Tag Archives: large

#437120 The New Indiana Jones? AI. Here’s How ...

Posted on May 7, 2020 by Android

Archaeologists have uncovered scores of long-abandoned settlements along coastal Madagascar that reveal environmental connections to modern-day communities. They have detected the nearly indiscernible bumps of earthen mounds left behind by prehistoric North American cultures. Still other researchers have mapped Bronze Age river systems in the Indus Valley, one of the cradles of civilization.

All of these recent discoveries are examples of landscape archaeology. They’re also examples of how artificial intelligence is helping scientists hunt for new archaeological digs on a scale and at a pace unimaginable even a decade ago.

“AI in archaeology has been increasing substantially over the past few years,” said Dylan Davis, a PhD candidate in the Department of Anthropology at Penn State University. “One of the major uses of AI in archaeology is for the detection of new archaeological sites.”

The near-ubiquitous availability of satellite data and other types of aerial imagery for many parts of the world has been both a boon and a bane to archaeologists. They can cover far more ground, but the job of manually mowing their way across digitized landscapes is still time-consuming and laborious. Machine learning algorithms offer a way to parse through complex data far more quickly.

AI Gives Archaeologists a Bird’s Eye View
Davis developed an automated algorithm for identifying large earthen and shell mounds built by native populations long before Europeans arrived with far-off visions of skyscrapers and superhighways in their eyes. The sites still hidden in places like the South Carolina wilderness contain a wealth of information about how people lived, even what they ate, and the ways they interacted with the local environment and other cultures.

In this particular case, the imagery comes from LiDAR, which uses light pulses that can penetrate tree canopies to map forest floors. The team taught the computer the shape, size, and texture characteristics of the mounds so it could identify potential sites from the digital 3D datasets that it analyzed.

“The process resulted in several thousand possible features that my colleagues and I checked by hand,” Davis told Singularity Hub. “While not entirely automated, this saved the equivalent of years of manual labor that would have been required for analyzing the whole LiDAR image by hand.”

In Madagascar—where Davis is studying human settlement history across the world’s fourth largest island over a timescale of millennia—he developed a predictive algorithm to help locate archaeological sites using freely available satellite imagery. His team was able to survey and identify more than 70 new archaeological sites—and potentially hundreds more—across an area of more than 1,000 square kilometers during the course of about a year.

Machines Learning From the Past Prepare Us for the Future
One impetus behind the rapid identification of archaeological sites is that many are under threat from climate change, such as coastal erosion from sea level rise, or other human impacts. Meanwhile, traditional archaeological approaches are expensive and laborious—serious handicaps in a race against time.

“It is imperative to record as many archaeological sites as we can in a short period of time. That is why AI and machine learning are useful for my research,” Davis said.

Studying the rise and fall of past civilizations can also teach modern humans a thing or two about how to grapple with these current challenges.

Researchers at the Institut Català d’Arqueologia Clàssica (ICAC) turned to machine-learning algorithms to reconstruct more than 20,000 kilometers of paleo-rivers along the Indus Valley civilization of what is now part of modern Pakistan and India. Such AI-powered mapping techniques wouldn’t be possible using satellite images alone.

That effort helped locate many previously unknown archaeological sites and unlocked new insights into those Bronze Age cultures. However, the analytics can also assist governments with important water resource management today, according to Hèctor A. Orengo Romeu, co-director of the Landscape Archaeology Research Group at ICAC.

“Our analyses can contribute to the forecasts of the evolution of aquifers in the area and provide valuable information on aspects such as the variability of agricultural productivity or the influence of climate change on the expansion of the Thar desert, in addition to providing cultural management tools to the government,” he said.

Leveraging AI for Language and Lots More
While landscape archaeology is one major application of AI in archaeology, it’s far from the only one. In 2000, only about a half-dozen scientific papers referred to the use of AI, according to the Web of Science, reputedly the world’s largest global citation database. Last year, more than 65 papers were published concerning the use of machine intelligence technologies in archaeology, with a significant uptick beginning in 2015.

