Tag Archives: technology

#431866 The Technologies We’ll Have Our Eyes ...

It’s that time of year again when our team has a little fun and throws on our futurist glasses to look ahead at some of the technologies and trends we’re most anticipating next year.
Whether the implications of a technology are vast or it resonates with one of us personally, here’s the list from some of the Singularity Hub team of what we have our eyes on as we enter the new year.
For a little refresher, these were the technologies our team was fired up about at the start of 2017.
Tweet us the technology you’re excited to watch in 2018 at @SingularityHub.
Cryptocurrency and Blockchain
“Given all the noise Bitcoin is making globally in the media, it is driving droves of main street investors to dabble in and learn more about cryptocurrencies. This will continue to raise valuations and drive adoption of blockchain. From Bank of America recently getting a blockchain-based patent approved to the Australian Securities Exchange’s plan to use blockchain, next year is going to be chock-full of these stories. Coindesk even recently spotted a patent filing from Apple involving blockchain. From ‘China’s Ethereum’, NEO, to IOTA to Golem to Qtum, there are a lot of interesting cryptos to follow given the immense numbers of potential applications. Hang on, it’s going to be a bumpy ride in 2018!”
–Kirk Nankivell, Website Manager
There Is No One Technology to Watch
“Next year may be remembered for advances in gene editing, blockchain, AI—or most likely all these and more. There is no single technology to watch. A number of consequential trends are advancing and converging. This general pace of change is exciting, and it also contributes to spiking anxiety. Technology’s invisible lines of force are extending further and faster into our lives and subtly subverting how we view the world and each other in unanticipated ways. Still, all the near-term messiness and volatility, the little and not-so-little dramas, the hype and disillusion, the controversies and conflict, all that smooths out a bit when you take a deep breath and a step back, and it’s my sincere hope and belief the net result will be more beneficial than harmful.”
–Jason Dorrier, Managing Editor
‘Fake News’ Fighting Technology
“It’s been a wild ride for the media this year with the term ‘fake news’ moving from the public’s peripheral and into mainstream vocabulary. The spread of ‘fake news’ is often blamed on media outlets, but social media platforms and search engines are often responsible too. (Facebook still won’t identify as a media company—maybe next year?) Yes, technology can contribute to spreading false information, but it can also help stop it. From technologists who are building in-article ‘trust indicator’ features, to artificial intelligence systems that can both spot and shut down fake news early on, I’m hopeful we can create new solutions to this huge problem. One step further: if publishers step up to fix this we might see some faith restored in the media.”
–Alison E. Berman, Digital Producer
Pay-as-You-Go Home Solar Power
“People in rural African communities are increasingly bypassing electrical grids (which aren’t even an option in many cases) and installing pay-as-you-go solar panels on their homes. The companies offering these services are currently not subject to any regulations, though they’re essentially acting as a utility. As demand for power grows, they’ll have to come up with ways to efficiently scale, and to balance the humanitarian and capitalistic aspects of their work. It’s fascinating to think traditional grids may never be necessary in many areas of the continent thanks to this technology.”
–Vanessa Bates Ramirez, Associate Editor
Virtual Personal Assistants
“AI is clearly going to rule our lives, and in many ways it already makes us look like clumsy apes. Alexa, Siri, and Google Assistant are promising first steps toward a world of computers that understand us and relate to us on an emotional level. I crave the day when my Apple Watch coaches me into healthier habits, lets me know about new concerts nearby, speaks to my self-driving Lyft on my behalf, and can help me respond effectively to aggravating emails based on communication patterns. But let’s not brush aside privacy concerns and the implications of handing over our personal data to megacorporations. The scariest thing here is that privacy laws and advertising ethics do not accommodate this level of intrusive data hoarding.”
–Matthew Straub, Director of Digital Engagement (Hub social media)
Solve for Learning: Educational Apps for Children in Conflict Zones
“I am most excited by exponential technology when it is used to help solve a global grand challenge. Educational apps are currently being developed to help solve for learning by increasing accessibility to learning opportunities for children living in conflict zones. Many children in these areas are not receiving an education, with girls being 2.5 times more likely than boys to be out of school. The EduApp4Syria project is developing apps to help children in Syria and Kashmir learn in their native languages. Mobile phones are increasingly available in these areas, and the apps are available offline for children who do not have consistent access to mobile networks. The apps are low-cost, easily accessible, and scalable educational opportunities.
–Paige Wilcoxson, Director, Curriculum & Learning Design
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#431859 Digitized to Democratized: These Are the ...

“The Six Ds are a chain reaction of technological progression, a road map of rapid development that always leads to enormous upheaval and opportunity.”
–Peter Diamandis and Steven Kotler, Bold
We live in incredible times. News travels the globe in an instant. Music, movies, games, communication, and knowledge are ever-available on always-connected devices. From biotechnology to artificial intelligence, powerful technologies that were once only available to huge organizations and governments are becoming more accessible and affordable thanks to digitization.
The potential for entrepreneurs to disrupt industries and corporate behemoths to unexpectedly go extinct has never been greater.
One hundred or fifty or even twenty years ago, disruption meant coming up with a product or service people needed but didn’t have yet, then finding a way to produce it with higher quality and lower costs than your competitors. This entailed hiring hundreds or thousands of employees, having a large physical space to put them in, and waiting years or even decades for hard work to pay off and products to come to fruition.

