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Robot technology is evolving at breakneck speed. SoftBank’s Pepper is found in companies across the globe and is rapidly improving its conversation skills. Telepresence robots open up new opportunities for remote working, while Boston Dynamics’ Handle robot could soon (literally) take a load off human colleagues in warehouses.
But warehouses and offices aren’t the only places where robots are lining up next to humans.
Toyota’s Cue 3 robot recently showed off its basketball skills, putting up better numbers than the NBA’s most accurate three-point shooter, the Golden State Warriors’ Steph Curry.
Cue 3 is still some way from being ready to take on Curry, or even amateur basketball players, in a real game. However, it is the latest member of a growing cast of robots challenging human dominance in sports.
As these robots continue to develop, they not only exemplify the speed of exponential technology development, but also how those technologies are improving human capabilities.
Meet the Contestants
The list of robots in sports is surprisingly long and diverse. There are robot skiers, tumblers, soccer players, sumos, and even robot game jockeys. Introductions to a few of them are in order.
Sport: Table tennis
Intro: Looks like something out of War of the Worlds equipped with a ping pong bat instead of a death ray.
Ability level: Capable of counteracting spin shots and good enough to beat many beginners.
Robot: Sumo bot
Sport: Sumo wrestling
Intro: Hyper-fast, hyper-aggressive. Think robot equivalent to an angry wasp on six cans of Red Bull crossed with a very small tank.
Ability level: Flies around the ring way faster than any human sumo. Tend to drive straight out of the ring at times.
Robot: Cue 3
Intro: Stands at an imposing 6 foot and 10 inches, so pretty much built for the NBA. Looks a bit like something that belongs in a video game.
Ability level: A 62.5 percent three-pointer percentage, which is better than Steph Curry’s; is less mobile than Charles Barkley – in his current form.
Robot: Robo Cup Robots
Intro: The future of soccer. If everything goes to plan, a team of robots will take on the Lionel Messis and Cristiano Ronaldos of 2050 and beat them in a full 11 vs. 11 game.
Ability level: Currently plays soccer more like the six-year-olds I used to coach than Lionel Messi.
The Limiting Factor
The skill level of all the robots above is impressive, and they are doing things that no human contestant can. The sumo bots’ inhuman speed is self-evident. Forpheus’ ability to track the ball with two cameras while simultaneously tracking its opponent with two other cameras requires a look at the spec sheet, but is similarly beyond human capability. While Cue 3 can’t move, it makes shots from the mid-court logo look easy.
Robots are performing at a level that was confined to the realm of science fiction at the start of the millennium. The speed of development indicates that in the near future, my national team soccer coach would likely call up a robot instead of me (he must have lost my number since he hasn’t done so yet. It’s the only logical explanation), and he’d be right to do so.
It is also worth considering that many current sports robots have a humanoid form, which limits their ability. If engineers were to optimize robot design to outperform humans in specific categories, many world champions would likely already be metallic.
Swimming is perhaps one of the most obvious. Even Michael Phelps would struggle to keep up with a torpedo-shaped robot, and if you beefed up a sumo robot to human size, human sumos might impress you by running away from them with a 100-meter speed close to Usain Bolt’s.
In other areas, the playing field for humans and robots is rapidly leveling. One likely candidate for the first head-to-head competitions is racing, where self-driving cars from the Roborace League could perhaps soon be ready to race the likes of Lewis Hamilton.
Tech Pushing Humans
Perhaps one of the biggest reasons why it may still take some time for robots to surpass us is that they, along with other exponential technologies, are already making us better at sports.
In Japan, elite volleyball players use a robot to practice their attacks. Some American football players also practice against robot opponents and hone their skills using VR.
On the sidelines, AI is being used to analyze and improve athletes’ performance, and we may soon see the first AI coaches, not to mention referees.
We may even compete in games dreamt up by our electronic cousins. SpeedGate, a new game created by an AI by studying 400 different sports, is a prime example of that quickly becoming a possibility.
However, we will likely still need to make the final call on what constitutes a good game. The AI that created SpeedGate reportedly also suggested less suitable pastimes, like underwater parkour and a game that featured exploding frisbees. Both of these could be fun…but only if you’re as sturdy as a robot.
Image Credit: RoboCup Standard Platform League 2018, ©The Robocup Federation. Published with permission of reproduction granted by the RoboCup Federation. Continue reading
Plants are the planet’s lungs, but they’re struggling to keep up due to rising CO2 emissions and deforestation. Engineers are giving them a helping hand, though, by augmenting their capacity with new technology and creating artificial substitutes to help them clean up our atmosphere.