AI methods, for instance, are being used to understand the chemical makeup of artifacts like pottery and ceramics, according to Davis. “This can help identify where these materials were made and how far they were transported. It can also help us to understand the extent of past trading networks.”

Linguistic anthropologists have also used machine intelligence methods to trace the evolution of different languages, Davis said. “Using AI, we can learn when and where languages emerged around the world.”

In other cases, AI has helped reconstruct or decipher ancient texts. Last year, researchers at Google’s DeepMind used a deep neural network called PYTHIA to recreate missing inscriptions in ancient Greek from damaged surfaces of objects made of stone or ceramics.

Named after the Oracle at Delphi, PYTHIA “takes a sequence of damaged text as input, and is trained to predict character sequences comprising hypothesised restorations of ancient Greek inscriptions,” the researchers reported.

In a similar fashion, Chinese scientists applied a convolutional neural network (CNN) to untangle another ancient tongue once found on turtle shells and ox bones. The CNN managed to classify oracle bone morphology in order to piece together fragments of these divination objects, some with inscriptions that represent the earliest evidence of China’s recorded history.

“Differentiating the materials of oracle bones is one of the most basic steps for oracle bone morphology—we need to first make sure we don’t assemble pieces of ox bones with tortoise shells,” lead author of the study, associate professor Shanxiong Chen at China’s Southwest University, told Synced, an online tech publication in China.

AI Helps Archaeologists Get the Scoop…
And then there are applications of AI in archaeology that are simply … interesting. Just last month, researchers published a paper about a machine learning method trained to differentiate between human and canine paleofeces.

The algorithm, dubbed CoproID, compares the gut microbiome DNA found in the ancient material with DNA found in modern feces, enabling it to get the scoop on the origin of the poop.

Also known as coprolites, paleo-feces from humans and dogs are often found in the same archaeological sites. Scientists need to know which is which if they’re trying to understand something like past diets or disease.

“CoproID is the first line of identification in coprolite analysis to confirm that what we’re looking for is actually human, or a dog if we’re interested in dogs,” Maxime Borry, a bioinformatics PhD student at the Max Planck Institute for the Science of Human History, told Vice.

…But Machine Intelligence Is Just Another Tool
There is obviously quite a bit of work that can be automated through AI. But there’s no reason for archaeologists to hit the unemployment line any time soon. There are also plenty of instances where machines can’t yet match humans in identifying objects or patterns. At other times, it’s just faster doing the analysis yourself, Davis noted.

“For ‘big data’ tasks like detecting archaeological materials over a continental scale, AI is useful,” he said. “But for some tasks, it is sometimes more time-consuming to train an entire computer algorithm to complete a task that you can do on your own in an hour.”

Still, there’s no telling what the future will hold for studying the past using artificial intelligence.

“We have already started to see real improvements in the accuracy and reliability of these approaches, but there is a lot more to do,” Davis said. “Hopefully, we start to see these methods being directly applied to a variety of interesting questions around the world, as these methods can produce datasets that would have been impossible a few decades ago.”

Image Credit: James Wheeler from Pixabay Continue reading →

Posted in Human Robots

#437103 How to Make Sense of Uncertainty in a ...

Posted on May 1, 2020 by Android

As the internet churns with information about Covid-19, about the virus that causes the disease, and about what we’re supposed to do to fight it, it can be difficult to see the forest for the trees. What can we realistically expect for the rest of 2020? And how do we even know what’s realistic?

Today, humanity’s primary, ideal goal is to eliminate the virus, SARS-CoV-2, and Covid-19. Our second-choice goal is to control virus transmission. Either way, we have three big aims: to save lives, to return to public life, and to keep the economy functioning.

To hit our second-choice goal—and maybe even our primary goal—countries are pursuing five major public health strategies. Note that many of these advances cross-fertilize: for example, advances in virus testing and antibody testing will drive data-based prevention efforts.

