Tag Archives: simple

#435423 Moving Beyond Mind-Controlled Limbs to ...

Posted on July 31, 2019 by Android

Brain-machine interface enthusiasts often gush about “closing the loop.” It’s for good reason. On the implant level, it means engineering smarter probes that only activate when they detect faulty electrical signals in brain circuits. Elon Musk’s Neuralink—among other players—are readily pursuing these bi-directional implants that both measure and zap the brain.

But to scientists laboring to restore functionality to paralyzed patients or amputees, “closing the loop” has broader connotations. Building smart mind-controlled robotic limbs isn’t enough; the next frontier is restoring sensation in offline body parts. To truly meld biology with machine, the robotic appendage has to “feel one” with the body.

This month, two studies from Science Robotics describe complementary ways forward. In one, scientists from the University of Utah paired a state-of-the-art robotic arm—the DEKA LUKE—with electrically stimulating remaining nerves above the attachment point. Using artificial zaps to mimic the skin’s natural response patterns to touch, the team dramatically increased the patient’s ability to identify objects. Without much training, he could easily discriminate between the small and large and the soft and hard while blindfolded and wearing headphones.

In another, a team based at the National University of Singapore took inspiration from our largest organ, the skin. Mimicking the neural architecture of biological skin, the engineered “electronic skin” not only senses temperature, pressure, and humidity, but continues to function even when scraped or otherwise damaged. Thanks to artificial nerves that transmit signals far faster than our biological ones, the flexible e-skin shoots electrical data 1,000 times quicker than human nerves.

Together, the studies marry neuroscience and robotics. Representing the latest push towards closing the loop, they show that integrating biological sensibilities with robotic efficiency isn’t impossible (super-human touch, anyone?). But more immediately—and more importantly—they’re beacons of hope for patients who hope to regain their sense of touch.

For one of the participants, a late middle-aged man with speckled white hair who lost his forearm 13 years ago, superpowers, cyborgs, or razzle-dazzle brain implants are the last thing on his mind. After a barrage of emotionally-neutral scientific tests, he grasped his wife’s hand and felt her warmth for the first time in over a decade. His face lit up in a blinding smile.

That’s what scientists are working towards.

Biomimetic Feedback
The human skin is a marvelous thing. Not only does it rapidly detect a multitude of sensations—pressure, temperature, itch, pain, humidity—its wiring “binds” disparate signals together into a sensory fingerprint that helps the brain identify what it’s feeling at any moment. Thanks to over 45 miles of nerves that connect the skin, muscles, and brain, you can pick up a half-full coffee cup, knowing that it’s hot and sloshing, while staring at your computer screen. Unfortunately, this complexity is also why restoring sensation is so hard.

The sensory electrode array implanted in the participant’s arm. Image Credit: George et al., Sci. Robot. 4, eaax2352 (2019)..
However, complex neural patterns can also be a source of inspiration. Previous cyborg arms are often paired with so-called “standard” sensory algorithms to induce a basic sense of touch in the missing limb. Here, electrodes zap residual nerves with intensities proportional to the contact force: the harder the grip, the stronger the electrical feedback. Although seemingly logical, that’s not how our skin works. Every time the skin touches or leaves an object, its nerves shoot strong bursts of activity to the brain; while in full contact, the signal is much lower. The resulting electrical strength curve resembles a “U.”

The LUKE hand. Image Credit: George et al., Sci. Robot. 4, eaax2352 (2019).
The team decided to directly compare standard algorithms with one that better mimics the skin’s natural response. They fitted a volunteer with a robotic LUKE arm and implanted an array of electrodes into his forearm—right above the amputation—to stimulate the remaining nerves. When the team activated different combinations of electrodes, the man reported sensations of vibration, pressure, tapping, or a sort of “tightening” in his missing hand. Some combinations of zaps also made him feel as if he were moving the robotic arm’s joints.

In all, the team was able to carefully map nearly 120 sensations to different locations on the phantom hand, which they then overlapped with contact sensors embedded in the LUKE arm. For example, when the patient touched something with his robotic index finger, the relevant electrodes sent signals that made him feel as if he were brushing something with his own missing index fingertip.

