’ll be discussing the Spatial Web’s vast implications for:

Professional Training
Delocalized Business and the Virtual Workplace
Smart Permissions and Data Security

Let’s dive in.

Virtual Training, Real-World Results
Virtual and augmented reality have already begun disrupting the professional training market.

Leading the charge, Walmart has already implemented VR across 200 Academy training centers, running over 45 modules and simulating everything from unusual customer requests to a Black Friday shopping rush.

In September 2018, Walmart committed to a 17,000-headset order of the Oculus Go to equip every US Supercenter, neighborhood market, and discount store with VR-based employee training.

In the engineering world, Bell Helicopter is using VR to massively expedite development and testing of its latest aircraft, FCX-001. Partnering with Sector 5 Digital and HTC VIVE, Bell found it could concentrate a typical six-year aircraft design process into the course of six months, turning physical mock-ups into CAD-designed virtual replicas.

But beyond the design process itself, Bell is now one of a slew of companies pioneering VR pilot tests and simulations with real-world accuracy. Seated in a true-to-life virtual cockpit, pilots have now tested countless iterations of the FCX-001 in virtual flight, drawing directly onto the 3D model and enacting aircraft modifications in real-time.

And in an expansion of our virtual senses, several key players are already working on haptic feedback. In the case of VR flight, French company Go Touch VR is now partnering with software developer FlyInside on fingertip-mounted haptic tech for aviation.

Dramatically reducing time and trouble required for VR-testing pilots, they aim to give touch-based confirmation of every switch and dial activated on virtual flights, just as one would experience in a full-sized cockpit mockup. Replicating texture, stiffness, and even the sensation of holding an object, these piloted devices contain a suite of actuators to simulate everything from a light touch to higher-pressured contact, all controlled by gaze and finger movements.

When it comes to other high-risk simulations, virtual and augmented reality have barely scratched the surface.

Firefighters can now combat virtual wildfires with new platforms like FLAIM Trainer or TargetSolutions. And thanks to the expansion of medical AR/VR services like 3D4Medical or Echopixel, surgeons might soon perform operations on annotated organs and magnified incision sites, speeding up reaction times and vastly improving precision.

But perhaps most urgent, Web 3.0 and its VR interface will offer an immediate solution for today’s constant industry turnover and large-scale re-education demands.

VR educational facilities with exact replicas of anything from large industrial equipment to minute circuitry will soon give anyone a second chance at the 21st-century job market.

Want to be an electric, autonomous vehicle mechanic at age 15? Throw on a demonetized VR module and learn by doing, testing your prototype iterations at almost zero cost and with no risk of harming others.

Want to be a plasma physicist and play around with a virtual nuclear fusion reactor? Now you’ll be able to simulate results and test out different tweaks, logging Smart Educational Record credits in the process.

As tomorrow’s career model shifts from a “one-and-done graduate degree” to lifelong education, professional VR-based re-education will allow for a continuous education loop, reducing the barrier to entry for anyone wanting to enter a new industry.

But beyond professional training and virtually enriched, real-world work scenarios, Web 3.0 promises entirely virtual workplaces and blockchain-secured authorization systems.

Rise of the Virtual Workplace and Digital Data Integrity
In addition to enabling an annual $52 billion virtual goods marketplace, the Spatial Web is also giving way to “virtual company headquarters” and completely virtualized companies, where employees can work from home or any place on the planet.

Too good to be true? Check out an incredible publicly listed company called eXp Realty.

Launched on the heels of the 2008 financial crisis, eXp Realty beat the odds, going public this past May and surpassing a $1B market cap on day one of trading.

But how? Opting for a demonetized virtual model, eXp’s founder Glenn Sanford decided to ditch brick and mortar from the get-go, instead building out an online virtual campus for employees, contractors, and thousands of agents.

And after years of hosting team meetings, training seminars, and even agent discussions with potential buyers through 2D digital interfaces, eXp’s virtual headquarters went spatial.

