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#435110 5 Coming Breakthroughs in Energy and ...

The energy and transportation industries are being aggressively disrupted by converging exponential technologies.

In just five days, the sun provides Earth with an energy supply exceeding all proven reserves of oil, coal, and natural gas. Capturing just 1 part in 8,000 of this available solar energy would allow us to meet 100 percent of our energy needs.

As we leverage renewable energy supplied by the sun, wind, geothermal sources, and eventually fusion, we are rapidly heading towards a future where 100 percent of our energy needs will be met by clean tech in just 30 years.

During the past 40 years, solar prices have dropped 250-fold. And as these costs plummet, solar panel capacity continues to grow exponentially.

On the heels of energy abundance, we are additionally witnessing a new transportation revolution, which sets the stage for a future of seamlessly efficient travel at lower economic and environmental costs.

Top 5 Transportation Breakthroughs (2019-2024)
Entrepreneur and inventor Ramez Naam is my go-to expert on all things energy and environment. Currently serving as the Energy Co-Chair at Singularity University, Naam is the award-winning author of five books, including the Nexus series of science fiction novels. Having spent 13 years at Microsoft, his software has touched the lives of over a billion people. Naam holds over 20 patents, including several shared with co-inventor Bill Gates.

In the next five years, he forecasts five respective transportation and energy trends, each poised to disrupt major players and birth entirely new business models.

Let’s dive in.

Autonomous cars drive 1 billion miles on US roads. Then 10 billion

Alphabet’s Waymo alone has already reached 10 million miles driven in the US. The 600 Waymo vehicles on public roads drive a total of 25,000 miles each day, and computer simulations provide an additional 25,000 virtual cars driving constantly. Since its launch in December, the Waymo One service has transported over 1,000 pre-vetted riders in the Phoenix area.

With more training miles, the accuracy of these cars continues to improve. Since last year, GM Cruise has improved its disengagement rate by 321 percent since last year, trailing close behind with only one human intervention per 5,025 miles self-driven.

Autonomous taxis as a service in top 20 US metro areas

Along with its first quarterly earnings released last week, Lyft recently announced that it would expand its Waymo partnership with the upcoming deployment of 10 autonomous vehicles in the Phoenix area. While individuals previously had to partake in Waymo’s “early rider program” prior to trying Waymo One, the Lyft partnership will allow anyone to ride in a self-driving vehicle without a prior NDA.

Strategic partnerships will grow increasingly essential between automakers, self-driving tech companies, and rideshare services. Ford is currently working with Volkswagen, and Nvidia now collaborates with Daimler (Mercedes) and Toyota. Just last week, GM Cruise raised another $1.15 billion at a $19 billion valuation as the company aims to launch a ride-hailing service this year.

“They’re going to come to the Bay Area, Los Angeles, Houston, other cities with relatively good weather,” notes Naam. “In every major city within five years in the US and in some other parts of the world, you’re going to see the ability to hail an autonomous vehicle as a ride.”

Cambrian explosion of vehicle formats

Naam explains, “If you look today at the average ridership of a taxi, a Lyft, or an Uber, it’s about 1.1 passengers plus the driver. So, why do you need a large four-seater vehicle for that?”

Small electric, autonomous pods that seat as few as two people will begin to emerge, satisfying the majority of ride-hailing demands we see today. At the same time, larger communal vehicles will appear, such as Uber Express, that will undercut even the cheapest of transportation methods—buses, trams, and the like. Finally, last-mile scooter transit (or simply short-distance walks) might connect you to communal pick-up locations.

By 2024, an unimaginably diverse range of vehicles will arise to meet every possible need, regardless of distance or destination.

Drone delivery for lightweight packages in at least one US city

Wing, the Alphabet drone delivery startup, recently became the first company to gain approval from the Federal Aviation Administration (FAA) to make deliveries in the US. Having secured approval to deliver to 100 homes in Canberra, Australia, Wing additionally plans to begin delivering goods from local businesses in the suburbs of Virginia.