Standard sensory feedback already helped: even with simple electrical stimulation, the man could tell apart size (golf versus lacrosse ball) and texture (foam versus plastic) while blindfolded and wearing noise-canceling headphones. But when the team implemented two types of neuromimetic feedback—electrical zaps that resembled the skin’s natural response—his performance dramatically improved. He was able to identify objects much faster and more accurately under their guidance. Outside the lab, he also found it easier to cook, feed, and dress himself. He could even text on his phone and complete routine chores that were previously too difficult, such as stuffing an insert into a pillowcase, hammering a nail, or eating hard-to-grab foods like eggs and grapes.

The study shows that the brain more readily accepts biologically-inspired electrical patterns, making it a relatively easy—but enormously powerful—upgrade that seamlessly integrates the robotic arms with the host. “The functional and emotional benefits…are likely to be further enhanced with long-term use, and efforts are underway to develop a portable take-home system,” the team said.

E-Skin Revolution: Asynchronous Coded Electronic Skin (ACES)
Flexible electronic skins also aren’t new, but the second team presented an upgrade in both speed and durability while retaining multiplexed sensory capabilities.

Starting from a combination of rubber, plastic, and silicon, the team embedded over 200 sensors onto the e-skin, each capable of discerning contact, pressure, temperature, and humidity. They then looked to the skin’s nervous system for inspiration. Our skin is embedded with a dense array of nerve endings that individually transmit different types of sensations, which are integrated inside hubs called ganglia. Compared to having every single nerve ending directly ping data to the brain, this “gather, process, and transmit” architecture rapidly speeds things up.

The team tapped into this biological architecture. Rather than pairing each sensor with a dedicated receiver, ACES sends all sensory data to a single receiver—an artificial ganglion. This setup lets the e-skin’s wiring work as a whole system, as opposed to individual electrodes. Every sensor transmits its data using a characteristic pulse, which allows it to be uniquely identified by the receiver.

The gains were immediate. First was speed. Normally, sensory data from multiple individual electrodes need to be periodically combined into a map of pressure points. Here, data from thousands of distributed sensors can independently go to a single receiver for further processing, massively increasing efficiency—the new e-skin’s transmission rate is roughly 1,000 times faster than that of human skin.

Second was redundancy. Because data from individual sensors are aggregated, the system still functioned even when any individual receptors are damaged, making it far more resilient than previous attempts. Finally, the setup could easily scale up. Although the team only tested the idea with 240 sensors, theoretically the system should work with up to 10,000.

The team is now exploring ways to combine their invention with other material layers to make it water-resistant and self-repairable. As you might’ve guessed, an immediate application is to give robots something similar to complex touch. A sensory upgrade not only lets robots more easily manipulate tools, doorknobs, and other objects in hectic real-world environments, it could also make it easier for machines to work collaboratively with humans in the future (hey Wall-E, care to pass the salt?).

Dexterous robots aside, the team also envisions engineering better prosthetics. When coated onto cyborg limbs, for example, ACES may give them a better sense of touch that begins to rival the human skin—or perhaps even exceed it.

Regardless, efforts that adapt the functionality of the human nervous system to machines are finally paying off, and more are sure to come. Neuromimetic ideas may very well be the link that finally closes the loop.

Image Credit: Dan Hixson/University of Utah College of Engineering.. Continue reading →

Posted in Human Robots

#435199 The Rise of AI Art—and What It Means ...

Posted on June 18, 2019 by Android

Artificially intelligent systems are slowly taking over tasks previously done by humans, and many processes involving repetitive, simple movements have already been fully automated. In the meantime, humans continue to be superior when it comes to abstract and creative tasks.

However, it seems like even when it comes to creativity, we’re now being challenged by our own creations.

In the last few years, we’ve seen the emergence of hundreds of “AI artists.” These complex algorithms are creating unique (and sometimes eerie) works of art. They’re generating stunning visuals, profound poetry, transcendent music, and even realistic movie scripts. The works of these AI artists are raising questions about the nature of art and the role of human creativity in future societies.

Here are a few works of art created by non-human entities.