Imperial College London, one of the UK’s top engineering schools, recently announced that it was teaming up with startup Arborea to build the company’s first outdoor pilot of its BioSolar Leaf cultivation system at the university’s White City campus in West London.
Arborea is developing large solar panel-like structures that house microscopic plants and can be installed on buildings or open land. The plants absorb light and carbon dioxide as they photosynthesize, removing greenhouse gases from the air and producing organic material, which can be processed to extract valuable food additives like omega-3 fatty acids.
The idea of growing algae to produce useful materials isn’t new, but Arborea’s pitch seems to be flexibility and affordability. The more conventional approach is to grow algae in open ponds, which are less efficient and open to contamination, or in photo-bioreactors, which typically require CO2 to be piped in rather than getting it from the air and can be expensive to run.
There’s little detail on how the technology deals with issues like nutrient supply and harvesting or how efficient it is. The company claims it can remove carbon dioxide as fast as 100 trees using the surface area of just a single tree, but there’s no published research to back that up, and it’s hard to compare the surface area of flat panels to that of a complex object like a tree. If you flattened out every inch of a tree’s surface it would cover a surprisingly large area.
Nonetheless, the ability to install these panels directly on buildings could present a promising way to soak up the huge amount of CO2 produced in our cities by transport and industry. And Arborea isn’t the only one trying to give plants a helping hand.
For decades researchers have been working on ways to use light-activated catalysts to split water into oxygen and hydrogen fuel, and more recently there have been efforts to fuse this with additional processes to combine the hydrogen with carbon from CO2 to produce all kinds of useful products.
Most notably, in 2016 Harvard researchers showed that water-splitting catalysts could be augmented with bacteria that combines the resulting hydrogen with CO2 to create oxygen and biomass, fuel, or other useful products. The approach was more efficient than plants at turning CO2 to fuel and was built using cheap materials, but turning it into a commercially viable technology will take time.
Not everyone is looking to mimic or borrow from biology in their efforts to suck CO2 out of the atmosphere. There’s been a recent glut of investment in startups working on direct-air capture (DAC) technology, which had previously been written off for using too much power and space to be practical. The looming climate change crisis appears to be rewriting some of those assumptions, though.
Most approaches aim to use the concentrated CO2 to produce synthetic fuels or other useful products, creating a revenue stream that could help improve their commercial viability. But we look increasingly likely to surpass the safe greenhouse gas limits, so attention is instead turning to carbon-negative technologies.
That means capturing CO2 from the air and then putting it into long-term storage. One way could be to grow lots of biomass and then bury it, mimicking the process that created fossil fuels in the first place. Or DAC plants could pump the CO2 they produce into deep underground wells.
But the former would take up unreasonably large amounts of land to make a significant dent in emissions, while the latter would require huge amounts of already scant and expensive renewable power. According to a recent analysis, artificial photosynthesis could sidestep these issues because it’s up to five times more efficient than its natural counterpart and could be cheaper than DAC.
Whether the technology will develop quickly enough for it to be deployed at scale and in time to mitigate the worst effects of climate change remains to be seen. Emissions reductions certainly present a more sure-fire way to deal with the problem, but nonetheless, cyborg plants could soon be a common sight in our cities.
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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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Convergence is accelerating disruption… everywhere! Exponential technologies are colliding into each other, reinventing products, services, and industries.
As AI algorithms such as Siri and Alexa can process your voice and output helpful responses, other AIs like Face++ can recognize faces. And yet others create art from scribbles, or even diagnose medical conditions.
Let’s dive into AI and convergence.
Top 5 Predictions for AI Breakthroughs (2019-2024)
My friend Neil Jacobstein is my ‘go-to expert’ in AI, with over 25 years of technical consulting experience in the field. Currently the AI and Robotics chair at Singularity University, Jacobstein is also a Distinguished Visiting Scholar in Stanford’s MediaX Program, a Henry Crown Fellow, an Aspen Institute moderator, and serves on the National Academy of Sciences Earth and Life Studies Committee. Neil predicted five trends he expects to emerge over the next five years, by 2024.
AI gives rise to new non-human pattern recognition and intelligence results
AlphaGo Zero, a machine learning computer program trained to play the complex game of Go, defeated the Go world champion in 2016 by 100 games to zero. But instead of learning from human play, AlphaGo Zero trained by playing against itself—a method known as reinforcement learning.