“Technology is disrupting traditional industrial processes, and they’re never going back.”

But thanks to digital technologies developing at exponential rates of change, the landscape of 21st-century business has taken on a dramatically different look and feel.
The structure of organizations is changing. Instead of thousands of employees and large physical plants, modern start-ups are small organizations focused on information technologies. They dematerialize what was once physical and create new products and revenue streams in months, sometimes weeks.
It no longer takes a huge corporation to have a huge impact.
Technology is disrupting traditional industrial processes, and they’re never going back. This disruption is filled with opportunity for forward-thinking entrepreneurs.
The secret to positively impacting the lives of millions of people is understanding and internalizing the growth cycle of digital technologies. This growth cycle takes place in six key steps, which Peter Diamandis calls the Six Ds of Exponentials: digitization, deception, disruption, demonetization, dematerialization, and democratization.
According to Diamandis, cofounder and chairman of Singularity University and founder and executive chairman of XPRIZE, when something is digitized it begins to behave like an information technology.

Newly digitized products develop at an exponential pace instead of a linear one, fooling onlookers at first before going on to disrupt companies and whole industries. Before you know it, something that was once expensive and physical is an app that costs a buck.
Newspapers and CDs are two obvious recent examples. The entertainment and media industries are still dealing with the aftermath of digitization as they attempt to transform and update old practices tailored to a bygone era. But it won’t end with digital media. As more of the economy is digitized—from medicine to manufacturing—industries will hop on an exponential curve and be similarly disrupted.
Diamandis’s 6 Ds are critical to understanding and planning for this disruption.
The 6 Ds of Exponential Organizations are Digitized, Deceptive, Disruptive, Demonetized, Dematerialized, and Democratized.

Diamandis uses the contrasting fates of Kodak and Instagram to illustrate the power of the six Ds and exponential thinking.
Kodak invented the digital camera in 1975, but didn’t invest heavily in the new technology, instead sticking with what had always worked: traditional cameras and film. In 1996, Kodak had a $28 billion market capitalization with 95,000 employees.
But the company didn’t pay enough attention to how digitization of their core business was changing it; people were no longer taking pictures in the same way and for the same reasons as before.
After a downward spiral, Kodak went bankrupt in 2012. That same year, Facebook acquired Instagram, a digital photo sharing app, which at the time was a startup with 13 employees. The acquisition’s price tag? $1 billion. And Instagram had been founded only 18 months earlier.
The most ironic piece of this story is that Kodak invented the digital camera; they took the first step toward overhauling the photography industry and ushering it into the modern age, but they were unwilling to disrupt their existing business by taking a risk in what was then uncharted territory. So others did it instead.
The same can happen with any technology that’s just getting off the ground. It’s easy to stop pursuing it in the early part of the exponential curve, when development appears to be moving slowly. But failing to follow through only gives someone else the chance to do it instead.
The Six Ds are a road map showing what can happen when an exponential technology is born. Not every phase is easy, but the results give even small teams the power to change the world in a faster and more impactful way than traditional business ever could.
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#431828 This Self-Driving AI Is Learning to ...