Unsecured Futures
by Ai.Da

Ai-Da Robot with Painting. Image Credit: Ai-Da portraits by Nicky Johnston. Published with permission from Midas Public Relations.
Earlier this month we saw the announcement of Ai.Da, considered the first ultra-realistic drawing robot artist. Her mechanical abilities, combined with AI-based algorithms, allow her to draw, paint, and even sculpt. She is able to draw people using her artificial eye and a pencil in her hand. Ai.Da’s artwork and first solo exhibition, Unsecured Futures, will be showcased at Oxford University in July.

Ai-Da Cartesian Painting. Image Credit: Ai-Da Artworks. Published with permission from Midas Public Relations.
Obviously Ai.Da has no true consciousness, thoughts, or feelings. Despite that, the (human) organizers of the exhibition believe that Ai.Da serves as a basis for crucial conversations about the ethics of emerging technologies. The exhibition will serve as a stimulant for engaging with critical questions about what kind of future we ought to create via such technologies.

The exhibition’s creators wrote, “Humans are confident in their position as the most powerful species on the planet, but how far do we actually want to take this power? To a Brave New World (Nightmare)? And if we use new technologies to enhance the power of the few, we had better start safeguarding the future of the many.”

Google’s PoemPortraits
Our transcendence adorns,
That society of the stars seem to be the secret.

The two lines of poetry above aren’t like any poetry you’ve come across before. They are generated by an algorithm that was trained via deep learning neural networks trained on 20 million words of 19th-century poetry.

Google’s latest art project, named PoemPortraits, takes a word of your suggestion and generates a unique poem (once again, a collaboration of man and machine). You can even add a selfie in the final “PoemPortrait.” Artist Es Devlin, the project’s creator, explains that the AI “doesn’t copy or rework existing phrases, but uses its training material to build a complex statistical model. As a result, the algorithm generates original phrases emulating the style of what it’s been trained on.”

The generated poetry can sometimes be profound, and sometimes completely meaningless.But what makes the PoemPortraits project even more interesting is that it’s a collaborative project. All of the generated lines of poetry are combined to form a consistently growing collective poem, which you can view after your lines are generated. In many ways, the final collective poem is a collaboration of people from around the world working with algorithms.

Faceless Portraits Transcending Time
AICAN + Ahmed Elgammal

Image Credit: AICAN + Ahmed Elgammal | Faceless Portrait #2 (2019) | Artsy.
In March of this year, an AI artist called AICAN and its creator Ahmed Elgammal took over a New York gallery. The exhibition at HG Commentary showed two series of canvas works portraying harrowing, dream-like faceless portraits.

The exhibition was not simply credited to a machine, but rather attributed to the collaboration between a human and machine. Ahmed Elgammal is the founder and director of the Art and Artificial Intelligence Laboratory at Rutgers University. He considers AICAN to not only be an autonomous AI artist, but also a collaborator for artistic endeavors.

How did AICAN create these eerie faceless portraits? The system was presented with 100,000 photos of Western art from over five centuries, allowing it to learn the aesthetics of art via machine learning. It then drew from this historical knowledge and the mandate to create something new to create an artwork without human intervention.

Genesis
by AIVA Technologies

Listen to the score above. While you do, reflect on the fact that it was generated by an AI.

AIVA is an AI that composes soundtrack music for movies, commercials, games, and trailers. Its creative works span a wide range of emotions and moods. The scores it generates are indistinguishable from those created by the most talented human composers.

The AIVA music engine allows users to generate original scores in multiple ways. One is to upload an existing human-generated score and select the temp track to base the composition process on. Another method involves using preset algorithms to compose music in pre-defined styles, including everything from classical to Middle Eastern.

Currently, the platform is promoted as an opportunity for filmmakers and producers. But in the future, perhaps every individual will have personalized music generated for them based on their interests, tastes, and evolving moods. We already have algorithms on streaming websites recommending novel music to us based on our interests and history. Soon, algorithms may be used to generate music and other works of art that are tailored to impact our unique psyches.

The Future of Art: Pushing Our Creative Limitations
These works of art are just a glimpse into the breadth of the creative works being generated by algorithms and machines. Many of us will rightly fear these developments. We have to ask ourselves what our role will be in an era where machines are able to perform what we consider complex, abstract, creative tasks. The implications on the future of work, education, and human societies are profound.

At the same time, some of these works demonstrate that AI artists may not necessarily represent a threat to human artists, but rather an opportunity for us to push our creative boundaries. The most exciting artistic creations involve collaborations between humans and machines.

