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#433655 First-Ever Grad Program in Space Mining ...

Posted on September 27, 2018 by Android

Maybe they could call it the School of Space Rock: A new program being offered at the Colorado School of Mines (CSM) will educate post-graduate students on the nuts and bolts of extracting and using valuable materials such as rare metals and frozen water from space rocks like asteroids or the moon.

Officially called Space Resources, the graduate-level program is reputedly the first of its kind in the world to offer a course in the emerging field of space mining. Heading the program is Angel Abbud-Madrid, director of the Center for Space Resources at Mines, a well-known engineering school located in Golden, Colorado, where Molson Coors taps Rocky Mountain spring water for its earthly brews.

The first semester for the new discipline began last month. While Abbud-Madrid didn’t immediately respond to an interview request, Singularity Hub did talk to Chris Lewicki, president and CEO of Planetary Resources, a space mining company whose founders include Peter Diamandis, Singularity University co-founder.

A former NASA engineer who worked on multiple Mars missions, Lewicki says the Space Resources program at CSM, with its multidisciplinary focus on science, economics, and policy, will help students be light years ahead of their peers in the nascent field of space mining.

“I think it’s very significant that they’ve started this program,” he said. “Having students with that kind of background exposure just allows them to be productive on day one instead of having to kind of fill in a lot of things for them.”

Who would be attracted to apply for such a program? There are many professionals who could be served by a post-baccalaureate certificate, master’s degree, or even Ph.D. in Space Resources, according to Lewicki. Certainly aerospace engineers and planetary scientists would be among the faces in the classroom.

“I think it’s [also] people who have an interest in what I would call maybe space robotics,” he said. Lewicki is referring not only to the classic example of robotic arms like the Canadarm2, which lends a hand to astronauts aboard the International Space Station, but other types of autonomous platforms.

One example might be Planetary Resources’ own Arkyd-6, a small, autonomous satellite called a CubeSat launched earlier this year to test different technologies that might be used for deep-space exploration of resources. The proof-of-concept was as much a test for the technology—such as the first space-based use of a mid-wave infrared imager to detect water resources—as it was for being able to work in space on a shoestring budget.

“We really proved that doing one of these billion-dollar science missions to deep space can be done for a lot less if you have a very focused goal, and if you kind of cut a lot of corners and then put some commercial approaches into those things,” Lewicki said.

A Trillion-Dollar Industry
Why space mining? There are at least a trillion reasons.

Astrophysicist Neil deGrasse Tyson famously said that the first trillionaire will be the “person who exploits the natural resources on asteroids.” That’s because asteroids—rocky remnants from the formation of our solar system more than four billion years ago—harbor precious metals, ranging from platinum and gold to iron and nickel.

For instance, one future target of exploration by NASA—an asteroid dubbed 16 Psyche, orbiting the sun in the asteroid belt between Mars and Jupiter—is worth an estimated $10,000 quadrillion. It’s a number so mind-bogglingly big that it would crash the global economy, if someone ever figured out how to tow it back to Earth without literally crashing it into the planet.

Living Off the Land
Space mining isn’t just about getting rich. Many argue that humanity’s ability to extract resources in space, especially water that can be refined into rocket fuel, will be a key technology to extend our reach beyond near-Earth space.

The presence of frozen water around the frigid polar regions of the moon, for example, represents an invaluable source to power future deep-space missions. Splitting H20 into its component elements of hydrogen and oxygen would provide a nearly inexhaustible source of rocket fuel. Today, it costs $10,000 to put a pound of payload in Earth orbit, according to NASA.

Until more advanced rocket technology is developed, the moon looks to be the best bet for serving as the launching pad to Mars and beyond.

Moon Versus Asteroid
However, Lewicki notes that despite the moon’s proximity and our more intimate familiarity with its pockmarked surface, that doesn’t mean a lunar mission to extract resources is any easier than a multi-year journey to a fast-moving asteroid.

For one thing, fighting gravity to and from the moon is no easy feat, as the moon has a significantly stronger gravitational field than an asteroid. Another challenge is that the frozen water is located in permanently shadowed lunar craters, meaning space miners can’t rely on solar-powered equipment, but on some sort of external energy source.