What is eXp’s primary corporate value? FUN! And Glenn Sanford’s employees love their jobs.

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.

Foregoing any physical locations for a centralized VR campus, eXp Realty has essentially thrown out all overhead and entered a lucrative market with barely any upfront costs.

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.

Throw in the Spatial Web’s fundamental blockchain-based data layer, and now cryptographically secured virtual IDs will let you validate colleagues’ identities or any of the virtual avatars we will soon inhabit.

This becomes critically important for spatial information logs—keeping incorruptible records of who’s present at a meeting, which data each person has access to, and AI-translated reports of everything discussed and contracts agreed to.

But as I discussed in a previous 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 too.

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.

Imaging 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.

Final Thoughts
While converging technologies slash the lifespan of Fortune 500 companies, bring on the rise of vast new industries, and transform the job market, Web 3.0 is changing the way we work, where we work, and who we work with.

Life-like virtual modules are already unlocking countless professional training camps, modifiable in real-time and easily updated.

Virtual programming and blockchain-based authentication are enabling smart data logging, identity protection, and on-demand smart asset trading.

And VR/AR-accessible worlds (and corporate campuses) not only demonetize, dematerialize, and delocalize our everyday workplaces, but enrich our physical worlds with AI-driven, context-specific data.

Welcome to the Spatial Web workplace.

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#433939 The Promise—and Complications—of ...

Every year, for just a few days in a major city, a small team of roboticists get to live the dream: ordering around their own personal robot butlers. In carefully-constructed replicas of a restaurant scene or a domestic setting, these robots perform any number of simple algorithmic tasks. “Get the can of beans from the shelf. Greet the visitors to the museum. Help the humans with their shopping. Serve the customers at the restaurant.”

This is Robocup @ Home, the annual tournament where teams of roboticists put their autonomous service robots to the test for practical domestic applications. The tasks seem simple and mundane, but considering the technology required reveals that they’re really not.

The Robot Butler Contest
Say you want a robot to fetch items in the supermarket. In a crowded, noisy environment, the robot must understand your commands, ask for clarification, and map out and navigate an unfamiliar environment, avoiding obstacles and people as it does so. Then it must recognize the product you requested, perhaps in a cluttered environment, perhaps in an unfamiliar orientation. It has to grasp that product appropriately—recall that there are entire multi-million-dollar competitions just dedicated to developing robots that can grasp a range of objects—and then return it to you.

It’s a job so simple that a child could do it—and so complex that teams of smart roboticists can spend weeks programming and engineering, and still end up struggling to complete simplified versions of this task. Of course, the child has the advantage of millions of years of evolutionary research and development, while the first robots that could even begin these tasks were only developed in the 1970s.

Even bearing this in mind, Robocup @ Home can feel like a place where futurist expectations come crashing into technologist reality. You dream of a smooth-voiced, sardonic JARVIS who’s already made your favorite dinner when you come home late from work; you end up shouting “remember the biscuits” at a baffled, ungainly droid in aisle five.

Caring for the Elderly
Famously, Japan is one of the most robo-enthusiastic nations in the world; they are the nation that stunned us all with ASIMO in 2000, and several studies have been conducted into the phenomenon. It’s no surprise, then, that humanoid robotics should be seriously considered as a solution to the crisis of the aging population. The Japanese government, as part of its robots strategy, has already invested $44 million in their development.

Toyota’s Human Support Robot (HSR-2) is a simple but programmable robot with a single arm; it can be remote-controlled to pick up objects and can monitor patients. HSR-2 has become the default robot for use in Robocup @ Home tournaments, at least in tasks that involve manipulating objects.

Alongside this, Toyota is working on exoskeletons to assist people in walking after strokes. It may surprise you to learn that nurses suffer back injuries more than any other occupation, at roughly three times the rate of construction workers, due to the day-to-day work of lifting patients. Toyota has a Care Assist robot/exoskeleton designed to fix precisely this problem by helping care workers with the heavy lifting.