We have always used our technological scaffolding to push ourselves beyond our biological limitations. We use the telescope to extend our line of sight, planes to fly, and smartphones to connect with others. Our machines are not always working against us, but rather working as an extension of our minds. Similarly, we could use our machines to expand on our creativity and push the boundaries of art.

Image Credit: Ai-Da portraits by Nicky Johnston. Published with permission from Midas Public Relations. Continue reading →

Posted in Human Robots

#435161 Less Like Us: An Alternate Theory of ...

Posted on June 3, 2019 by Android

The question of whether an artificial general intelligence will be developed in the future—and, if so, when it might arrive—is controversial. One (very uncertain) estimate suggests 2070 might be the earliest we could expect to see such technology.

Some futurists point to Moore’s Law and the increasing capacity of machine learning algorithms to suggest that a more general breakthrough is just around the corner. Others suggest that extrapolating exponential improvements in hardware is unwise, and that creating narrow algorithms that can beat humans at specialized tasks brings us no closer to a “general intelligence.”

But evolution has produced minds like the human mind at least once. Surely we could create artificial intelligence simply by copying nature, either by guided evolution of simple algorithms or wholesale emulation of the human brain.

Both of these ideas are far easier to conceive of than they are to achieve. The 302 neurons of the nematode worm’s brain are still an extremely difficult engineering challenge, let alone the 86 billion in a human brain.

Leaving aside these caveats, though, many people are worried about artificial general intelligence. Nick Bostrom’s influential book on superintelligence imagines it will be an agent—an intelligence with a specific goal. Once such an agent reaches a human level of intelligence, it will improve itself—increasingly rapidly as it gets smarter—in pursuit of whatever goal it has, and this “recursive self-improvement” will lead it to become superintelligent.

This “intelligence explosion” could catch humans off guard. If the initial goal is poorly specified or malicious, or if improper safety features are in place, or if the AI decides it would prefer to do something else instead, humans may be unable to control our own creation. Bostrom gives examples of how a seemingly innocuous goal, such as “Make everyone happy,” could be misinterpreted; perhaps the AI decides to drug humanity into a happy stupor, or convert most of the world into computing infrastructure to pursue its goal.

Drexler and Comprehensive AI Services
These are increasingly familiar concerns for an AI that behaves like an agent, seeking to achieve its goal. There are dissenters to this picture of how artificial general intelligence might arise. One notable alternative point of view comes from Eric Drexler, famous for his work on molecular nanotechnology and Engines of Creation, the book that popularized it.

With respect to AI, Drexler believes our view of an artificial intelligence as a single “agent” that acts to maximize a specific goal is too narrow, almost anthropomorphizing AI, or modeling it as a more realistic route towards general intelligence. Instead, he proposes “Comprehensive AI Services” (CAIS) as an alternative route to artificial general intelligence.

What does this mean? Drexler’s argument is that we should look more closely at how machine learning and AI algorithms are actually being developed in the real world. The optimization effort is going into producing algorithms that can provide services and perform tasks like translation, music recommendations, classification, medical diagnoses, and so forth.

AI-driven improvements in technology, argues Drexler, will lead to a proliferation of different algorithms: technology and software improvement, which can automate increasingly more complicated tasks. Recursive improvement in this regime is already occurring—take the newer versions of AlphaGo, which can learn to improve themselves by playing against previous versions.

Many Smart Arms, No Smart Brain
Instead of relying on some unforeseen breakthrough, the CAIS model of AI just assumes that specialized, narrow AI will continue to improve at performing each of its tasks, and the range of tasks that machine learning algorithms will be able to perform will become wider. Ultimately, once a sufficient number of tasks have been automated, the services that an AI will provide will be so comprehensive that they will resemble a general intelligence.

One could then imagine a “general” intelligence as simply an algorithm that is extremely good at matching the task you ask it to perform to the specialized service algorithm that can perform that task. Rather than acting like a single brain that strives to achieve a particular goal, the central AI would be more like a search engine, looking through the tasks it can perform to find the closest match and calling upon a series of subroutines to achieve the goal.