The current state of drone delivery is best suited for lightweight, urgent-demand payloads like pharmaceuticals, thumb drives, or connectors. And as Amazon continues to decrease its Prime delivery times—now as speedy as a one-day turnaround in many cities—the use of drones will become essential.

Robotic factories drive onshoring of US factories… but without new jobs

The supply chain will continue to shorten and become more agile with the re-onshoring of manufacturing jobs in the US and other countries. Naam reasons that new management and software jobs will drive this shift, as these roles develop the necessary robotics to manufacture goods. Equally as important, these robotic factories will provide a more humane setting than many of the current manufacturing practices overseas.

Top 5 Energy Breakthroughs (2019-2024)

First “1 cent per kWh” deals for solar and wind signed

Ten years ago, the lowest price of solar and wind power fell between 10 to 12 cents per kilowatt hour (kWh), over twice the price of wholesale power from coal or natural gas.

Today, the gap between solar/wind power and fossil fuel-generated electricity is nearly negligible in many parts of the world. In G20 countries, fossil fuel electricity costs between 5 to 17 cents per kWh, while the average cost per kWh of solar power in the US stands at under 10 cents.

Spanish firm Solarpack Corp Technological recently won a bid in Chile for a 120 MW solar power plant supplying energy at 2.91 cents per kWh. This deal will result in an estimated 25 percent drop in energy costs for Chilean businesses by 2021.

Naam indicates, “We will see the first unsubsidized 1.0 cent solar deals in places like Chile, Mexico, the Southwest US, the Middle East, and North Africa, and we’ll see similar prices for wind in places like Mexico, Brazil, and the US Great Plains.”

Solar and wind will reach >15 percent of US electricity, and begin to drive all growth

Just over eight percent of energy in the US comes from solar and wind sources. In total, 17 percent of American energy is derived from renewable sources, while a whopping 63 percent is sourced from fossil fuels, and 17 percent from nuclear.

Last year in the U.K., twice as much energy was generated from wind than from coal. For over a week in May, the U.K. went completely coal-free, using wind and solar to supply 35 percent and 21 percent of power, respectively. While fossil fuels remain the primary electricity source, this week-long experiment highlights the disruptive potential of solar and wind power that major countries like the U.K. are beginning to emphasize.

“Solar and wind are still a relatively small part of the worldwide power mix, only about six percent. Within five years, it’s going to be 15 percent in the US and more than close to that worldwide,” Naam predicts. “We are nearing the point where we are not building any new fossil fuel power plants.”

It will be cheaper to build new solar/wind/batteries than to run on existing coal

Last October, Northern Indiana utility company NIPSCO announced its transition from a 65 percent coal-powered state to projected coal-free status by 2028. Importantly, this decision was made purely on the basis of financials, with an estimated $4 billion in cost savings for customers. The company has already begun several initiatives in solar, wind, and batteries.

NextEra, the largest power generator in the US, has taken on a similar goal, making a deal last year to purchase roughly seven million solar panels from JinkoSolar over four years. Leading power generators across the globe have vocalized a similar economic case for renewable energy.

ICE car sales have now peaked. All car sales growth will be electric

While electric vehicles (EV) have historically been more expensive for consumers than internal combustion engine-powered (ICE) cars, EVs are cheaper to operate and maintain. The yearly cost of operating an EV in the US is about $485, less than half the $1,117 cost of operating a gas-powered vehicle.

And as battery prices continue to shrink, the upfront costs of EVs will decline until a long-term payoff calculation is no longer required to determine which type of car is the better investment. EVs will become the obvious choice.

Many experts including Naam believe that ICE-powered vehicles peaked worldwide in 2018 and will begin to decline over the next five years, as has already been demonstrated in the past five months. At the same time, EVs are expected to quadruple their market share to 1.6 percent this year.

New storage technologies will displace Li-ion batteries for tomorrow’s most demanding applications

Lithium ion batteries have dominated the battery market for decades, but Naam anticipates new storage technologies will take hold for different contexts. Flow batteries, which can collect and store solar and wind power at large scales, will supply city grids. Already, California’s Independent System Operator, the nonprofit that maintains the majority of the state’s power grid, recently installed a flow battery system in San Diego.