Five major public health strategies are underway to bring Covid-19 under control and to contain the spread of SARS-CoV-2.
These strategies arise from things we can control based on the things that we know at any given moment. But what about the things we can’t control and don’t yet know?

The biology of the virus and how it interacts with our bodies is what it is, so we should seek to understand it as thoroughly as possible. How long any immunity gained from prior infection lasts—and indeed whether people develop meaningful immunity at all after infection—are open questions urgently in need of greater clarity. Similarly, right now it’s important to focus on understanding rather than making assumptions about environmental factors like seasonality.

But the biggest question on everyone’s lips is, “When?” When will we see therapeutic progress against Covid-19? And when will life get “back to normal”? There are lots of models out there on the internet; which of those models are right? The simple answer is “none of them.” That’s right—it’s almost certain that every model you’ve seen is wrong in at least one detail, if not all of them. But modeling is meant to be a tool for deeper thinking, a way to run mental (and computational) experiments before—and while—taking action. As George E. P. Box famously wrote in 1976, “All models are wrong, but some are useful.”

Here, we’re seeking useful insights, as opposed to exact predictions, which is why we’re pulling back from quantitative details to get at the mindsets that will support agency and hope. To that end, I’ve been putting together timelines that I believe will yield useful expectations for the next year or two—and asking how optimistic I need to be in order to believe a particular timeline.

For a moderately optimistic scenario to be relevant, breakthroughs in science and technology come at paces expected based on previous efforts and assumptions that turn out to be basically correct; accessibility of those breakthroughs increases at a reasonable pace; regulation achieves its desired effects, without major surprises; and compliance with regulations is reasonably high.

In contrast, if I’m being highly optimistic, breakthroughs in science and technology and their accessibility come more quickly than they ever have before; regulation is evidence-based and successful in the first try or two; and compliance with those regulations is high and uniform. If I’m feeling not-so-optimistic, then I anticipate serious setbacks to breakthroughs and accessibility (with the overturning of many important assumptions), repeated failure of regulations to achieve their desired outcomes, and low compliance with those regulations.

The following scenarios outline the things that need to happen in the fight against Covid-19, when I expect to see them, and how confident I feel in those expectations. They focus on North America and Europe because there are data missing about China’s 2019 outbreak and other regions are still early in their outbreaks. Perhaps the most important thing to keep in mind throughout: We know more today than we did yesterday, but we still have much to learn. New knowledge derived from greater study and debate will almost certainly inspire ongoing course corrections.

As you dive into the scenarios below, practice these three mindset shifts. First, defeating Covid-19 will be a marathon, not a sprint. We shouldn’t expect life to look like 2019 for the next year or two—if ever. As Ed Yong wrote recently in The Atlantic, “There won’t be an obvious moment when everything is under control and regular life can safely resume.” Second, remember that you have important things to do for at least a year. And third, we are all in this together. There is no “us” and “them.” We must all be alert, responsive, generous, and strong throughout 2020 and 2021—and willing to throw away our assumptions when scientific evidence invalidates them.

The Middle Way: Moderate Optimism
Let’s start with the case in which I have the most confidence: moderate optimism.

This timeline considers milestones through late 2021, the earliest that I believe vaccines will become available. The “normal” timeline for developing a vaccine for diseases like seasonal flu is 18 months, which leads to my projection that we could potentially have vaccines as soon as 18 months from the first quarter of 2020. While Melinda Gates agrees with that projection, others (including AI) believe that 3 to 5 years is far more realistic, based on past vaccine development and the need to test safety and efficacy in humans. However, repurposing existing vaccines against other diseases—or piggybacking off clever synthetic platforms—could lead to vaccines being available sooner. I tried to balance these considerations for this moderately optimistic scenario. Either way, deploying vaccines at the end of 2021 is probably much later than you may have been led to believe by the hype engine. Again, if you take away only one message from this article, remember that the fight against Covid-19 is a marathon, not a sprint.