For Drexler, this is inherently a safety feature. Rather than Bostrom’s single, impenetrable, conscious and superintelligent brain (which we must try to psychoanalyze in advance without really knowing what it will look like), we have a network of capabilities. If you don’t want your system to perform certain tasks, you can simply cut it off from access to those services. There is no superintelligent consciousness to outwit or “trap”: more like an extremely high-level programming language that can respond to complicated commands by calling upon one of the myriad specialized algorithms that have been developed by different groups.

This skirts the complex problem of consciousness and all of the sticky moral quandaries that arise in making minds that might be like ours. After all, if you could simulate a human mind, you could simulate it experiencing unimaginable pain. Black Mirror-esque dystopias where emulated minds have no rights and are regularly “erased” or forced to labor in dull and repetitive tasks, hove into view.

Drexler argues that, in this world, there is no need to ever build a conscious algorithm. Yet it seems likely that, at some point, humans will attempt to simulate our own brains, if only in the vain attempt to pursue immortality. This model cannot hold forever. Yet its proponents argue that any world in which we could develop general AI would probably also have developed superintelligent capabilities in a huge range of different tasks, such as computer programming, natural language understanding, and so on. In other words, CAIS arrives first.

The Future In Our Hands?
Drexler argues that his model already incorporates many of the ideas from general AI development. In the marketplace, algorithms compete all the time to perform these services: they undergo the same evolutionary pressures that lead to “higher intelligence,” but the behavior that’s considered superior is chosen by humans, and the nature of the “general intelligence” is far more shaped by human decision-making and human programmers. Development in AI services could still be rapid and disruptive.

But in Drexler’s case, the research and development capacity comes from humans and organizations driven by the desire to improve algorithms that are performing individualized and useful tasks, rather than from a conscious AI recursively reprogramming and improving itself.

In other words, this vision does not absolve us of the responsibility of making our AI safe; if anything, it gives us a greater degree of responsibility. As more and more complex “services” are automated, performing what used to be human jobs at superhuman speed, the economic disruption will be severe.

Equally, as machine learning is trusted to carry out more complex decisions, avoiding algorithmic bias becomes crucial. Shaping each of these individual decision-makers—and trying to predict the complex ways they might interact with each other—is no less daunting a task than specifying the goal for a hypothetical, superintelligent, God-like AI. Arguably, the consequences of the “misalignment” of these services algorithms are already multiplying around us.

The CAIS model bridges the gap between real-world AI, machine learning developments, and real-world safety considerations, as well as the speculative world of superintelligent agents and the safety considerations involved with controlling their behavior. We should keep our minds open as to what form AI and machine learning will take, and how it will influence our societies—and we must take care to ensure that the systems we create don’t end up forcing us all to live in a world of unintended consequences.

Image Credit: MF Production/Shutterstock.com Continue reading →

Posted in Human Robots

#435080 12 Ways Big Tech Can Take Big Action on ...

Posted on May 14, 2019 by Android

Bill Gates and Mark Zuckerberg have invested $1 billion in Breakthrough Energy to fund next-generation solutions to tackle climate. But there is a huge risk that any successful innovation will only reach the market as the world approaches 2030 at the earliest.

We now know that reducing the risk of dangerous climate change means halving global greenhouse gas emissions by that date—in just 11 years. Perhaps Gates, Zuckerberg, and all the tech giants should invest equally in innovations to do with how their own platforms —search, social media, eCommerce—can support societal behavior changes to drive down emissions.

After all, the tech giants influence the decisions of four billion consumers every day. It is time for a social contract between tech and society.

Recently myself and collaborator Johan Falk published a report during the World Economic Forum in Davos outlining 12 ways the tech sector can contribute to supporting societal goals to stabilize Earth’s climate.

Become genuine climate guardians

Tech giants go to great lengths to show how serious they are about reducing their emissions. But I smell cognitive dissonance. Google and Microsoft are working in partnership with oil companies to develop AI tools to help maximize oil recovery. This is not the behavior of companies working flat-out to stabilize Earth’s climate. Indeed, few major tech firms have visions that indicate a stable and resilient planet might be a good goal, yet AI alone has the potential to slash greenhouse gas emissions by four percent by 2030—equivalent to the emissions of Australia, Canada, and Japan combined.