The Home of the Future
The enthusiasm for domestic robotics is easy to understand and, in fact, many startups already sell robots marketed as domestic helpers in some form or another. In general, though, they skirt the immensely complicated task of building a fully capable humanoid robot—a task that even Google’s skunk-works department gave up on, at least until recently.

It’s plain to see why: far more research and development is needed before these domestic robots could be used reliably and at a reasonable price. Consumers with expectations inflated by years of science fiction saturation might find themselves frustrated as the robots fail to perform basic tasks.

Instead, domestic robotics efforts fall into one of two categories. There are robots specialized to perform a domestic task, like iRobot’s Roomba, which stuck to vacuuming and became the most successful domestic robot of all time by far.

The tasks need not necessarily be simple, either: the impressive but expensive automated kitchen uses the world’s most dexterous hands to cook meals, providing it can recognize the ingredients. Other robots focus on human-robot interaction, like Jibo: they essentially package the abilities of a voice assistant like Siri, Cortana, or Alexa to respond to simple questions and perform online tasks in a friendly, dynamic robot exterior.

In this way, the future of domestic automation starts to look a lot more like smart homes than a robot or domestic servant. General robotics is difficult in the same way that general artificial intelligence is difficult; competing with humans, the great all-rounders, is a challenge. Getting superhuman performance at a more specific task, however, is feasible and won’t cost the earth.

Individual startups without the financial might of a Google or an Amazon can develop specialized robots, like Seven Dreamers’ laundry robot, and hope that one day it will form part of a network of autonomous robots that each have a role to play in the household.

Domestic Bliss?
The Smart Home has been a staple of futurist expectations for a long time, to the extent that movies featuring smart homes out of control are already a cliché. But critics of the smart home idea—and of the internet of things more generally—tend to focus on the idea that, more often than not, software just adds an additional layer of things that can break (NSFW), in exchange for minimal added convenience. A toaster that can short-circuit is bad enough, but a toaster that can refuse to serve you toast because its firmware is updating is something else entirely.

That’s before you even get into the security vulnerabilities, which are all the more important when devices are installed in your home and capable of interacting with them. The idea of a smart watch that lets you keep an eye on your children might sound like something a security-conscious parent would like: a smart watch that can be hacked to track children, listen in on their surroundings, and even fool them into thinking a call is coming from their parents is the stuff of nightmares.

Key to many of these problems is the lack of standardization for security protocols, and even the products themselves. The idea of dozens of startups each developing a highly-specialized piece of robotics to perform a single domestic task sounds great in theory, until you realize the potential hazards and pitfalls of getting dozens of incompatible devices to work together on the same system.

It seems inevitable that there are yet more layers of domestic drudgery that can be automated away, decades after the first generation of time-saving domestic devices like the dishwasher and vacuum cleaner became mainstream. With projected market values into the billions and trillions of dollars, there is no shortage of industry interest in ironing out these kinks. But, for now at least, the answer to the question: “Where’s my robot butler?” is that it is gradually, painstakingly learning how to sort through groceries.

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#433907 How the Spatial Web Will Fix What’s ...

Converging exponential technologies will transform media, advertising and the retail world. The world we see, through our digitally-enhanced eyes, will multiply and explode with intelligence, personalization, and brilliance.

This is the age of Web 3.0.

Last week, I discussed the what and how of Web 3.0 (also known as the Spatial Web), walking through its architecture and the converging technologies that enable it.

To recap, while Web 1.0 consisted of static documents and read-only data, Web 2.0 introduced multimedia content, interactive web applications, and participatory social media, all of these mediated by two-dimensional screens—a flat web of sensorily confined information.

During the next two to five years, the convergence of 5G, AI, a trillion sensors, and VR/AR will enable us to both map our physical world into virtual space and superimpose a digital layer onto our physical environments.

Web 3.0 is about to transform everything—from the way we learn and educate, to the way we trade (smart) assets, to our interactions with real and virtual versions of each other.