Here, I’ve visualized a moderately optimistic scenario as a baseline. Think of these timelines as living guides, as opposed to exact predictions. There are still many unknowns. More or less optimistic views (see below) and new information could shift these timelines forward or back and change the details of the strategies.
Based on current data, I expect that the first wave of Covid-19 cases (where we are now) will continue to subside in many areas, leading governments to ease restrictions in an effort to get people back to work. We’re already seeing movement in that direction, with a variety of benchmarks and changes at state and country levels around the world. But depending on the details of the changes, easing restrictions will probably cause a second wave of sickness (see Germany and Singapore), which should lead governments to reimpose at least some restrictions.

In tandem, therapeutic efforts will be transitioning from emergency treatments to treatments that have been approved based on safety and efficacy data in clinical trials. In a moderately optimistic scenario, assuming clinical trials currently underway yield at least a few positive results, this shift to mostly approved therapies could happen as early as the third or fourth quarter of this year and continue from there. One approval that should come rather quickly is for plasma therapies, in which the blood from people who have recovered from Covid-19 is used as a source of antibodies for people who are currently sick.

Companies around the world are working on both viral and antibody testing, focusing on speed, accuracy, reliability, and wide accessibility. While these tests are currently being run in hospitals and research laboratories, at-home testing is a critical component of the mass testing we’ll need to keep viral spread in check. These are needed to minimize the impact of asymptomatic cases, test the assumption that infection yields resistance to subsequent infection (and whether it lasts), and construct potential immunity passports if this assumption holds. Testing is also needed for contact tracing efforts to prevent further spread and get people back to public life. Finally, it’s crucial to our fundamental understanding of the biology of SARS-CoV-2 and Covid-19.

We need tests that are very reliable, both in the clinic and at home. So, don’t go buying any at-home test kits just yet, even if you find them online. Wait for reliable test kits and deeper understanding of how a test result translates to everyday realities. If we’re moderately optimistic, in-clinic testing will rapidly expand this quarter and/or next, with the possibility of broadly available, high-quality at-home sampling (and perhaps even analysis) thereafter.

Note that testing is not likely to be a “one-and-done” endeavor, as a person’s infection and immunity status change over time. Expect to be testing yourself—and your family—often as we move later into 2020.

Testing data are also going to inform distancing requirements at the country and local levels. In this scenario, restrictions—at some level of stringency—could persist at least through the end of 2020, as most countries are way behind the curve on testing (Iceland is an informative exception). Governments will likely continue to ask citizens to work from home if at all possible; to wear masks or face coverings in public; to employ heightened hygiene and social distancing in workplaces; and to restrict travel and social gatherings. So while it’s likely we’ll be eating in local restaurants again in 2020 in this scenario, at least for a little while, it’s not likely we’ll be heading to big concerts any time soon.

The Extremes: High and Low Optimism
How would high and low levels of optimism change our moderately optimistic timeline? The milestones are the same, but the time required to achieve them is shorter or longer, respectively. Quantifying these shifts is less important than acknowledging and incorporating a range of possibilities into our view. It pays to pay attention to our bias. Here are a few examples of reasonable possibilities that could shift the moderately optimistic timeline.

When vaccines become available
Vaccine repurposing could shorten the time for vaccines to become available; today, many vaccine candidates are in various stages of testing. On the other hand, difficulties in manufacture and distribution, or faster-than-expected mutation of SARS-CoV-2, could slow vaccine development. Given what we know now, I am not strongly concerned about either of these possibilities—drug companies are rapidly expanding their capabilities, and viral mutation isn’t an urgent concern at this time based on sequencing data—but they could happen.

At first, governments will likely supply vaccines to essential workers such as healthcare workers, but it is essential that vaccines become widely available around the world as quickly and as safely as possible. Overall, I suggest a dose of skepticism when reading highly optimistic claims about a vaccine (or multiple vaccines) being available in 2020. Remember, a vaccine is a knockout punch, not a first line of defense for an outbreak.