Solid-state batteries, which consist of entirely solid electrolytes, will supply mobile devices in cars. A growing body of competitors, including Toyota, BMW, Honda, Hyundai, and Nissan, are already working on developing solid-state battery technology. These types of batteries offer up to six times faster charging periods, three times the energy density, and eight years of added lifespan, compared to lithium ion batteries.

Final Thoughts
Major advancements in transportation and energy technologies will continue to converge over the next five years. A case in point, Tesla’s recent announcement of its “robotaxi” fleet exemplifies the growing trend towards joint priority of sustainability and autonomy.

On the connectivity front, 5G and next-generation mobile networks will continue to enable the growth of autonomous fleets, many of which will soon run on renewable energy sources. This growth demands important partnerships between energy storage manufacturers, automakers, self-driving tech companies, and ridesharing services.

In the eco-realm, increasingly obvious economic calculi will catalyze consumer adoption of autonomous electric vehicles. In just five years, Naam predicts that self-driving rideshare services will be cheaper than owning a private vehicle for urban residents. And by the same token, plummeting renewable energy costs will make these fuels far more attractive than fossil fuel-derived electricity.

As universally optimized AI systems cut down on traffic, aggregate time spent in vehicles will decimate, while hours in your (or not your) car will be applied to any number of activities as autonomous systems steer the way. All the while, sharing an electric vehicle will cut down not only on your carbon footprint but on the exorbitant costs swallowed by your previous SUV. How will you spend this extra time and money? What new natural resources will fuel your everyday life?

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Posted in Human Robots

#435098 Coming of Age in the Age of AI: The ...

The first generation to grow up entirely in the 21st century will never remember a time before smartphones or smart assistants. They will likely be the first children to ride in self-driving cars, as well as the first whose healthcare and education could be increasingly turned over to artificially intelligent machines.

Futurists, demographers, and marketers have yet to agree on the specifics of what defines the next wave of humanity to follow Generation Z. That hasn’t stopped some, like Australian futurist Mark McCrindle, from coining the term Generation Alpha, denoting a sort of reboot of society in a fully-realized digital age.

“In the past, the individual had no power, really,” McCrindle told Business Insider. “Now, the individual has great control of their lives through being able to leverage this world. Technology, in a sense, transformed the expectations of our interactions.”

No doubt technology may impart Marvel superhero-like powers to Generation Alpha that even tech-savvy Millennials never envisioned over cups of chai latte. But the powers of machine learning, computer vision, and other disciplines under the broad category of artificial intelligence will shape this yet unformed generation more definitively than any before it.

What will it be like to come of age in the Age of AI?

The AI Doctor Will See You Now
Perhaps no other industry is adopting and using AI as much as healthcare. The term “artificial intelligence” appears in nearly 90,000 publications from biomedical literature and research on the PubMed database.

AI is already transforming healthcare and longevity research. Machines are helping to design drugs faster and detect disease earlier. And AI may soon influence not only how we diagnose and treat illness in children, but perhaps how we choose which children will be born in the first place.

A study published earlier this month in NPJ Digital Medicine by scientists from Weill Cornell Medicine used 12,000 photos of human embryos taken five days after fertilization to train an AI algorithm on how to tell which in vitro fertilized embryo had the best chance of a successful pregnancy based on its quality.

Investigators assigned each embryo a grade based on various aspects of its appearance. A statistical analysis then correlated that grade with the probability of success. The algorithm, dubbed Stork, was able to classify the quality of a new set of images with 97 percent accuracy.

“Our algorithm will help embryologists maximize the chances that their patients will have a single healthy pregnancy,” said Dr. Olivier Elemento, director of the Caryl and Israel Englander Institute for Precision Medicine at Weill Cornell Medicine, in a press release. “The IVF procedure will remain the same, but we’ll be able to improve outcomes by harnessing the power of artificial intelligence.”

