Tag Archives: china

#432009 How Swarm Intelligence Is Making Simple ...

As a group, simple creatures following simple rules can display a surprising amount of complexity, efficiency, and even creativity. Known as swarm intelligence, this trait is found throughout nature, but researchers have recently begun using it to transform various fields such as robotics, data mining, medicine, and blockchains.

Ants, for example, can only perform a limited range of functions, but an ant colony can build bridges, create superhighways of food and information, wage war, and enslave other ant species—all of which are beyond the comprehension of any single ant. Likewise, schools of fish, flocks of birds, beehives, and other species exhibit behavior indicative of planning by a higher intelligence that doesn’t actually exist.

It happens by a process called stigmergy. Simply put, a small change by a group member causes other members to behave differently, leading to a new pattern of behavior.

When an ant finds a food source, it marks the path with pheromones. This attracts other ants to that path, leads them to the food source, and prompts them to mark the same path with more pheromones. Over time, the most efficient route will become the superhighway, as the faster and easier a path is, the more ants will reach the food and the more pheromones will be on the path. Thus, it looks as if a more intelligent being chose the best path, but it emerged from the tiny, simple changes made by individuals.

So what does this mean for humans? Well, a lot. In the past few decades, researchers have developed numerous algorithms and metaheuristics, such as ant colony optimization and particle swarm optimization, and they are rapidly being adopted.

Swarm Robotics
A swarm of robots would work on the same principles as an ant colony: each member has a simple set of rules to follow, leading to self-organization and self-sufficiency.

For example, researchers at Georgia Robotics and InTelligent Systems (GRITS) created a small swarm of simple robots that can spell and play piano. The robots cannot communicate, but based solely on the position of surrounding robots, they are able to use their specially-created algorithm to determine the optimal path to complete their task.

This is also immensely useful for drone swarms.

Last February, Ehang, an aviation company out of China, created a swarm of a thousand drones that not only lit the sky with colorful, intricate displays, but demonstrated the ability to improvise and troubleshoot errors entirely autonomously.

Further, just recently, the University of Cambridge and Koc University unveiled their idea for what they call the Energy Neutral Internet of Drones. Amazingly, this drone swarm would take initiative to share information or energy with other drones that did not receive a communication or are running low on energy.

Militaries all of the world are utilizing this as well.

Last year, the US Department of Defense announced it had successfully tested a swarm of miniature drones that could carry out complex missions cheaper and more efficiently. They claimed, “The micro-drones demonstrated advanced swarm behaviors such as collective decision-making, adaptive formation flying, and self-healing.”

Some experts estimate at least 30 nations are actively developing drone swarms—and even submersible drones—for military missions, including intelligence gathering, missile defense, precision missile strikes, and enhanced communication.

NASA also plans on deploying swarms of tiny spacecraft for space exploration, and the medical community is looking into using swarms of nanobots for precision delivery of drugs, microsurgery, targeting toxins, and biological sensors.

What If Humans Are the Ants?
The strength of any blockchain comes from the size and diversity of the community supporting it. Cryptocurrencies like Bitcoin, Ethereum, and Litecoin are driven by the people using, investing in, and, most importantly, mining them so their blockchains can function. Without an active community, or swarm, their blockchains wither away.

When viewed from a great height, a blockchain performs eerily like an ant colony in that it will naturally find the most efficient way to move vast amounts of information.

Miners compete with each other to perform the complex calculations necessary to add another block, for which the winner is rewarded with the blockchain’s native currency and agreed-upon fees. Of course, the miner with the more powerful computers is more likely to win the reward, thereby empowering the winner’s ability to mine and receive even more rewards. Over time, fewer and fewer miners are going to exist, as the winners are able to more efficiently shoulder more of the workload, in much the same way that ants build superhighways.

Further, a company called Unanimous AI has developed algorithms that allow humans to collectively make predictions. So far, the AI algorithms and their human participants have made some astoundingly accurate predictions, such as the first four winning horses of the Kentucky Derby, the Oscar winners, the Stanley Cup winners, and others. The more people involved in the swarm, the greater their predictive power will be.

To be clear, this is not a prediction based on group consensus. Rather, the swarm of humans uses software to input their opinions in real time, thus making micro-changes to the rest of the swarm and the inputs of other members.

Studies show that swarm intelligence consistently outperforms individuals and crowds working without the algorithms. While this is only the tip of the iceberg, some have suggested swarm intelligence can revolutionize how doctors diagnose a patient or how products are marketed to consumers. It might even be an essential step in truly creating AI.

While swarm intelligence is an essential part of many species’ success, it’s only a matter of time before humans harness its effectiveness as well.