When testing hits its stride
While I am confident that testing is a critical component of our response to Covid-19, reliability is incredibly important to testing for SARS-CoV-2 and for immunity to the disease, particularly at home. For an individual, a false negative (being told you don’t have antibodies when you really do) could be just as bad as a false positive (being told you do have antibodies when you really don’t). Those errors are compounded when governments are trying to make evidence-based policies for social and physical distancing.

If you’re highly optimistic, high-quality testing will ramp up quickly as companies and scientists innovate rapidly by cleverly combining multiple test modalities, digital signals, and cutting-edge tech like CRISPR. Pop-up testing labs could also take some pressure off hospitals and clinics.

If things don’t go well, reliability issues could hinder testing, manufacturing bottlenecks could limit availability, and both could hamstring efforts to control spread and ease restrictions. And if it turns out that immunity to Covid-19 isn’t working the way we assumed, then we must revisit our assumptions about our path(s) back to public life, as well as our vaccine-development strategies.

How quickly safe and effective treatments appear
Drug development is known to be long, costly, and fraught with failure. It’s not uncommon to see hope in a drug spike early only to be dashed later on down the road. With that in mind, the number of treatments currently under investigation is astonishing, as is the speed through which they’re proceeding through testing. Breakthroughs in a therapeutic area—for example in treating the seriously ill or in reducing viral spread after an infection takes hold—could motivate changes in the focus of distancing regulations.

While speed will save lives, we cannot overlook the importance of knowing a treatment’s efficacy (does it work against Covid-19?) and safety (does it make you sick in a different, or worse, way?). Repurposing drugs that have already been tested for other diseases is speeding innovation here, as is artificial intelligence.

Remarkable collaborations among governments and companies, large and small, are driving innovation in therapeutics and devices such as ventilators for treating the sick.

Whether government policies are effective and responsive
Those of us who have experienced lockdown are eager for it to be over. Businesses, economists, and governments are also eager to relieve the terrible pressure that is being exerted on the global economy. However, lifting restrictions will almost certainly lead to a resurgence in sickness.

Here, the future is hard to model because there are many, many factors at play, and at play differently in different places—including the extent to which individuals actually comply with regulations.

Reliable testing—both in the clinic and at home—is crucial to designing and implementing restrictions, monitoring their effectiveness, and updating them; delays in reliable testing could seriously hamper this design cycle. Lack of trust in governments and/or companies could also suppress uptake. That said, systems are already in place for contact tracing in East Asia. Other governments could learn important lessons, but must also earn—and keep—their citizens’ trust.

Expect to see restrictions descend and then lift in response to changes in the number of Covid-19 cases and in the effectiveness of our prevention strategies. Also expect country-specific and perhaps even area-specific responses that differ from each other. The benefit of this approach? Governments around the world are running perhaps hundreds of real-time experiments and design cycles in balancing health and the economy, and we can learn from the results.

A Way Out
As Jeremy Farrar, head of the Wellcome Trust, told Science magazine, “Science is the exit strategy.” Some of our greatest technological assistance is coming from artificial intelligence, digital tools for collaboration, and advances in biotechnology.

Our exit strategy also needs to include empathy and future visioning—because in the midst of this crisis, we are breaking ground for a new, post-Covid future.

What do we want that future to look like? How will the hard choices we make now about data ethics impact the future of surveillance? Will we continue to embrace inclusiveness and mass collaboration? Perhaps most importantly, will we lay the foundation for successfully confronting future challenges? Whether we’re thinking about the next pandemic (and there will be others) or the cascade of catastrophes that climate change is bringing ever closer—it’s important to remember that we all have the power to become agents of that change.

Special thanks to Ola Kowalewski and Jason Dorrier for significant conversations.

Image Credit: Drew Beamer / Unsplash Continue reading →

Posted in Human Robots

#436962 Scientists Engineered Neurons to Make ...

Posted on March 23, 2020 by Android

Electricity plays a surprisingly powerful role in our bodies. While most people are aware that it plays a crucial role in carrying signals to and from our nerves, our bodies produce electric fields that can do everything from helping heal wounds to triggering the release of hormones.