Other medical researchers see potential in applying AI to detect possible developmental issues in newborns. Scientists in Europe, working with a Finnish AI startup that creates seizure monitoring technology, have developed a technique for detecting movement patterns that might indicate conditions like cerebral palsy.

Published last month in the journal Acta Pediatrica, the study relied on an algorithm to extract the movements from a newborn, turning it into a simplified “stick figure” that medical experts could use to more easily detect clinically relevant data.

The researchers are continuing to improve the datasets, including using 3D video recordings, and are now developing an AI-based method for determining if a child’s motor maturity aligns with its true age. Meanwhile, a study published in February in Nature Medicine discussed the potential of using AI to diagnose pediatric disease.

AI Gets Classy
After being weaned on algorithms, Generation Alpha will hit the books—about machine learning.

China is famously trying to win the proverbial AI arms race by spending billions on new technologies, with one Chinese city alone pledging nearly $16 billion to build a smart economy based on artificial intelligence.

To reach dominance by its stated goal of 2030, Chinese cities are also incorporating AI education into their school curriculum. Last year, China published its first high school textbook on AI, according to the South China Morning Post. More than 40 schools are participating in a pilot program that involves SenseTime, one of the country’s biggest AI companies.

In the US, where it seems every child has access to their own AI assistant, researchers are just beginning to understand how the ubiquity of intelligent machines will influence the ways children learn and interact with their highly digitized environments.

Sandra Chang-Kredl, associate professor of the department of education at Concordia University, told The Globe and Mail that AI could have detrimental effects on learning creativity or emotional connectedness.

Similar concerns inspired Stefania Druga, a member of the Personal Robots group at the MIT Media Lab (and former Education Teaching Fellow at SU), to study interactions between children and artificial intelligence devices in order to encourage positive interactions.

Toward that goal, Druga created Cognimates, a platform that enables children to program and customize their own smart devices such as Alexa or even a smart, functional robot. The kids can also use Cognimates to train their own AI models or even build a machine learning version of Rock Paper Scissors that gets better over time.

“I believe it’s important to also introduce young people to the concepts of AI and machine learning through hands-on projects so they can make more informed and critical use of these technologies,” Druga wrote in a Medium blog post.

Druga is also the founder of Hackidemia, an international organization that sponsors workshops and labs around the world to introduce kids to emerging technologies at an early age.

“I think we are in an arms race in education with the advancement of technology, and we need to start thinking about AI literacy before patterns of behaviors for children and their families settle in place,” she wrote.

AI Goes Back to School
It also turns out that AI has as much to learn from kids. More and more researchers are interested in understanding how children grasp basic concepts that still elude the most advanced machine minds.

For example, developmental psychologist Alison Gopnik has written and lectured extensively about how studying the minds of children can provide computer scientists clues on how to improve machine learning techniques.

In an interview on Vox, she described that while DeepMind’s AlpahZero was trained to be a chessmaster, it struggles with even the simplest changes in the rules, such as allowing the bishop to move horizontally instead of vertically.

“A human chess player, even a kid, will immediately understand how to transfer that new rule to their playing of the game,” she noted. “Flexibility and generalization are something that even human one-year-olds can do but that the best machine learning systems have a much harder time with.”

Last year, the federal defense agency DARPA announced a new program aimed at improving AI by teaching it “common sense.” One of the chief strategies is to develop systems for “teaching machines through experience, mimicking the way babies grow to understand the world.”

Such an approach is also the basis of a new AI program at MIT called the MIT Quest for Intelligence.

The research leverages cognitive science to understand human intelligence, according to an article on the project in MIT Technology Review, such as exploring how young children visualize the world using their own innate 3D models.

“Children’s play is really serious business,” said Josh Tenenbaum, who leads the Computational Cognitive Science lab at MIT and his head of the new program. “They’re experiments. And that’s what makes humans the smartest learners in the known universe.”

In a world increasingly driven by smart technologies, it’s good to know the next generation will be able to keep up.