I don’t have to open the doors of AImotive’s white 2015 Prius to see that it’s not your average car. This particular Prius has been christened El Capitan, the name written below the rear doors, and two small cameras are mounted on top of the car. Bundles of wire snake out from them, as well as from the two additional cameras on the car’s hood and trunk.
Inside is where things really get interesting, though. The trunk holds a computer the size of a microwave, and a large monitor covers the passenger glove compartment and dashboard. The center console has three switches labeled “Allowed,” “Error,” and “Active.”
Budapest-based AImotive is working to provide scalable self-driving technology alongside big players like Waymo and Uber in the autonomous vehicle world. On a highway test ride with CEO Laszlo Kishonti near the company’s office in Mountain View, California, I got a glimpse of just how complex that world is.
Camera-Based Feedback System
AImotive’s approach to autonomous driving is a little different from that of some of the best-known systems. For starters, they’re using cameras, not lidar, as primary sensors. “The traffic system is visual and the cost of cameras is low,” Kishonti said. “A lidar can recognize when there are people near the car, but a camera can differentiate between, say, an elderly person and a child. Lidar’s resolution isn’t high enough to recognize the subtle differences of urban driving.”
Image Credit: AImotive
The company’s aiDrive software uses data from the camera sensors to feed information to its algorithms for hierarchical decision-making, grouped under four concurrent activities: recognition, location, motion, and control.
Kishonti pointed out that lidar has already gotten more cost-efficient, and will only continue to do so.
“Ten years ago, lidar was best because there wasn’t enough processing power to do all the calculations by AI. But the cost of running AI is decreasing,” he said. “In our approach, computer vision and AI processing are key, and for safety, we’ll have fallback sensors like radar or lidar.”
aiDrive currently runs on Nvidia chips, which Kishonti noted were originally designed for graphics, and are not terribly efficient given how power-hungry they are. “We’re planning to substitute lower-cost, lower-energy chips in the next six months,” he said.
Testing in Virtual Reality
Waymo recently announced its fleet has now driven four million miles autonomously. That’s a lot of miles, and hard to compete with. But AImotive isn’t trying to compete, at least not by logging more real-life test miles. Instead, the company is doing 90 percent of its testing in virtual reality. “This is what truly differentiates us from competitors,” Kishonti said.
He outlined the three main benefits of VR testing: it can simulate scenarios too dangerous for the real world (such as hitting something), too costly (not every company has Waymo’s funds to run hundreds of cars on real roads), or too time-consuming (like waiting for rain, snow, or other weather conditions to occur naturally and repeatedly).
“Real-world traffic testing is very skewed towards the boring miles,” he said. “What we want to do is test all the cases that are hard to solve.”
On a screen that looked not unlike multiple games of Mario Kart, he showed me the simulator. Cartoon cars cruised down winding streets, outfitted with all the real-world surroundings: people, trees, signs, other cars. As I watched, a furry kangaroo suddenly hopped across one screen. “Volvo had an issue in Australia,” Kishonti explained. “A kangaroo’s movement is different than other animals since it hops instead of running.” Talk about cases that are hard to solve.
AImotive is currently testing around 1,000 simulated scenarios every night, with a steadily-rising curve of successful tests. These scenarios are broken down into features, and the car’s behavior around those features fed into a neural network. As the algorithms learn more features, the level of complexity the vehicles can handle goes up.
On the Road
After Kishonti and his colleagues filled me in on the details of their product, it was time to test it out. A safety driver sat in the driver’s seat, a computer operator in the passenger seat, and Kishonti and I in back. The driver maintained full control of the car until we merged onto the highway. Then he flicked the “Allowed” switch, his copilot pressed the “Active” switch, and he took his hands off the wheel.
What happened next, you ask?
A few things. El Capitan was going exactly the speed limit—65 miles per hour—which meant all the other cars were passing us. When a car merged in front of us or cut us off, El Cap braked accordingly (if a little abruptly). The monitor displayed the feed from each of the car’s cameras, plus multiple data fields and a simulation where a blue line marked the center of the lane, measured by the cameras tracking the lane markings on either side.
I noticed El Cap wobbling out of our lane a bit, but it wasn’t until two things happened in a row that I felt a little nervous: first we went under a bridge, then a truck pulled up next to us, both bridge and truck casting a complete shadow over our car. At that point El Cap lost it, and we swerved haphazardly to the right, narrowly missing the truck’s rear wheels. The safety driver grabbed the steering wheel and took back control of the car.
What happened, Kishonti explained, was that the shadows made it hard for the car’s cameras to see the lane markings. This was a new scenario the algorithm hadn’t previously encountered. If we’d only gone under a bridge or only been next to the truck for a second, El Cap may not have had so much trouble, but the two events happening in a row really threw the car for a loop—almost literally.
“This is a new scenario we’ll add to our testing,” Kishonti said. He added that another way for the algorithm to handle this type of scenario, rather than basing its speed and positioning on the lane markings, is to mimic nearby cars. “The human eye would see that other cars are still moving at the same speed, even if it can’t see details of the road,” he said.
After another brief—and thankfully uneventful—hands-off cruise down the highway, the safety driver took over, exited the highway, and drove us back to the office.
Driving into the Future
I climbed out of the car feeling amazed not only that self-driving cars are possible, but that driving is possible at all. I squint when driving into a tunnel, swerve to avoid hitting a stray squirrel, and brake gradually at stop signs—all without consciously thinking to do so. On top of learning to steer, brake, and accelerate, self-driving software has to incorporate our brains’ and bodies’ unconscious (but crucial) reactions, like our pupils dilating to let in more light so we can see in a tunnel.
Despite all the progress of machine learning, artificial intelligence, and computing power, I have a wholly renewed appreciation for the thing that’s been in charge of driving up till now: the human brain.
Kishonti seemed to feel similarly. “I don’t think autonomous vehicles in the near future will be better than the best drivers,” he said. “But they’ll be better than the average driver. What we want to achieve is safe, good-quality driving for everyone, with scalability.”
AImotive is currently working with American tech firms and with car and truck manufacturers in Europe, China, and Japan.
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#431827 How Technology Disrupts and Drives The ...

Photo credit Technology sets us apart and puts us at the forefront, and one industry that is definitely embracing automation and robotics readily is the motor industry. Technology has touched every aspect of motoring – from updates to the manufacturing process that produce much safer and more reliable vehicles to black box diagnostics being used …
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#431806 Robotics researchers track autonomous ...

QUT robotics researchers have developed new technology to equip underground mining vehicles to navigate autonomously through dust, camera blur and bad lighting. Continue reading

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