Electric fields can influence a host of important cellular behavior, like directional migration, proliferation, division, or even differentiation into different cell types. The work of Michael Levin at Tufts University even suggests that electrical fields may play a crucial role in the way our bodies organize themselves.

This has prompted considerable interest in exploiting our body’s receptiveness to electrical stimulation for therapeutic means, but given the diffuse nature of electrical fields a key challenge is finding a way to localize these effects. Conductive polymers have proven a useful tool in this regard thanks to their good electrical properties and biocompatibility, and have been used in everything from neural implants to biosensors.

But now, a team at Stanford University has developed a way to genetically engineer neurons to build the materials into their own cell membranes. The approach could make it possible to target highly specific groups of cells, providing unprecedented control over the body’s response to electrical stimulation.

In a paper in Science, the team explained how they used re-engineered viruses to deliver DNA that hijacks cells’ biosynthesis machinery to create an enzyme that assembles electroactive polymers onto their membranes. This changes the electrical properties of the cells, which the team demonstrated could be used to control their behavior.

They used the approach to modulate neuronal firing in cultures of rat hippocampal neurons, mouse brain slices, and even human cortical spheroids. Most impressively, they showed that they could coax the neurons of living C. elegans worms to produce the polymers in large enough quantities to alter their behavior without impairing the cells’ natural function.

Translating the idea to humans poses major challenges, not least because the viruses used to deliver the genetic changes are still a long way from being approved for clinical use. But the ability to precisely target specific cells using a genetic approach holds enormous promise for bioelectronic medicine, Kevin Otto and Christine Schmidt from the University of Florida say in an accompanying perspective.

Interest is booming in therapies that use electrical stimulation of neural circuits as an alternative to drugs for diseases as varied as arthritis, Alzheimer’s, diabetes, and cardiovascular disease, and hundreds of clinical trials are currently underway.

At present these approaches rely on electrodes that can provide some level of localization, but because different kinds of nerve cells are often packed closely together it’s proven hard to stimulate exactly the right nerves, say Otto and Schmidt. This new approach makes it possible to boost the conductivity of specific cell types, which could make these kinds of interventions dramatically more targeted.

Besides disease-focused bioelectronic interventions, Otto and Schmidt say the approach could prove invaluable for helping to interface advanced prosthetics with patients’ nervous systems by making it possible to excite sensory neurons without accidentally triggering motor neurons, or vice versa.

More speculatively, the approach could one day help create far more efficient bridges between our minds and machines. One of the major challenges for brain-machine interfaces is recording from specific neurons, something that a genetically targeted approach might be able to help greatly with.

If the researchers can replicate the ability to build electronic-tissue “composites” in humans, we may be well on our way to the cyborg future predicted by science fiction.

Image Credit: Gerd Altmann from Pixabay Continue reading →

Posted in Human Robots

#436573 This Week’s Awesome Tech Stories From ...

Posted on February 23, 2020 by Android

ARTIFICIAL INTELLIGENCE
The Messy, Secretive Reality Behind OpenAI’s Bid to Save the World
Karen Hao | MIT Technology Review
“The AI moonshot was founded in the spirit of transparency. This is the inside story of how competitive pressure eroded that idealism. …Yet OpenAI is still a bastion of talent and cutting-edge research, filled with people who are sincerely striving to work for the benefit of humanity. In other words, it still has the most important elements, and there’s still time for it to change.”

ROBOTICS
3D Printed Four-Legged Robot Is Ready to Take on Spot—at a Lower Price
Luke Dormehl | Digital Trends
“[Ghost Robotics and Origin] have teamed up to develop a new line of robots, called the Spirit Series, which offer impressively capable four-legged robots, but which can be printed using additive manufacturing at a fraction of the cost and speed of traditional manufacturing approaches.”