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#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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#431862 Want Self-Healing Robots and Tires? ...

We all have scars, and each one tells a story. Tales of tomfoolery, tales of haphazardness, or in my case, tales of stupidity.
Whether the cause of your scar was a push-bike accident, a lack of concentration while cutting onions, or simply the byproduct of an active lifestyle, the experience was likely extremely painful and distressing. Not to mention the long and vexatious recovery period, stretching out for weeks and months after the actual event!
Cast your minds back to that time. How you longed for instant relief from your discomfort! How you longed to have your capabilities restored in an instant!
Well, materials that can heal themselves in an instant may not be far from becoming a reality—and a family of them known as elastomers holds the key.
“Elastomer” is essentially a big, fancy word for rubber. However, elastomers have one unique property—they are capable of returning to their original form after being vigorously stretched and deformed.
This unique property of elastomers has caught the eye of many scientists around the world, particularly those working in the field of robotics. The reason? Elastomer can be encouraged to return to its original shape, in many cases by simply applying heat. The implication of this is the quick and cost-effective repair of “wounds”—cuts, tears, and punctures to the soft, elastomer-based appendages of a robot’s exoskeleton.

Researchers from Vrije University in Brussels, Belgium have been toying with the technique, and with remarkable success. The team built a robotic hand with fingers made of a type of elastomer. They found that cuts and punctures were indeed able to repair themselves simply by applying heat to the affected area.
How long does the healing process take? In this instance, about a day. Now that’s a lot shorter than the weeks and months of recovery time we typically need for a flesh wound, during which we are unable to write, play the guitar, or do the dishes. If you consider the latter to be a bad thing…
However, it’s not the first time scientists have played around with elastomers and examined their self-healing properties. Another team of scientists, headed up by Cheng-Hui Li and Chao Wang, discovered another type of elastomer that exhibited autonomous self-healing properties. Just to help you picture this stuff, the material closely resembles animal muscle— strong, flexible, and elastic. With autogenetic restorative powers to boot.
Advancements in the world of self-healing elastomers, or rubbers, may also affect the lives of everyday motorists. Researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a self-healing rubber material that could be used to make tires that repair their own punctures.
This time the mechanism of self-healing doesn’t involve heat. Rather, it is related to a physical phenomenon associated with the rubber’s unique structure. Normally, when a large enough stress is applied to a typical rubber, there is catastrophic failure at the focal point of that stress. The self-healing rubber the researchers created, on the other hand, distributes that same stress evenly over a network of “crazes”—which are like cracks connected by strands of fiber.
Here’s the interesting part. Not only does this unique physical characteristic of the rubber prevent catastrophic failure, it facilitates self-repair. According to Harvard researchers, when the stress is released, the material snaps back to its original form and the crazes heal.
This wonder material could be used in any number of rubber-based products.
Professor Jinrong Wu, of Sichuan University, China, and co-author of the study, happened to single out tires: “Imagine that we could use this material as one of the components to make a rubber tire… If you have a cut through the tire, this tire wouldn’t have to be replaced right away. Instead, it would self-heal while driving, enough to give you leeway to avoid dramatic damage,” said Wu.
So where to from here? Well, self-healing elastomers could have a number of different applications. According to the article published by Quartz, cited earlier, the material could be used on artificial limbs. Perhaps it will provide some measure of structural integrity without looking like a tattered mess after years of regular use.
Or perhaps a sort of elastomer-based hybrid skin is on the horizon. A skin in which wounds heal instantly. And recovery time, unlike your regular old human skin of yesteryear, is significantly slashed. Furthermore, this future skin might eliminate those little reminders we call scars.
For those with poor judgment skills, this spells an end to disquieting reminders of our own stupidity.
Image Credit: Vrije Universiteit Brussel / Prof. Dr. ir. Bram Vanderborght Continue reading

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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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#431543 China Is an Entrepreneurial Hotbed That ...