And then there’s the fact that moon craters might just be the coldest places in the solar system. NASA’s Lunar Reconnaissance Orbiter found temperatures plummeted as low as 26 Kelvin, or more than minus 400 degrees Fahrenheit. In comparison, the coldest temperatures on Earth have been recorded near the South Pole in Antarctica—about minus 148 degrees F.

“We don’t operate machines in that kind of thermal environment,” Lewicki said of the extreme temperatures detected in the permanent dark regions of the moon. “Antarctica would be a balmy desert island compared to a lunar polar crater.”

Of course, no one knows quite what awaits us in the asteroid belt. Answers may soon be forthcoming. Last week, the Japan Aerospace Exploration Agency landed two small, hopping rovers on an asteroid called Ryugu. Meanwhile, NASA hopes to retrieve a sample from the near-Earth asteroid Bennu when its OSIRIS-REx mission makes contact at the end of this year.

No Bucks, No Buck Rogers
Visionaries like Elon Musk and Jeff Bezos talk about colonies on Mars, with millions of people living and working in space. The reality is that there’s probably a reason Buck Rogers was set in the 25th century: It’s going to take a lot of money and a lot of time to realize those sci-fi visions.

Or, as Lewicki put it: “No bucks, no Buck Rogers.”

The cost of operating in outer space can be prohibitive. Planetary Resources itself is grappling with raising additional funding, with reports this year about layoffs and even a possible auction of company assets.

Still, Lewicki is confident that despite economic and technical challenges, humanity will someday exceed even the boldest dreamers—skyscrapers on the moon, interplanetary trips to Mars—as judged against today’s engineering marvels.

“What we’re doing is going to be very hard, very painful, and almost certainly worth it,” he said. “Who would have thought that there would be a job for a space miner that you could go to school for, even just five or ten years ago. Things move quickly.”

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#433288 The New AI Tech Turning Heads in Video ...

Posted on September 9, 2018 by Android

A new technique using artificial intelligence to manipulate video content gives new meaning to the expression “talking head.”

An international team of researchers showcased the latest advancement in synthesizing facial expressions—including mouth, eyes, eyebrows, and even head position—in video at this month’s 2018 SIGGRAPH, a conference on innovations in computer graphics, animation, virtual reality, and other forms of digital wizardry.

The project is called Deep Video Portraits. It relies on a type of AI called generative adversarial networks (GANs) to modify a “target” actor based on the facial and head movement of a “source” actor. As the name implies, GANs pit two opposing neural networks against one another to create a realistic talking head, right down to the sneer or raised eyebrow.

In this case, the adversaries are actually working together: One neural network generates content, while the other rejects or approves each effort. The back-and-forth interplay between the two eventually produces a realistic result that can easily fool the human eye, including reproducing a static scene behind the head as it bobs back and forth.

The researchers say the technique can be used by the film industry for a variety of purposes, from editing facial expressions of actors for matching dubbed voices to repositioning an actor’s head in post-production. AI can not only produce highly realistic results, but much quicker ones compared to the manual processes used today, according to the researchers. You can read the full paper of their work here.

“Deep Video Portraits shows how such a visual effect could be created with less effort in the future,” said Christian Richardt, from the University of Bath’s motion capture research center CAMERA, in a press release. “With our approach, even the positioning of an actor’s head and their facial expression could be easily edited to change camera angles or subtly change the framing of a scene to tell the story better.”

AI Tech Different Than So-Called “Deepfakes”
The work is far from the first to employ AI to manipulate video and audio. At last year’s SIGGRAPH conference, researchers from the University of Washington showcased their work using algorithms that inserted audio recordings from a person in one instance into a separate video of the same person in a different context.

In this case, they “faked” a video using a speech from former President Barack Obama addressing a mass shooting incident during his presidency. The AI-doctored video injects the audio into an unrelated video of the president while also blending the facial and mouth movements, creating a pretty credible job of lip synching.

A previous paper by many of the same scientists on the Deep Video Portraits project detailed how they were first able to manipulate a video in real time of a talking head (in this case, actor and former California governor Arnold Schwarzenegger). The Face2Face system pulled off this bit of digital trickery using a depth-sensing camera that tracked the facial expressions of an Asian female source actor.