PRIVACY
The Studs on This Punk Bracelet Are Actually Microphone-Jamming Ultrasonic Speakers
Andrew Liszewski | Gizmodo
“You can prevent facial recognition cameras from identifying you by wearing face paint, masks, or sometimes just a pair of oversized sunglasses. Keeping conversations private from an ever-growing number of microphone-equipped devices isn’t quite as easy, but researchers have created what could be the first wearable that actually helps increase your privacy.”

TRANSPORTATION
Iron Man Dreams Are Closer to Becoming a Reality Thanks to This New Jetman Dubai Video
Julia Alexander | The Verge
“Tony Stark may have destroyed his Iron Man suits in Iron Man 3 (only to bring out a whole new line in Avengers: Age of Ultron), but Jetman Dubai’s Iron Man-like dreams of autonomous human flight are realer than ever. A new video published by the company shows pilot Vince Reffet using a jet-powered, carbon-fiber suit to launch off the ground and fly 6,000 feet in the air.”

TECHNOLOGY
Wikipedia Is the Last Best Place on the Internet
Richard Cooke | Wired
“More than an encyclopedia, Wikipedia has become a community, a library, a constitution, an experiment, a political manifesto—the closest thing there is to an online public square. It is one of the few remaining places that retains the faintly utopian glow of the early World Wide Web.”

SCIENCE
The Very Large Array Will Search for Evidence of Extraterrestrial Life
Georgina Torbet | Digital Trends
“To begin the project, an interface will be added to the NRAO’s Very Large Array (VLA) in New Mexico to search for events or structures which could indicate the presence of life, such as laser beams, structures built around stars, indications of constructed satellites, or atmospheric chemicals produced by industry.”

SCIENCE FICTION
The Terrible Truth About Star Trek’s Transporters
Cassidy Ward | SyFy Wire
“The fact that you are scanned, deconstructed, and rebuilt almost immediately thereafter only creates the illusion of continuity. In reality, you are killed and then something exactly like you is born, elsewhere. There’s a whole philosophical debate about whether this really matters. If the person constructed on the other end is identical to you, down to the atomic level, is there any measurable difference from it being actually you?”

Image Credit: Samuel Giacomelli / Unsplash Continue reading →

Posted in Human Robots

#436550 Work in the Age of Web 3.0

Posted on February 7, 2020 by Android

What is the future of work? Is our future one of ‘technological socialism’ (where technology is taking care of our needs)? Or will tomorrow’s workplace be completely virtualized, allowing us to 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 artificial intelligence, virtual reality, and the spatial web converge to transform every element of our careers, from training, to execution, to free time.

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 blog, I’ll be discussing the Spatial Web’s vast implications for:

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

Let’s dive in.

Virtual Training, Real-World Results
Virtual and augmented reality have already begun disrupting the professional training market. As projected by ABI Research, the enterprise VR training market is on track to exceed $6.3 billion in value by 2022.

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.

Then 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. By mid-2019, Walmart had tracked a 10-15 percent boost in employee confidence as a result of newly implemented VR 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 6-year aircraft design process into the course of 6 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 continuous 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 & Digital Data Integrity
In addition to enabling a 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.

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.

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.

Join Me
(1) A360 Executive Mastermind: If you’re an exponentially and abundance-minded entrepreneur who would like coaching directly from me, consider joining my Abundance 360 Mastermind, a highly selective community of 360 CEOs and entrepreneurs who I coach for 3 days every January in Beverly Hills, Ca. Through A360, I provide my members with context and clarity about how converging exponential technologies will transform every industry. I’m committed to running A360 for the course of an ongoing 25-year journey as a “countdown to the Singularity.”

If you’d like to learn more and consider joining our 2021 membership, apply here.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs—those who want to get involved and play at a higher level. Click here to learn more.

(Both A360 and Abundance-Digital are part of Singularity University—your participation opens you to a global community.)

This article originally appeared on diamandis.com. Read the original article here.

Image Credit: Image by Gerd Altmann from Pixabay Continue reading →

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