Last week, Eric Schmidt, chairman of Alphabet, predicted that China will rapidly overtake the US in artificial intelligence…in as little as five years.
Last month, China announced plans to open a $10 billion quantum computing research center in 2020.
Bottom line, China is aggressively investing in exponential technologies, pursuing a bold goal of becoming the global AI superpower by 2030.
Based on what I’ve observed from China’s entrepreneurial scene, I believe they have a real shot of hitting that goal.
As I described in a previous tech blog, I recently traveled to China with a group of my Abundance 360 members, where I was hosted by my friend Kai-Fu Lee, the founder, chairman, and CEO of Sinovation Ventures.
On one of our first nights, Kai-Fu invited us to a special dinner at Da Dong Roast, which specializes in Peking duck, where we shared an 18-course meal.
The meal was amazing, and Kai-Fu’s dinner conversation provided us priceless insights on Chinese entrepreneurs.
Three topics opened my eyes. Here’s the wisdom I’d like to share with you.
1. The Entrepreneurial Culture in China
Chinese entrepreneurship has exploded onto the scene and changed significantly over the past 10 years.
In my opinion, one significant way that Chinese entrepreneurs vary from their American counterparts is in work ethic. The mantra I found in the startups I visited in Beijing and Shanghai was “9-9-6”—meaning the employees only needed to work from 9 am to 9 pm, 6 days a week.
Another concept Kai-Fu shared over dinner was the almost ‘dictatorial’ leadership of the founder/CEO. In China, it’s not uncommon for the Founder/CEO to own the majority of the company, or at least 30–40 percent. It’s also the case that what the CEO says is gospel. Period, no debate. There is no minority or dissenting opinion. When the CEO says “march,” the company asks, “which way?”
When Kai-Fu started Sinovation (his $1 billion+ venture fund), there were few active angel investors. Today, China has a rich ecosystem of angel, venture capital, and government-funded innovation parks.
As venture capital in China has evolved, so too has the mindset of the entrepreneur.
Kai -Fu recalled an early investment he made in which, after an unfortunate streak, the entrepreneur came to him, almost in tears, apologizing for losing his money and promising he would earn it back for him in another way. Kai-Fu comforted the entrepreneur and said there was no such need.
Only a few years later, the situation was vastly different. An entrepreneur who was going through a similar unfortunate streak came to Kai Fu and told him he only had $2 million left of his initial $12 million investment. He informed him he saw no value in returning the money and instead was going to take the last $2 million and use it as a final push to see if the company could succeed. He then promised Kai-Fu if he failed, he would remember what Kai-Fu did for him and, as such, possibly give Sinovation an opportunity to invest in him with his next company.
2. Chinese Companies Are No Longer Just ‘Copycats’
During dinner, Kai-Fu lamented that 10 years ago, it would be fair to call Chinese companies copycats of American companies. Five years ago, the claim would be controversial. Today, however, Kai-Fu is clear that claim is entirely false.
While smart Chinese startups will still look at what American companies are doing and build on trends, today it’s becoming a wise business practice for American tech giants to analyze Chinese companies. If you look at many new features of Facebook’s Messenger, it seems to very closely mirror TenCent’s WeChat.
Interestingly, tight government controls in China have actually spurred innovation. Take TV, for example, a highly regulated industry. Because of this regulation, most entertainment in China is consumed on the internet or by phone. Game shows, reality shows, and more will be entirely centered online.
Kai-Fu told us about one of his investments in a company that helps create Chinese singing sensations. They take girls in from a young age, school them, and regardless of talent, help build their presence and brand as singers. Once ready, these singers are pushed across all the available platforms, and superstars are born. The company recognizes its role in this superstar status, though, which is why it takes a 50 percent cut of all earnings.
This company is just one example of how Chinese entrepreneurs take advantage of China’s unique position, market, and culture.
3. China’s Artificial Intelligence Play
Kai-Fu wrapped up his talk with a brief introduction into the expansive AI industry in China. I previously discussed Face++, a Sinovation investment, which is creating radically efficient facial recognition technology. Face++ is light years ahead of anyone else globally at recognition in live videos. However, Face++ is just one of the incredible advances in AI coming out of China.
Baidu, one of China’s most valuable tech companies, started out as just a search company. However, they now run one of the country’s leading self-driving car programs.
Baidu’s goal is to create a software suite atop existing hardware that will control all self-driving aspects of a vehicle but also be able to provide additional services such as HD mapping and more.
Another interesting application came from another of Sinovation’s investments, Smart Finance Group (SFG). Given most payments are mobile (through WeChat or Alipay), only ~20 percent of the population in China have a credit history. This makes it very difficult for individuals in China to acquire a loan.
SFG’s mobile application takes in user data (as much as the user allows) and, based on the information provided, uses an AI agent to create a financial profile with the power to offer an instant loan. This loan can be deposited directly into their WeChat or Alipay account and is typically approved in minutes. Unlike American loan companies, they avoid default and long-term debt by only providing a one-month loan with 10% interest. Borrow $200, and you pay back $220 by the following month.
Artificial intelligence is exploding in China, and Kai-Fu believes it will touch every single industry.
The only constant is change, and the rate of change is constantly increasing.
In the next 10 years, we’ll see tremendous changes on the geopolitical front and the global entrepreneurial scene caused by technological empowerment.
China is an entrepreneurial hotbed that cannot be ignored. I’m monitoring it closely. Are you?
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