A less sophisticated method of swapping faces using a machine learning software dubbed FakeApp emerged earlier this year. Predictably, the tech—requiring numerous photos of the source actor in order to train the neural network—was used for more juvenile pursuits, such as injecting a person’s face onto a porn star.

The application gave rise to the term “deepfakes,” which is now used somewhat ubiquitously to describe all such instances of AI-manipulated video—much to the chagrin of some of the researchers involved in more legitimate uses.

Fighting AI-Created Video Forgeries
However, the researchers are keenly aware that their work—intended for benign uses such as in the film industry or even to correct gaze and head positions for more natural interactions through video teleconferencing—could be used for nefarious purposes. Fake news is the most obvious concern.

“With ever-improving video editing technology, we must also start being more critical about the video content we consume every day, especially if there is no proof of origin,” said Michael Zollhöfer, a visiting assistant professor at Stanford University and member of the Deep Video Portraits team, in the press release.

Toward that end, the research team is training the same adversarial neural networks to spot video forgeries. They also strongly recommend that developers clearly watermark videos that are edited through AI or otherwise, and denote clearly what part and element of the scene was modified.

To catch less ethical users, the US Department of Defense, through the Defense Advanced Research Projects Agency (DARPA), is supporting a program called Media Forensics. This latest DARPA challenge enlists researchers to develop technologies to automatically assess the integrity of an image or video, as part of an end-to-end media forensics platform.

The DARPA official in charge of the program, Matthew Turek, did tell MIT Technology Review that so far the program has “discovered subtle cues in current GAN-manipulated images and videos that allow us to detect the presence of alterations.” In one reported example, researchers have targeted eyes, which rarely blink in the case of “deepfakes” like those created by FakeApp, because the AI is trained on still pictures. That method would seem to be less effective to spot the sort of forgeries created by Deep Video Portraits, which appears to flawlessly match the entire facial and head movements between the source and target actors.

“We believe that the field of digital forensics should and will receive a lot more attention in the future to develop approaches that can automatically prove the authenticity of a video clip,” Zollhöfer said. “This will lead to ever-better approaches that can spot such modifications even if we humans might not be able to spot them with our own eyes.

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#433282 The 4 Waves of AI: Who Will Own the ...

Posted on September 9, 2018 by Android

Recently, I picked up Kai-Fu Lee’s newest book, AI Superpowers.

Kai-Fu Lee is one of the most plugged-in AI investors on the planet, managing over $2 billion between six funds and over 300 portfolio companies in the US and China.

Drawing from his pioneering work in AI, executive leadership at Microsoft, Apple, and Google (where he served as founding president of Google China), and his founding of VC fund Sinovation Ventures, Lee shares invaluable insights about:

The four factors driving today’s AI ecosystems;
China’s extraordinary inroads in AI implementation;
Where autonomous systems are headed;
How we’ll need to adapt.

With a foothold in both Beijing and Silicon Valley, Lee looks at the power balance between Chinese and US tech behemoths—each turbocharging new applications of deep learning and sweeping up global markets in the process.

In this post, I’ll be discussing Lee’s “Four Waves of AI,” an excellent framework for discussing where AI is today and where it’s going. I’ll also be featuring some of the hottest Chinese tech companies leading the charge, worth watching right now.

I’m super excited that this Tuesday, I’ve scored the opportunity to sit down with Kai-Fu Lee to discuss his book in detail via a webinar.

With Sino-US competition heating up, who will own the future of technology?

Let’s dive in.

The First Wave: Internet AI
In this first stage of AI deployment, we’re dealing primarily with recommendation engines—algorithmic systems that learn from masses of user data to curate online content personalized to each one of us.

Think Amazon’s spot-on product recommendations, or that “Up Next” YouTube video you just have to watch before getting back to work, or Facebook ads that seem to know what you’ll buy before you do.

Powered by the data flowing through our networks, internet AI leverages the fact that users automatically label data as we browse. Clicking versus not clicking; lingering on a web page longer than we did on another; hovering over a Facebook video to see what happens at the end.