We are now developing a playbook, which we plan to publish later this year at the UN climate summit, about making it as simple as possible for a CEO to become a climate guardian.

Hey Alexa, do you care about the stability of Earth’s climate?

Increasingly, consumers are delegating their decisions to narrow artificial intelligence like Alexa and Siri. Welcome to a world of zero-click purchases.

Should algorithms and information architecture be designed to nudge consumer behavior towards low-carbon choices, for example by making these options the default? We think so. People don’t mind being nudged; in fact, they welcome efforts to make their lives better. For instance, if I want to lose weight, I know I will need all the help I can get. Let’s ‘nudge for good’ and experiment with supporting societal goals.

Use social media for good

Facebook’s goal is to bring the world closer together. With 2.2 billion users on the platform, CEO Mark Zuckerberg can reasonably claim this goal is possible. But social media has changed the flow of information in the world, creating a lucrative industry around a toxic brown-cloud of confusion and anger, with frankly terrifying implications for democracy. This has been linked to the rise of nationalism and populism, and to the election of leaders who shun international cooperation, dismiss scientific knowledge, and reverse climate action at a moment when we need it more than ever.

Social media tools need re-engineering to help people make sense of the world, support democratic processes, and build communities around societal goals. Make this your mission.

Design for a future on Earth

Almost everything is designed with computer software, from buildings to mobile phones to consumer packaging. It is time to make zero-carbon design the new default and design products for sharing, re-use and disassembly.

The future is circular

Halving emissions in a decade will require all companies to adopt circular business models to reduce material use. Some tech companies are leading the charge. Apple has committed to becoming 100 percent circular as soon as possible. Great.

While big tech companies strive to be market leaders here, many other companies lack essential knowledge. Tech companies can support rapid adoption in different economic sectors, not least because they have the know-how to scale innovations exponentially. It makes business sense. If economies of scale drive the price of recycled steel and aluminium down, everyone wins.

Reward low-carbon consumption

eCommerce platforms can create incentives for low-carbon consumption. The world’s largest experiment in greening consumer behavior is Ant Forest, set up by Chinese fintech giant Ant Financial.

An estimated 300 million customers—similar to the population of the United States—gain points for making low-carbon choices such as walking to work, using public transport, or paying bills online. Virtual points are eventually converted into real trees. Sure, big questions remain about its true influence on emissions, but this is a space for rapid experimentation for big impact.

Make information more useful

Science is our tool for defining reality. Scientific consensus is how we attain reliable knowledge. Even after the information revolution, reliable knowledge about the world remains fragmented and unstructured. Build the next generation of search engines to genuinely make the world’s knowledge useful for supporting societal goals.

We need to put these tools towards supporting shared world views of the state of the planet based on the best science. New AI tools being developed by startups like Iris.ai can help see through the fog. From Alexa to Google Home and Siri, the future is “Voice”, but who chooses the information source? The highest bidder? Again, the implications for climate are huge.

Create new standards for digital advertising and marketing

Half of global ad revenue will soon be online, and largely going to a small handful of companies. How about creating a novel ethical standard on what is advertised and where? Companies could consider promoting sustainable choices and healthy lifestyles and limiting advertising of high-emissions products such as cheap flights.

We are what we eat

It is no secret that tech is about to disrupt grocery. The supermarkets of the future will be built on personal consumer data. With about two billion people either obese or overweight, revolutions in choice architecture could support positive diet choices, reduce meat consumption, halve food waste and, into the bargain, slash greenhouse gas emissions.

The future of transport is not cars, it’s data

The 2020s look set to be the biggest disruption of the automobile industry since Henry Ford unveiled the Model T. Two seismic shifts are on their way.

First, electric cars now compete favorably with petrol engines on range. Growth will reach an inflection point within a year or two once prices reach parity. The death of the internal combustion engine in Europe and Asia is assured with end dates announced by China, India, France, the UK, and most of Scandinavia. Dates range from 2025 (Norway) to 2040 (UK and China).

Tech giants can accelerate the demise. Uber recently announced a passenger surcharge to help London drivers save around $1,500 a year towards the cost of an electric car.

Second, driverless cars can shift the transport economic model from ownership to service and ride sharing. A complete shift away from privately-owned vehicles is around the corner, with large implications for emissions.