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Posted in Human Robots

#434797 This Week’s Awesome Stories From ...

GENE EDITING
Genome Engineers Made More Than 13,000 Genome Edits in a Single Cell
Antonio Regalado | MIT Technology Review
“The group, led by gene technologist George Church, wants to rewrite genomes at a far larger scale than has currently been possible, something it says could ultimately lead to the ‘radical redesign’ of species—even humans.”

ROBOTICS
Inside Google’s Rebooted Robotics Program
Cade Metz | The New York Times
“Google’s new lab is indicative of a broader effort to bring so-called machine learning to robotics. …Many believe that machine learning—not extravagant new devices—will be the key to developing robotics for manufacturing, warehouse automation, transportation and many other tasks.

VIDEOS
Boston Dynamics Builds the Warehouse Robot of Jeff Bezos’ Dreams
Luke Dormehl | Digital Trends
“…for anyone wondering what the future of warehouse operation is likely to look like, this offers a far more practical glimpse of the years to come than, say, a dancing dog robot. As Boston Dynamics moves toward commercializing its creations for the first time, this could turn out to be a lot closer than you might think.”

TECHNOLOGY
Europe Is Splitting the Internet Into Three
Casey Newton | The Verge
“The internet had previously been divided into two: the open web, which most of the world could access; and the authoritarian web of countries like China, which is parceled out stingily and heavily monitored. As of today, though, the web no longer feels truly worldwide. Instead we now have the American internet, the authoritarian internet, and the European internet. How does the EU Copyright Directive change our understanding of the web?”

VIRTUAL REALITY
No Man’s Sky’s Next Update Will Let You Explore Infinite Space in Virtual Reality
Taylor Hatmaker | TechCrunch
“Assuming the game runs well enough, No Man’s Sky Virtual Reality will be a far cry from gimmicky VR games that lack true depth, offering one of the most expansive—if not the most expansive—VR experiences to date.”

3D PRINTING
3D Metal Printing Tries to Break Into the Manufacturing Mainstream
Mark Anderson | IEEE Spectrum
“It’s been five or so years since 3D printing was at peak hype. Since then, the technology has edged its way into a new class of materials and started to break into more applications. Today, 3D printers are being seriously considered as a means to produce stainless steel 5G smartphones, high-strength alloy gas-turbine blades, and other complex metal parts.”

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Posted in Human Robots

#434701 3 Practical Solutions to Offset ...

In recent years, the media has sounded the alarm about mass job loss to automation and robotics—some studies predict that up to 50 percent of current jobs or tasks could be automated in coming decades. While this topic has received significant attention, much of the press focuses on potential problems without proposing realistic solutions or considering new opportunities.

The economic impacts of AI, robotics, and automation are complex topics that require a more comprehensive perspective to understand. Is universal basic income, for example, the answer? Many believe so, and there are a number of experiments in progress. But it’s only one strategy, and without a sustainable funding source, universal basic income may not be practical.

As automation continues to accelerate, we’ll need a multi-pronged approach to ease the transition. In short, we need to update broad socioeconomic strategies for a new century of rapid progress. How, then, do we plan practical solutions to support these new strategies?

Take history as a rough guide to the future. Looking back, technology revolutions have three themes in common.

First, past revolutions each produced profound benefits to productivity, increasing human welfare. Second, technological innovation and technology diffusion have accelerated over time, each iteration placing more strain on the human ability to adapt. And third, machines have gradually replaced more elements of human work, with human societies adapting by moving into new forms of work—from agriculture to manufacturing to service, for example.

Public and private solutions, therefore, need to be developed to address each of these three components of change. Let’s explore some practical solutions for each in turn.

Figure 1. Technology’s structural impacts in the 21st century. Refer to Appendix I for quantitative charts and technological examples corresponding to the numbers (1-22) in each slice.
Solution 1: Capture New Opportunities Through Aggressive Investment
The rapid emergence of new technology promises a bounty of opportunity for the twenty-first century’s economic winners. This technological arms race is shaping up to be a global affair, and the winners will be determined in part by who is able to build the future economy fastest and most effectively. Both the private and public sectors have a role to play in stimulating growth.