And while users grow rightly concerned about data privacy and misuse, the Spatial Web’s use of blockchain in its data and governance layer will secure and validate our online identities, protecting everything from your virtual assets to personal files.

In this second installment of the Web 3.0 series, I’ll be discussing the Spatial Web’s vast implications for a handful of industries:

News & Media Coverage
Smart Advertising
Personalized Retail

Let’s dive in.

Transforming Network News with Web 3.0
News media is big business. In 2016, global news media (including print) generated 168 billion USD in circulation and advertising revenue.

The news we listen to impacts our mindset. Listen to dystopian news on violence, disaster, and evil, and you’ll more likely be searching for a cave to hide in, rather than technology for the launch of your next business.

Today, different news media present starkly different realities of everything from foreign conflict to domestic policy. And outcomes are consequential. What reporters and news corporations decide to show or omit of a given news story plays a tremendous role in shaping the beliefs and resulting values of entire populations and constituencies.

But what if we could have an objective benchmark for today’s news, whereby crowdsourced and sensor-collected evidence allows you to tour the site of journalistic coverage, determining for yourself the most salient aspects of a story?

Enter mesh networks, AI, public ledgers, and virtual reality.

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 protests break out across the country, each cluster of activists broadcasting an aggregate of 360-degree videos, all fed through photogrammetry AIs that build out a live hologram of the march in real time. Want to see and hear what the NYC-based crowds are advocating for? Throw on some VR goggles and explore the event with full access. Or cue into the southern Texan border to assess for yourself the handling of immigrant entry and border conflicts.

Take a front seat in the Capitol during tomorrow’s Senate hearing, assessing each Senator’s reactions, questions and arguments without a Fox News or CNN filter. Or if you’re short on time, switch on the holographic press conference and host 3D avatars of live-broadcasting politicians in your living room.

We often think of modern media as taking away consumer agency, feeding tailored and often partisan ideology to a complacent audience. But as wireless mesh networks and agnostic sensor data allow for immersive VR-accessible news sites, the average viewer will necessarily become an active participant in her own education of current events.

And with each of us interpreting the news according to our own values, I envision a much less polarized world. A world in which civic engagement, moderately reasoned dialogue, and shared assumptions will allow us to empathize and make compromises.

The future promises an era in which news is verified and balanced; wherein public ledgers, AI, and new web interfaces bring you into the action and respect your intelligence—not manipulate your ignorance.

Web 3.0 Reinventing Advertising
Bringing about the rise of ‘user-owned data’ and self-established permissions, Web 3.0 is poised to completely disrupt digital advertising—a global industry worth over 192 billion USD.

Currently, targeted advertising leverages tomes of personal data and online consumer behavior to subtly engage you with products you might not want, or sell you on falsely advertised services promising inaccurate results.

With a new Web 3.0 data and governance layer, however, distributed ledger technologies will require advertisers to engage in more direct interaction with consumers, validating claims and upping transparency.

And with a data layer that allows users to own and authorize third-party use of their data, blockchain also holds extraordinary promise to slash not only data breaches and identity theft, but covert advertiser bombardment without your authorization.

Accessing crowdsourced reviews and AI-driven fact-checking, users will be able to validate advertising claims more efficiently and accurately than ever before, potentially rating and filtering out advertisers in the process. And in such a streamlined system of verified claims, sellers will face increased pressure to compete more on product and rely less on marketing.

But perhaps most exciting is the convergence of artificial intelligence and augmented reality.

As Spatial Web networks begin to associate digital information with physical objects and locations, products will begin to “sell themselves.” Each with built-in smart properties, products will become hyper-personalized, communicating information directly to users through Web 3.0 interfaces.

Imagine stepping into a department store in pursuit of a new web-connected fridge. As soon as you enter, your AR goggles register your location and immediately grant you access to a populated register of store products.

As you move closer to a kitchen set that catches your eye, a virtual salesperson—whether by holographic video or avatar—pops into your field of view next to the fridge you’ve been examining and begins introducing you to its various functions and features. You quickly decide you’d rather disable the avatar and get textual input instead, and preferences are reset to list appliance properties visually.