Clean-energy living and working

Most buildings are barely used and inefficiently heated and cooled. Digitization can slash this waste and its corresponding emissions through measurement, monitoring, and new business models to use office space. While, just a few unicorns are currently in this space, the potential is enormous. Buildings are one of the five biggest sources of emissions, yet have the potential to become clean energy producers in a distributed energy network.

Creating liveable cities

More cities are setting ambitious climate targets to halve emissions in a decade or even less. Tech companies can support this transition by driving demand for low-carbon services for their workforces and offices, but also by providing tools to help monitor emissions and act to reduce them. Google, for example, is collecting travel and other data from across cities to estimate emissions in real time. This is possible through technologies like artificial intelligence and the internet of things. But beware of smart cities that turn out to be not so smart. Efficiencies can reduce resilience when cities face crises.

It’s a Start
Of course, it will take more than tech to solve the climate crisis. But tech is a wildcard. The actions of the current tech giants and their acolytes could serve to destabilize the climate further or bring it under control.

We need a new social contract between tech companies and society to achieve societal goals. The alternative is unthinkable. Without drastic action now, climate chaos threatens to engulf us all. As this future approaches, regulators will be forced to take ever more draconian action to rein in the problem. Acting now will reduce that risk.

Note: A version of this article was originally published on World Economic Forum

Image Credit: Bruce Rolff / Shutterstock.com Continue reading →

Posted in Human Robots

#435070 5 Breakthroughs Coming Soon in Augmented ...

Posted on May 11, 2019 by Android

Convergence is accelerating disruption… everywhere! Exponential technologies are colliding into each other, reinventing products, services, and industries.

In this third installment of my Convergence Catalyzer series, I’ll be synthesizing key insights from my annual entrepreneurs’ mastermind event, Abundance 360. This five-blog series looks at 3D printing, artificial intelligence, VR/AR, energy and transportation, and blockchain.

Today, let’s dive into virtual and augmented reality.

Today’s most prominent tech giants are leaping onto the VR/AR scene, each driving forward new and upcoming product lines. Think: Microsoft’s HoloLens, Facebook’s Oculus, Amazon’s Sumerian, and Google’s Cardboard (Apple plans to release a headset by 2021).

And as plummeting prices meet exponential advancements in VR/AR hardware, this burgeoning disruptor is on its way out of the early adopters’ market and into the majority of consumers’ homes.

My good friend Philip Rosedale is my go-to expert on AR/VR and one of the foremost creators of today’s most cutting-edge virtual worlds. After creating the virtual civilization Second Life in 2013, now populated by almost 1 million active users, Philip went on to co-found High Fidelity, which explores the future of next-generation shared VR.

In just the next five years, he predicts five emerging trends will take hold, together disrupting major players and birthing new ones.

Let’s dive in…

Top 5 Predictions for VR/AR Breakthroughs (2019-2024)
“If you think you kind of understand what’s going on with that tech today, you probably don’t,” says Philip. “We’re still in the middle of landing the airplane of all these new devices.”

(1) Transition from PC-based to standalone mobile VR devices

Historically, VR devices have relied on PC connections, usually involving wires and clunky hardware that restrict a user’s field of motion. However, as VR enters the dematerialization stage, we are about to witness the rapid rise of a standalone and highly mobile VR experience economy.

Oculus Go, the leading standalone mobile VR device on the market, requires only a mobile app for setup and can be transported anywhere with WiFi.

With a consumer audience in mind, the 32GB headset is priced at $200 and shares an app ecosystem with Samsung’s Gear VR. While Google Daydream are also standalone VR devices, they require a docked mobile phone instead of the built-in screen of Oculus Go.

In the AR space, Lenovo’s standalone Microsoft’s HoloLens 2 leads the way in providing tetherless experiences.

Freeing headsets from the constraints of heavy hardware will make VR/AR increasingly interactive and transportable, a seamless add-on whenever, wherever. Within a matter of years, it may be as simple as carrying lightweight VR goggles wherever you go and throwing them on at a moment’s notice.

(2) Wide field-of-view AR displays

Microsoft’s HoloLens 2 leads the AR industry in headset comfort and display quality. The most significant issue with their prior version was the limited rectangular field of view (FOV).