At the country level, several nations have created competitive strategies to promote research and development investments as automation technologies become more mature.

Germany and China have two of the most notable growth strategies. Germany’s Industrie 4.0 plan targets a 50 percent increase in manufacturing productivity via digital initiatives, while halving the resources required. China’s Made in China 2025 national strategy sets ambitious targets and provides subsidies for domestic innovation and production. It also includes building new concept cities, investing in robotics capabilities, and subsidizing high-tech acquisitions abroad to become the leader in certain high-tech industries. For China, specifically, tech innovation is driven partially by a fear that technology will disrupt social structures and government control.

Such opportunities are not limited to existing economic powers. Estonia’s progress after the breakup of the Soviet Union is a good case study in transitioning to a digital economy. The nation rapidly implemented capitalistic reforms and transformed itself into a technology-centric economy in preparation for a massive tech disruption. Internet access was declared a right in 2000, and the country’s classrooms were outfitted for a digital economy, with coding as a core educational requirement starting at kindergarten. Internet broadband speeds in Estonia are among the fastest in the world. Accordingly, the World Bank now ranks Estonia as a high-income country.

Solution 2: Address Increased Rate of Change With More Nimble Education Systems
Education and training are currently not set for the speed of change in the modern economy. Schools are still based on a one-time education model, with school providing the foundation for a single lifelong career. With content becoming obsolete faster and rapidly escalating costs, this system may be unsustainable in the future. To help workers more smoothly transition from one job into another, for example, we need to make education a more nimble, lifelong endeavor.

Primary and university education may still have a role in training foundational thinking and general education, but it will be necessary to curtail rising price of tuition and increase accessibility. Massive open online courses (MooCs) and open-enrollment platforms are early demonstrations of what the future of general education may look like: cheap, effective, and flexible.

Georgia Tech’s online Engineering Master’s program (a fraction of the cost of residential tuition) is an early example in making university education more broadly available. Similarly, nanodegrees or microcredentials provided by online education platforms such as Udacity and Coursera can be used for mid-career adjustments at low cost. AI itself may be deployed to supplement the learning process, with applications such as AI-enhanced tutorials or personalized content recommendations backed by machine learning. Recent developments in neuroscience research could optimize this experience by perfectly tailoring content and delivery to the learner’s brain to maximize retention.

Finally, companies looking for more customized skills may take a larger role in education, providing on-the-job training for specific capabilities. One potential model involves partnering with community colleges to create apprenticeship-style learning, where students work part-time in parallel with their education. Siemens has pioneered such a model in four states and is developing a playbook for other companies to do the same.

Solution 3: Enhance Social Safety Nets to Smooth Automation Impacts
If predicted job losses to automation come to fruition, modernizing existing social safety nets will increasingly become a priority. While the issue of safety nets can become quickly politicized, it is worth noting that each prior technological revolution has come with corresponding changes to the social contract (see below).

The evolving social contract (U.S. examples)
– 1842 | Right to strike
– 1924 | Abolish child labor
– 1935 | Right to unionize
– 1938 | 40-hour work week
– 1962, 1974 | Trade adjustment assistance
– 1964 | Pay discrimination prohibited
– 1970 | Health and safety laws
– 21st century | AI and automation adjustment assistance?

Figure 2. Labor laws have historically adjusted as technology and society progressed

Solutions like universal basic income (no-strings-attached monthly payout to all citizens) are appealing in concept, but somewhat difficult to implement as a first measure in countries such as the US or Japan that already have high debt. Additionally, universal basic income may create dis-incentives to stay in the labor force. A similar cautionary tale in program design was the Trade Adjustment Assistance (TAA), which was designed to protect industries and workers from import competition shocks from globalization, but is viewed as a missed opportunity due to insufficient coverage.