After a virtual tour of several other fridges, you decide on the one you want and seamlessly execute a smart contract, carried out by your smart wallet and the fridge. The transaction takes place in seconds, and the fridge’s blockchain-recorded ownership record has been updated.

Better yet, you head over to a friend’s home for dinner after moving into the neighborhood. While catching up in the kitchen, your eyes fixate on the cabinets, which quickly populate your AR glasses with a price-point and selection of colors.

But what if you’d rather not get auto-populated product info in the first place? No problem!

Now empowered with self-sovereign identities, users might be able to turn off advertising preferences entirely, turning on smart recommendations only when they want to buy a given product or need new supplies.

And with user-centric data, consumers might even sell such information to advertisers directly. Now, instead of Facebook or Google profiting off your data, you might earn a passive income by giving advertisers permission to personalize and market their services. Buy more, and your personal data marketplace grows in value. Buy less, and a lower-valued advertising profile causes an ebb in advertiser input.

With user-controlled data, advertisers now work on your terms, putting increased pressure on product iteration and personalizing products for each user.

This brings us to the transformative future of retail.

Personalized Retail–Power of the Spatial Web
In a future of smart and hyper-personalized products, I might walk through a virtual game space or a digitally reconstructed Target, browsing specific categories of clothing I’ve predetermined prior to entry.

As I pick out my selection, my AI assistant hones its algorithm reflecting new fashion preferences, and personal shoppers—also visiting the store in VR—help me pair different pieces as I go.

Once my personal shopper has finished constructing various outfits, I then sit back and watch a fashion show of countless Peter avatars with style and color variations of my selection, each customizable.

After I’ve made my selection, I might choose to purchase physical versions of three outfits and virtual versions of two others for my digital avatar. Payments are made automatically as I leave the store, including a smart wallet transaction made with the personal shopper at a per-outfit rate (for only the pieces I buy).

Already, several big players have broken into the VR market. Just this year, Walmart has announced its foray into the VR space, shipping 17,000 Oculus Go VR headsets to Walmart locations across the US.

And just this past January, Walmart filed two VR shopping-related patents. In a new bid to disrupt a rapidly changing retail market, Walmart now describes a system in which users couple their VR headset with haptic gloves for an immersive in-store experience, whether at 3am in your living room or during a lunch break at the office.

But Walmart is not alone. Big e-commerce players from Amazon to Alibaba are leaping onto the scene with new software buildout to ride the impending headset revolution.

Beyond virtual reality, players like IKEA have even begun using mobile-based augmented reality to map digitally replicated furniture in your physical living room, true to dimension. And this is just the beginning….

As AR headset hardware undergoes breakneck advancements in the next two to five years, we might soon be able to project watches onto our wrists, swapping out colors, styles, brand, and price points.

Or let’s say I need a new coffee table in my office. Pulling up multiple models in AR, I can position each option using advanced hand-tracking technology and customize height and width according to my needs. Once the smart payment is triggered, the manufacturer prints my newly-customized piece, droning it to my doorstep. As soon as I need to assemble the pieces, overlaid digital prompts walk me through each step, and any user confusions are communicated to a company database.

Perhaps one of the ripest industries for Spatial Web disruption, retail presents one of the greatest opportunities for profit across virtual apparel, digital malls, AI fashion startups and beyond.

In our next series iteration, I’ll be looking at the tremendous opportunities created by Web 3.0 for the Future of Work and Entertainment.

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#433901 The SpiNNaker Supercomputer, Modeled ...

We’ve long used the brain as inspiration for computers, but the SpiNNaker supercomputer, switched on this month, is probably the closest we’ve come to recreating it in silicon. Now scientists hope to use the supercomputer to model the very thing that inspired its design.

The brain is the most complex machine in the known universe, but that complexity comes primarily from its architecture rather than the individual components that make it up. Its highly interconnected structure means that relatively simple messages exchanged between billions of individual neurons add up to carry out highly complex computations.