These cascades of labeled data build a detailed picture of our personalities, habits, demands, and desires: the perfect recipe for more tailored content to keep us on a given platform.

Currently, Lee estimates that Chinese and American companies stand head-to-head when it comes to deployment of internet AI. But given China’s data advantage, he predicts that Chinese tech giants will have a slight lead (60-40) over their US counterparts in the next five years.

While you’ve most definitely heard of Alibaba and Baidu, you’ve probably never stumbled upon Toutiao.

Starting out as a copycat of America’s wildly popular Buzzfeed, Toutiao reached a valuation of $20 billion by 2017, dwarfing Buzzfeed’s valuation by more than a factor of 10. But with almost 120 million daily active users, Toutiao doesn’t just stop at creating viral content.

Equipped with natural-language processing and computer vision, Toutiao’s AI engines survey a vast network of different sites and contributors, rewriting headlines to optimize for user engagement, and processing each user’s online behavior—clicks, comments, engagement time—to curate individualized news feeds for millions of consumers.

And as users grow more engaged with Toutiao’s content, the company’s algorithms get better and better at recommending content, optimizing headlines, and delivering a truly personalized feed.

It’s this kind of positive feedback loop that fuels today’s AI giants surfing the wave of internet AI.

The Second Wave: Business AI
While internet AI takes advantage of the fact that netizens are constantly labeling data via clicks and other engagement metrics, business AI jumps on the data that traditional companies have already labeled in the past.

Think banks issuing loans and recording repayment rates; hospitals archiving diagnoses, imaging data, and subsequent health outcomes; or courts noting conviction history, recidivism, and flight.

While we humans make predictions based on obvious root causes (strong features), AI algorithms can process thousands of weakly correlated variables (weak features) that may have much more to do with a given outcome than the usual suspects.

By scouting out hidden correlations that escape our linear cause-and-effect logic, business AI leverages labeled data to train algorithms that outperform even the most veteran of experts.

Apply these data-trained AI engines to banking, insurance, and legal sentencing, and you get minimized default rates, optimized premiums, and plummeting recidivism rates.

While Lee confidently places America in the lead (90-10) for business AI, China’s substantial lag in structured industry data could actually work in its favor going forward.

In industries where Chinese startups can leapfrog over legacy systems, China has a major advantage.

Take Chinese app Smart Finance, for instance.

While Americans embraced credit and debit cards in the 1970s, China was still in the throes of its Cultural Revolution, largely missing the bus on this technology.

Fast forward to 2017, and China’s mobile payment spending outnumbered that of Americans’ by a ratio of 50 to 1. Without the competition of deeply entrenched credit cards, mobile payments were an obvious upgrade to China’s cash-heavy economy, embraced by 70 percent of China’s 753 million smartphone users by the end of 2017.

But by leapfrogging over credit cards and into mobile payments, China largely left behind the notion of credit.

And here’s where Smart Finance comes in.

An AI-powered app for microfinance, Smart Finance depends almost exclusively on its algorithms to make millions of microloans. For each potential borrower, the app simply requests access to a portion of the user’s phone data.

On the basis of variables as subtle as your typing speed and battery percentage, Smart Finance can predict with astounding accuracy your likelihood of repaying a $300 loan.

Such deployments of business AI and internet AI are already revolutionizing our industries and individual lifestyles. But still on the horizon lie two even more monumental waves— perception AI and autonomous AI.

The Third Wave: Perception AI
In this wave, AI gets an upgrade with eyes, ears, and myriad other senses, merging the digital world with our physical environments.

As sensors and smart devices proliferate through our homes and cities, we are on the verge of entering a trillion-sensor economy.

Companies like China’s Xiaomi are putting out millions of IoT-connected devices, and teams of researchers have already begun prototyping smart dust—solar cell- and sensor-geared particulates that can store and communicate troves of data anywhere, anytime.

As Kai-Fu explains, perception AI “will bring the convenience and abundance of the online world into our offline reality.” Sensor-enabled hardware devices will turn everything from hospitals to cars to schools into online-merge-offline (OMO) environments.