Building its own knowledge from scratch, AlphaGo Zero demonstrates a novel form of creativity, free of human bias. Even more groundbreaking, this type of AI pattern recognition allows machines to accumulate thousands of years of knowledge in a matter of hours.
While these systems can’t answer the question “What is orange juice?” or compete with the intelligence of a fifth grader, they are growing more and more strategically complex, merging with other forms of narrow artificial intelligence. Within the next five years, who knows what successors of AlphaGo Zero will emerge, augmenting both your business functions and day-to-day life.
Doctors risk malpractice when not using machine learning for diagnosis and treatment planning
A group of Chinese and American researchers recently created an AI system that diagnoses common childhood illnesses, ranging from the flu to meningitis. Trained on electronic health records compiled from 1.3 million outpatient visits of almost 600,000 patients, the AI program produced diagnosis outcomes with unprecedented accuracy.
While the US health system does not tout the same level of accessible universal health data as some Chinese systems, we’ve made progress in implementing AI in medical diagnosis. Dr. Kang Zhang, chief of ophthalmic genetics at the University of California, San Diego, created his own system that detects signs of diabetic blindness, relying on both text and medical images.
With an eye to the future, Jacobstein has predicted that “we will soon see an inflection point where doctors will feel it’s a risk to not use machine learning and AI in their everyday practices because they don’t want to be called out for missing an important diagnostic signal.”
Quantum advantage will massively accelerate drug design and testing
Researchers estimate that there are 1060 possible drug-like molecules—more than the number of atoms in our solar system. But today, chemists must make drug predictions based on properties influenced by molecular structure, then synthesize numerous variants to test their hypotheses.
Quantum computing could transform this time-consuming, highly costly process into an efficient, not to mention life-changing, drug discovery protocol.
“Quantum computing is going to have a major industrial impact… not by breaking encryption,” said Jacobstein, “but by making inroads into design through massive parallel processing that can exploit superposition and quantum interference and entanglement, and that can wildly outperform classical computing.”
AI accelerates security systems’ vulnerability and defense
With the incorporation of AI into almost every aspect of our lives, cyberattacks have grown increasingly threatening. “Deep attacks” can use AI-generated content to avoid both human and AI controls.
Previous examples include fake videos of former President Obama speaking fabricated sentences, and an adversarial AI fooling another algorithm into categorizing a stop sign as a 45 mph speed limit sign. Without the appropriate protections, AI systems can be manipulated to conduct any number of destructive objectives, whether ruining reputations or diverting autonomous vehicles.
Jacobstein’s take: “We all have security systems on our buildings, in our homes, around the healthcare system, and in air traffic control, financial organizations, the military, and intelligence communities. But we all know that these systems have been hacked periodically and we’re going to see that accelerate. So, there are major business opportunities there and there are major opportunities for you to get ahead of that curve before it bites you.”
AI design systems drive breakthroughs in atomically precise manufacturing
Just as the modern computer transformed our relationship with bits and information, AI will redefine and revolutionize our relationship with molecules and materials. AI is currently being used to discover new materials for clean-tech innovations, such as solar panels, batteries, and devices that can now conduct artificial photosynthesis.
Today, it takes about 15 to 20 years to create a single new material, according to industry experts. But as AI design systems skyrocket in capacity, these will vastly accelerate the materials discovery process, allowing us to address pressing issues like climate change at record rates. Companies like Kebotix are already on their way to streamlining the creation of chemistries and materials at the click of a button.
Atomically precise manufacturing will enable us to produce the previously unimaginable.
Within just the past three years, countries across the globe have signed into existence national AI strategies and plans for ramping up innovation. Businesses and think tanks have leaped onto the scene, hiring AI engineers and tech consultants to leverage what computer scientist Andrew Ng has even called the new ‘electricity’ of the 21st century.
As AI plays an exceedingly vital role in everyday life, how will your business leverage it to keep up and build forward?
In the wake of burgeoning markets, new ventures will quickly arise, each taking advantage of untapped data sources or unmet security needs.
And as your company aims to ride the wave of AI’s exponential growth, consider the following pointers to leverage AI and disrupt yourself before it reaches you first:
Determine where and how you can begin collecting critical data to inform your AI algorithms
Identify time-intensive processes that can be automated and accelerated within your company
Discern which global challenges can be expedited by hyper-fast, all-knowing minds
Remember: good data is vital fuel. Well-defined problems are the best compass. And the time to start implementing AI is now.
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