That’s the paradigm that has inspired the ‘Spiking Neural Network Architecture” (SpiNNaker) supercomputer at the University of Manchester in the UK. The project is the brainchild of Steve Furber, the designer of the original ARM processor. After a decade of development, a million-core version of the machine that will eventually be able to simulate up to a billion neurons was switched on earlier this month.

The idea of splitting computation into very small chunks and spreading them over many processors is already the leading approach to supercomputing. But even the most parallel systems require a lot of communication, and messages may have to pack in a lot of information, such as the task that needs to be completed or the data that needs to be processed.

In contrast, messages in the brain consist of simple electrochemical impulses, or spikes, passed between neurons, with information encoded primarily in the timing or rate of those spikes (which is more important is a topic of debate among neuroscientists). Each neuron is connected to thousands of others via synapses, and complex computation relies on how spikes cascade through these highly-connected networks.

The SpiNNaker machine attempts to replicate this using a model called Address Event Representation. Each of the million cores can simulate roughly a million synapses, so depending on the model, 1,000 neurons with 1,000 connections or 100 neurons with 10,000 connections. Information is encoded in the timing of spikes and the identity of the neuron sending them. When a neuron is activated it broadcasts a tiny packet of data that contains its address, and spike timing is implicitly conveyed.

By modeling their machine on the architecture of the brain, the researchers hope to be able to simulate more biological neurons in real time than any other machine on the planet. The project is funded by the European Human Brain Project, a ten-year science mega-project aimed at bringing together neuroscientists and computer scientists to understand the brain, and researchers will be able to apply for time on the machine to run their simulations.

Importantly, it’s possible to implement various different neuronal models on the machine. The operation of neurons involves a variety of complex biological processes, and it’s still unclear whether this complexity is an artefact of evolution or central to the brain’s ability to process information. The ability to simulate up to a billion simple neurons or millions of more complex ones on the same machine should help to slowly tease out the answer.

Even at a billion neurons, that still only represents about one percent of the human brain, so it’s still going to be limited to investigating isolated networks of neurons. But the previous 500,000-core machine has already been used to do useful simulations of the Basal Ganglia—an area affected in Parkinson’s disease—and an outer layer of the brain that processes sensory information.

The full-scale supercomputer will make it possible to study even larger networks previously out of reach, which could lead to breakthroughs in our understanding of both the healthy and unhealthy functioning of the brain.

And while neurological simulation is the main goal for the machine, it could also provide a useful research tool for roboticists. Previous research has already shown a small board of SpiNNaker chips can be used to control a simple wheeled robot, but Furber thinks the SpiNNaker supercomputer could also be used to run large-scale networks that can process sensory input and generate motor output in real time and at low power.

That low power operation is of particular promise for robotics. The brain is dramatically more power-efficient than conventional supercomputers, and by borrowing from its principles SpiNNaker has managed to capture some of that efficiency. That could be important for running mobile robotic platforms that need to carry their own juice around.

This ability to run complex neural networks at low power has been one of the main commercial drivers for so-called neuromorphic computing devices that are physically modeled on the brain, such as IBM’s TrueNorth chip and Intel’s Loihi. The hope is that complex artificial intelligence applications normally run in massive data centers could be run on edge devices like smartphones, cars, and robots.

But these devices, including SpiNNaker, operate very differently from the leading AI approaches, and its not clear how easy it would be to transfer between the two. The need to adopt an entirely new programming paradigm is likely to limit widespread adoption, and the lack of commercial traction for the aforementioned devices seems to back that up.

At the same time, though, this new paradigm could potentially lead to dramatic breakthroughs in massively parallel computing. SpiNNaker overturns many of the foundational principles of how supercomputers work that make it much more flexible and error-tolerant.

For now, the machine is likely to be firmly focused on accelerating our understanding of how the brain works. But its designers also hope those findings could in turn point the way to more efficient and powerful approaches to computing.

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