Imagine walking into a grocery store, scanning your face to pull up your most common purchases, and then picking up a virtual assistant (VA) shopping cart. Having pre-loaded your data, the cart adjusts your usual grocery list with voice input, reminds you to get your spouse’s favorite wine for an upcoming anniversary, and guides you through a personalized store route.

While we haven’t yet leveraged the full potential of perception AI, China and the US are already making incredible strides. Given China’s hardware advantage, Lee predicts China currently has a 60-40 edge over its American tech counterparts.

Now the go-to city for startups building robots, drones, wearable technology, and IoT infrastructure, Shenzhen has turned into a powerhouse for intelligent hardware, as I discussed last week. Turbocharging output of sensors and electronic parts via thousands of factories, Shenzhen’s skilled engineers can prototype and iterate new products at unprecedented scale and speed.

With the added fuel of Chinese government support and a relaxed Chinese attitude toward data privacy, China’s lead may even reach 80-20 in the next five years.

Jumping on this wave are companies like Xiaomi, which aims to turn bathrooms, kitchens, and living rooms into smart OMO environments. Having invested in 220 companies and incubated 29 startups that produce its products, Xiaomi surpassed 85 million intelligent home devices by the end of 2017, making it the world’s largest network of these connected products.

One KFC restaurant in China has even teamed up with Alipay (Alibaba’s mobile payments platform) to pioneer a ‘pay-with-your-face’ feature. Forget cash, cards, and cell phones, and let OMO do the work.

The Fourth Wave: Autonomous AI
But the most monumental—and unpredictable—wave is the fourth and final: autonomous AI.

Integrating all previous waves, autonomous AI gives machines the ability to sense and respond to the world around them, enabling AI to move and act productively.

While today’s machines can outperform us on repetitive tasks in structured and even unstructured environments (think Boston Dynamics’ humanoid Atlas or oncoming autonomous vehicles), machines with the power to see, hear, touch and optimize data will be a whole new ballgame.

Think: swarms of drones that can selectively spray and harvest entire farms with computer vision and remarkable dexterity, heat-resistant drones that can put out forest fires 100X more efficiently, or Level 5 autonomous vehicles that navigate smart roads and traffic systems all on their own.

While autonomous AI will first involve robots that create direct economic value—automating tasks on a one-to-one replacement basis—these intelligent machines will ultimately revamp entire industries from the ground up.

Kai-Fu Lee currently puts America in a commanding lead of 90-10 in autonomous AI, especially when it comes to self-driving vehicles. But Chinese government efforts are quickly ramping up the competition.

Already in China’s Zhejiang province, highway regulators and government officials have plans to build China’s first intelligent superhighway, outfitted with sensors, road-embedded solar panels and wireless communication between cars, roads and drivers.

Aimed at increasing transit efficiency by up to 30 percent while minimizing fatalities, the project may one day allow autonomous electric vehicles to continuously charge as they drive.

A similar government-fueled project involves Beijing’s new neighbor Xiong’an. Projected to take in over $580 billion in infrastructure spending over the next 20 years, Xiong’an New Area could one day become the world’s first city built around autonomous vehicles.

Baidu is already working with Xiong’an’s local government to build out this AI city with an environmental focus. Possibilities include sensor-geared cement, computer vision-enabled traffic lights, intersections with facial recognition, and parking lots-turned parks.

Lastly, Lee predicts China will almost certainly lead the charge in autonomous drones. Already, Shenzhen is home to premier drone maker DJI—a company I’ll be visiting with 24 top executives later this month as part of my annual China Platinum Trip.

Named “the best company I have ever encountered” by Chris Anderson, DJI owns an estimated 50 percent of the North American drone market, supercharged by Shenzhen’s extraordinary maker movement.

While the long-term Sino-US competitive balance in fourth wave AI remains to be seen, one thing is certain: in a matter of decades, we will witness the rise of AI-embedded cityscapes and autonomous machines that can interact with the real world and help solve today’s most pressing grand challenges.

Join Me
Webinar with Dr. Kai-Fu Lee: Dr. Kai-Fu Lee — one of the world’s most respected experts on AI — and I will discuss his latest book AI Superpowers: China, Silicon Valley, and the New World Order. Artificial Intelligence is reshaping the world as we know it. With U.S.-Sino competition heating up, who will own the future of technology? Register here for the free webinar on September 4th, 2018 from 11:00am–12:30pm PST.