A near-term solution could come in the form of graduated wage insurance (compensation for those forced to take a lower-paying job), including health insurance subsidies to individuals directly impacted by automation, with incentives to return to the workforce quickly. Another topic to tackle is geographic mismatch between workers and jobs, which can be addressed by mobility assistance. Lastly, a training stipend can be issued to individuals as means to upskill.

Policymakers can intervene to reverse recent historical trends that have shifted incomes from labor to capital owners. The balance could be shifted back to labor by placing higher taxes on capital—an example is the recently proposed “robot tax” where the taxation would be on the work rather than the individual executing it. That is, if a self-driving car performs the task that formerly was done by a human, the rideshare company will still pay the tax as if a human was driving.

Other solutions may involve distribution of work. Some countries, such as France and Sweden, have experimented with redistributing working hours. The idea is to cap weekly hours, with the goal of having more people employed and work more evenly spread. So far these programs have had mixed results, with lower unemployment but high costs to taxpayers, but are potential models that can continue to be tested.

We cannot stop growth, nor should we. With the roles in response to this evolution shifting, so should the social contract between the stakeholders. Government will continue to play a critical role as a stabilizing “thumb” in the invisible hand of capitalism, regulating and cushioning against extreme volatility, particularly in labor markets.

However, we already see business leaders taking on some of the role traditionally played by government—thinking about measures to remedy risks of climate change or economic proposals to combat unemployment—in part because of greater agility in adapting to change. Cross-disciplinary collaboration and creative solutions from all parties will be critical in crafting the future economy.

Note: The full paper this article is based on is available here.

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Posted in Human Robots

#434673 The World’s Most Valuable AI ...

It recognizes our faces. It knows the videos we might like. And it can even, perhaps, recommend the best course of action to take to maximize our personal health.

Artificial intelligence and its subset of disciplines—such as machine learning, natural language processing, and computer vision—are seemingly becoming integrated into our daily lives whether we like it or not. What was once sci-fi is now ubiquitous research and development in company and university labs around the world.

Similarly, the startups working on many of these AI technologies have seen their proverbial stock rise. More than 30 of these companies are now valued at over a billion dollars, according to data research firm CB Insights, which itself employs algorithms to provide insights into the tech business world.

Private companies with a billion-dollar valuation were so uncommon not that long ago that they were dubbed unicorns. Now there are 325 of these once-rare creatures, with a combined valuation north of a trillion dollars, as CB Insights maintains a running count of this exclusive Unicorn Club.

The subset of AI startups accounts for about 10 percent of the total membership, growing rapidly in just 4 years from 0 to 32. Last year, an unprecedented 17 AI startups broke the billion-dollar barrier, with 2018 also a record year for venture capital into private US AI companies at $9.3 billion, CB Insights reported.

What exactly is all this money funding?

AI Keeps an Eye Out for You
Let’s start with the bad news first.

Facial recognition is probably one of the most ubiquitous applications of AI today. It’s actually a decades-old technology often credited to a man named Woodrow Bledsoe, who used an instrument called a RAND tablet that could semi-autonomously match faces from a database. That was in the 1960s.

Today, most of us are familiar with facial recognition as a way to unlock our smartphones. But the technology has gained notoriety as a surveillance tool of law enforcement, particularly in China.

It’s no secret that the facial recognition algorithms developed by several of the AI unicorns from China—SenseTime, CloudWalk, and Face++ (also known as Megvii)—are used to monitor the country’s 1.3 billion citizens. Police there are even equipped with AI-powered eyeglasses for such purposes.

A fourth billion-dollar Chinese startup, Yitu Technologies, also produces a platform for facial recognition in the security realm, and develops AI systems in healthcare on top of that. For example, its CARE.AITM Intelligent 4D Imaging System for Chest CT can reputedly identify in real time a variety of lesions for the possible early detection of cancer.

The AI Doctor Is In
As Peter Diamandis recently noted, AI is rapidly augmenting healthcare and longevity. He mentioned another AI unicorn from China in this regard—iCarbonX, which plans to use machines to develop personalized health plans for every individual.