By implementing laser technology to create a microelectromechanical systems (MEMS) display, however, HoloLens 2 can position waveguides in front of users’ eyes, directed by mirrors. Subsequently enlarging images can be accomplished by shifting the angles of these mirrors. Coupled with a 47 pixel per degree resolution, HoloLens 2 has now doubled its predecessor’s FOV. Microsoft anticipates the release of its headset by the end of this year at a $3,500 price point, first targeting businesses and eventually rolling it out to consumers.

Magic Leap provides a similar FOV but with lower resolution than the HoloLens 2. The Meta 2 boasts an even wider 90-degree FOV, but requires a cable attachment. The race to achieve the natural human 120-degree horizontal FOV continues.

“The technology to expand the field of view is going to make those devices much more usable by giving you bigger than a small box to look through,” Rosedale explains.

(3) Mapping of real world to enable persistent AR ‘mirror worlds’

‘Mirror worlds’ are alternative dimensions of reality that can blanket a physical space. While seated in your office, the floor beneath you could dissolve into a calm lake and each desk into a sailboat. In the classroom, mirror worlds would convert pencils into magic wands and tabletops into touch screens.

Pokémon Go provides an introductory glimpse into the mirror world concept and its massive potential to unite people in real action.

To create these mirror worlds, AR headsets must precisely understand the architecture of the surrounding world. Rosedale predicts the scanning accuracy of devices will improve rapidly over the next five years to make these alternate dimensions possible.

(4) 5G mobile devices reduce latency to imperceptible levels

Verizon has already launched 5G networks in Minneapolis and Chicago, compatible with the Moto Z3. Sprint plans to follow with its own 5G launch in May. Samsung, LG, Huawei, and ZTE have all announced upcoming 5G devices.

“5G is rolling out this year and it’s going to materially affect particularly my work, which is making you feel like you’re talking to somebody else directly face to face,” explains Rosedale. “5G is critical because currently the cell devices impose too much delay, so it doesn’t feel real to talk to somebody face to face on these devices.”

To operate seamlessly from anywhere on the planet, standalone VR/AR devices will require a strong 5G network. Enhancing real-time connectivity in VR/AR will transform the communication methods of tomorrow.

(5) Eye-tracking and facial expressions built in for full natural communication

Companies like Pupil Labs and Tobii provide eye tracking hardware add-ons and software to VR/AR headsets. This technology allows for foveated rendering, which renders a given scene in high resolution only in the fovea region, while the peripheral regions appear in lower resolution, conserving processing power.

As seen in the HoloLens 2, eye tracking can also be used to identify users and customize lens widths to provide a comfortable, personalized experience for each individual.

According to Rosedale, “The fundamental opportunity for both VR and AR is to improve human communication.” He points out that current VR/AR headsets miss many of the subtle yet important aspects of communication. Eye movements and microexpressions provide valuable insight into a user’s emotions and desires.

Coupled with emotion-detecting AI software, such as Affectiva, VR/AR devices might soon convey much more richly textured and expressive interactions between any two people, transcending physical boundaries and even language gaps.

Final Thoughts
As these promising trends begin to transform the market, VR/AR will undoubtedly revolutionize our lives… possibly to the point at which our virtual worlds become just as consequential and enriching as our physical world.

A boon for next-gen education, VR/AR will empower youth and adults alike with holistic learning that incorporates social, emotional, and creative components through visceral experiences, storytelling, and simulation. Traveling to another time, manipulating the insides of a cell, or even designing a new city will become daily phenomena of tomorrow’s classrooms.

In real estate, buyers will increasingly make decisions through virtual tours. Corporate offices might evolve into spaces that only exist in ‘mirror worlds’ or grow virtual duplicates for remote workers.

In healthcare, accuracy of diagnosis will skyrocket, while surgeons gain access to digital aids as they conduct life-saving procedures. Or take manufacturing, wherein training and assembly will become exponentially more efficient as visual cues guide complex tasks.

In the mere matter of a decade, VR and AR will unlock limitless applications for new and converging industries. And as virtual worlds converge with AI, 3D printing, computing advancements and beyond, today’s experience economies will explode in scale and scope. Prepare yourself for the exciting disruption ahead!

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