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Posted in Human Robots

#433278 Outdated Evolution: Updating Our ...

Posted on September 9, 2018 by Android

What happens when evolution shapes an animal for tribes of 150 primitive individuals living in a chaotic jungle, and then suddenly that animal finds itself living with millions of others in an engineered metropolis, their pockets all bulging with devices of godlike power?

The result, it seems, is a modern era of tension where archaic forms of governance struggle to keep up with the technological advances of their citizenry, where governmental policies act like constraining bottlenecks rather than spearheads of progress.

Simply put, our governments have failed to adapt to disruptive technologies. And if we are to regain our stability moving forward into a future of even greater disruption, it’s imperative that we understand the issues that got us into this situation and what kind of solutions we can engineer to overcome our governmental weaknesses.

Hierarchy vs. Technological Decentralization
Many of the greatest issues our governments face today come from humanity’s biologically-hardwired desire for centralized hierarchies. This innate proclivity towards building and navigating systems of status and rank were evolutionary gifts handed down to us by our ape ancestors, where each member of a community had a mental map of their social hierarchy. Their nervous systems behaved differently depending on their rank in this hierarchy, influencing their interactions in a way that ensured only the most competent ape would rise to the top to gain access to the best food and mates.

As humanity emerged and discovered the power of language, we continued this practice by ensuring that those at the top of the hierarchies, those with the greatest education and access to information, were the dominant decision-makers for our communities.

However, this kind of structured chain of power is only necessary if we’re operating in conditions of scarcity. But resources, including information, are no longer scarce.

It’s estimated that more than two-thirds of adults in the world now own a smartphone, giving the average citizen the same access to the world’s information as the leaders of our governments. And with global poverty falling from 35.5 percent to 10.9 percent over the last 25 years, our younger generations are growing up seeing automation and abundance as a likely default, where innovations like solar energy, lab-grown meat, and 3D printing are expected to become commonplace.

It’s awareness of this paradigm shift that has empowered the recent rise of decentralization. As information and access to resources become ubiquitous, there is noticeably less need for our inefficient and bureaucratic hierarchies.

For example, if blockchain can prove its feasibility for large-scale systems, it can be used to update and upgrade numerous applications to a decentralized model, including currency and voting. Such innovations would lower the risk of failing banks collapsing the economy like they did in 2008, as well as prevent corrupt politicians from using gerrymandering and long queues at polling stations to deter voter participation.

Of course, technology isn’t a magic wand that should be implemented carelessly. Facebook’s “move fast and break things” approach might have very possibly broken American democracy in 2016, as social media played on some of the worst tendencies humanity can operate on during an election: fear and hostility.

But if decentralized technology, like blockchain’s public ledgers, can continue to spread a sense of security and transparency throughout society, perhaps we can begin to quiet that paranoia and hyper-vigilance our brains evolved to cope with living as apes in dangerous jungles. By decentralizing our power structures, we take away the channels our outdated biological behaviors might use to enact social dominance and manipulation.

The peace of mind this creates helps to reestablish trust in our communities and in our governments. And with trust in the government increased, it’s likely we’ll see our next issue corrected.

From Business and Law to Science and Technology
A study found that 59 percent of US presidents, 68 percent of vice presidents, and 78 percent of secretaries of state were lawyers by education and occupation. That’s more than one out of every two people in the most powerful positions in the American government restricted to a field dedicated to convincing other people (judges) their perspective is true, even if they lack evidence.

And so the scientific method became less important than semantics to our leaders.

Similarly, of the 535 individuals in the American congress, only 24 hold a PhD, only 2 of which are in a STEM field. And so far, it’s not getting better: Trump is the first president since WWII not to name a science advisor.

But if we can use technologies like blockchain to increase transparency, efficiency, and trust in the government, then the upcoming generations who understand decentralization, abundance, and exponential technologies might feel inspired enough to run for government positions. This helps solve that common problem where the smartest and most altruistic people tend to avoid government positions because they don’t want to play the semantic and deceitful game of politics.