A couple of AI unicorns on the hardware side of healthcare are OrCam Technologies and Butterfly. The former, an Israeli company, has developed a wearable device for the vision impaired called MyEye that attaches to one’s eyeglasses. The device can identify people and products, as well as read text, conveying the information through discrete audio.

Butterfly Network, out of Connecticut, has completely upended the healthcare market with a handheld ultrasound machine that works with a smartphone.

“Orcam and Butterfly are amazing examples of how machine learning can be integrated into solutions that provide a step-function improvement over state of the art in ultra-competitive markets,” noted Andrew Byrnes, investment director at Comet Labs, a venture capital firm focused on AI and robotics, in an email exchange with Singularity Hub.

AI in the Driver’s Seat
Comet Labs’ portfolio includes two AI unicorns, Megvii and Pony.ai.

The latter is one of three billion-dollar startups developing the AI technology behind self-driving cars, with the other two being Momenta.ai and Zoox.

Founded in 2016 near San Francisco (with another headquarters in China), Pony.ai debuted its latest self-driving system, called PonyAlpha, last year. The platform uses multiple sensors (LiDAR, cameras, and radar) to navigate its environment, but its “sensor fusion technology” makes things simple by choosing the most reliable sensor data for any given driving scenario.

Zoox is another San Francisco area startup founded a couple of years earlier. In late 2018, it got the green light from the state of California to be the first autonomous vehicle company to transport a passenger as part of a pilot program. Meanwhile, China-based Momenta.ai is testing level four autonomy for its self-driving system. Autonomous driving levels are ranked zero to five, with level five being equal to a human behind the wheel.

The hype around autonomous driving is currently in overdrive, and Byrnes thinks regulatory roadblocks will keep most self-driving cars in idle for the foreseeable future. The exception, he said, is China, which is adopting a “systems” approach to autonomy for passenger transport.

“If [autonomous mobility] solves bigger problems like traffic that can elicit government backing, then that has the potential to go big fast,” he said. “This is why we believe Pony.ai will be a winner in the space.”

AI in the Back Office
An AI-powered technology that perhaps only fans of the cult classic Office Space might appreciate has suddenly taken the business world by storm—robotic process automation (RPA).

RPA companies take the mundane back office work, such as filling out invoices or processing insurance claims, and turn it over to bots. The intelligent part comes into play because these bots can tackle unstructured data, such as text in an email or even video and pictures, in order to accomplish an increasing variety of tasks.

Both Automation Anywhere and UiPath are older companies, founded in 2003 and 2005, respectively. However, since just 2017, they have raised nearly a combined $1 billion in disclosed capital.

Cybersecurity Embraces AI
Cybersecurity is another industry where AI is driving investment into startups. Sporting imposing names like CrowdStrike, Darktrace, and Tanium, these cybersecurity companies employ different machine-learning techniques to protect computers and other IT assets beyond the latest software update or virus scan.

Darktrace, for instance, takes its inspiration from the human immune system. Its algorithms can purportedly “learn” the unique pattern of each device and user on a network, detecting emerging problems before things spin out of control.

All three companies are used by major corporations and governments around the world. CrowdStrike itself made headlines a few years ago when it linked the hacking of the Democratic National Committee email servers to the Russian government.

Looking Forward
I could go on, and introduce you to the world’s most valuable startup, a Chinese company called Bytedance that is valued at $75 billion for news curation and an app to create 15-second viral videos. But that’s probably not where VC firms like Comet Labs are generally putting their money.

Byrnes sees real value in startups that are taking “data-driven approaches to problems specific to unique industries.” Take the example of Chicago-based unicorn Uptake Technologies, which analyzes incoming data from machines, from wind turbines to tractors, to predict problems before they occur with the machinery. A not-yet unicorn called PingThings in the Comet Labs portfolio does similar predictive analytics for the energy utilities sector.

“One question we like asking is, ‘What does the state of the art look like in your industry in three to five years?’” Byrnes said. “We ask that a lot, then we go out and find the technology-focused teams building those things.”

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