By changing this narrative, our governments can begin to fill with techno-progressive individuals who actually understand the technologies that are rapidly reshaping our reality. And this influence of expertise is going to be crucial as our governments are forced to restructure and create new policies to accommodate the incoming disruption.

Clearing Regulations to Begin Safe Experimentation
As exponential technologies become more ubiquitous, we’re likely going to see young kids and garage tinkerers creating powerful AIs and altering genetics thanks to tools like CRISPR and free virtual reality tutorials.

This easy accessibility to such powerful technology means unexpected and rapid progress can occur almost overnight, quickly overwhelming our government’s regulatory systems.

Uber and Airbnb are two of the best examples of our government’s inability to keep up with such technology, both companies achieving market dominance before regulators were even able to consider how to handle them. And when a government has decided against them, they often still continue to operate because people simply choose to keep using the apps.

Luckily, this kind of disruption hasn’t yet posed a major existential threat. But this will change when we see companies begin developing cyborg body parts, brain-computer interfaces, nanobot health injectors, and at-home genetic engineering kits.

For this reason, it’s crucial that we have experts who understand how to update our regulations to be as flexible as is necessary to ensure we don’t create black market conditions like we’ve done with drugs. It’s better to have safe and monitored experimentation, rather than forcing individuals into seedy communities using unsafe products.

Survival of the Most Adaptable
If we hope to be an animal that survives our changing environment, we have to adapt. We cannot cling to the behaviors and systems formed thousands of years ago. We must instead acknowledge that we now exist in an ecosystem of disruptive technology, and we must evolve and update our governments if they’re going to be capable of navigating these transformative impacts.

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Posted in Human Robots

#432884 This Week’s Awesome Stories From ...

Posted on May 18, 2018 by Android

ROBOTICS
Boston Dynamics’ SpotMini Robot Dog Goes on Sale in 2019
Stephen Shankland | CNET
“The company has 10 SpotMini prototypes now and will work with manufacturing partners to build 100 this year, said company co-founder and President Marc Raibert at a TechCrunch robotics conference Friday. ‘That’s a prelude to getting into a higher rate of production’ in anticipation of sales next year, he said. Who’ll buy it? Probably not you.”

Also from Boston Dynamics’ this week:

SPACE
Made In Space Wins NASA Contract for Next-Gen ‘Vulcan’ Manufacturing System
Mike Wall | Space.com
“’The Vulcan hybrid manufacturing system allows for flexible augmentation and creation of metallic components on demand with high precision,’ Mike Snyder, Made In Space chief engineer and principal investigator, said in a statement. …When Vulcan is ready to go, Made In Space aims to demonstrate the technology on the ISS, showing Vulcan’s potential usefulness for a variety of exploration missions.”

ARTIFICIAL INTELLIGENCE
Duplex Shows Google Failing at Ethical and Creative AI Design
Natasha Lomas | TechCrunch
“But while the home crowd cheered enthusiastically at how capable Google had seemingly made its prototype robot caller—with Pichai going on to sketch a grand vision of the AI saving people and businesses time—the episode is worryingly suggestive of a company that views ethics as an after-the-fact consideration. One it does not allow to trouble the trajectory of its engineering ingenuity.”

DESIGN
What Artists Can Tech Us About Making Technology More Human
Elizabeth Stinson| Wired
“For the last year, Park, along with the artist Sougwen Chung and dancers Jason Oremus and Garrett Coleman of the dance collective Hammerstep, have been working out of Bell Labs as part of a residency called Experiments in Art and Technology. The year-long residency, a collaboration between Bell Labs and the New Museum’s incubator, New Inc, culminated in ‘Only Human,’ a recently-opened exhibition at Mana where the artists’ pieces will be on display through the end of May.”

GOVERNANCE
The White House Says a New AI Task Force Will Protect Workers and Keep America First
Will Knight | MIT Technology Review
“The meeting and the select committee signal that the administration takes the impact of artificial intellgence seriously. This has not always been apparent. In his campaign speeches, Trump suggested reviving industries that have already been overhauled by automation. The Treasury secretary, Steven Mnuchin, also previously said that the idea of robots and AI taking people’s jobs was ‘not even on my radar screen.’”

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Posted in Human Robots