Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
In Ethiopia, Samuna’s three donkeys help her transport produce to market and to collect the water essential to her family, neighbours and livestock. Donkeys are more endangered than people realize, experts say.
“That's the reason why some breeds begin to disappear because humans were not really interested in having that specific breed anymore,” Gambini says. Nonetheless, in Africa, India and Latin America millions of rural families still rely on these hardy creatures for agriculture and transportation. And the only two wild donkey species—Equus africanus in Africa and Equus hemionus in Asia—are also dwindling, due to losing their habitats to human activities, diseases and slow reproduction rates. Gambini’s team wanted to create a way to preserve the animals for the future. “Donkeys are more endangered than people realize,” he says.
There’s much more to donkeys' trouble though. For the past 20 or so years, they have been facing a huge existential threat due to their hide gelatin, a compound derived from their skins by soaking and stewing. In Chinese traditional medicine, the compound, called ejiao, is believed to have a medicinal value, so it’s used in skin creams, added to food and taken in capsules. Centuries ago, ejiao was a very expensive luxury product available only for the emperor and his household. That changed in the 1990s when the Chinese economy boomed, and many people were suddenly able to afford it. “It went from a very elite product to a very popular product,” says Janneke Merkx, a campaign manager at The Donkey Sanctuary, a United Kingdom-based nonprofit organization that keeps tabs on the animals’ welfare worldwide. “It is a status symbol for gift giving.”
Having evolved in the harsh and arid mountainous terrains where food and water were scarce, donkeys are extremely adaptable and hardy. But the Donkey Sanctuary documented cases in which an entire village had their animals disappear overnight, finding them killed and skinned outside their settlement.
The Chinese donkey population was quickly decimated. Unlike many other farm animals, donkeys are finicky breeders. When stressed and unhappy, they don’t procreate, so growing them in large industrial settings isn’t possible. “Donkeys are notoriously slow breeders and really very difficult to farm,” says Merkx. “They are not the same as other livestock like sheep and pigs and cattle.” Within years the, the donkey numbers in China dropped precipitously. “China used to have the largest donkey population in the world in the 1990s. They had 11 million donkeys, and it's now down to less than 3 million, and they just can't keep up with the demand.”
To keep the ejiao conveyor going, some producers turned to the illegal wildlife trade. Poachers began to steal and slaughter donkeys from rural villages in Africa. The Donkey Sanctuary documented cases in which an entire village had their animals disappear overnight, finding them killed and skinned outside their settlement. Exactly how many creatures were lost to the skin trade to-date isn’t possible to calculate, says Faith Burden, the Donkey Sanctuary’s director of equine operations. Traditionally a poor people’s beast of burden, donkey counts are hard to keep track of. “When an animal doesn't produce meat, milk or eggs or whatever edible product, they're often less likely to be acknowledged in a government population census,” Burden says. “So reliable statistics are hard to come by.” The nonprofit estimates that about 4.8 million are slaughtered annually.
During their six to seven thousand years of domestication, donkeys rarely got the full appreciation for their services. They are often compared to horses, which doesn’t do them justice. They’re entirely different animals, Burden says. Built for speed, horses respond to predators and other dangers by running as fast as they can. Donkeys, which originate from the rocky, mountainous regions of Africa where running is dangerous, react to threats by freezing and assessing the situation for the best response. “Those so-called stubborn donkeys that won’t move as you want, they are actually thinking ‘what’s the best approach,’” Burden says. They may even choose to fight the predators rather than flee, she adds. “In some parts of the world, people use them as guard animals against things like coyotes and wolves.”
Scientists believe that domestic donkeys take their origin from Equus africanus or African wild ass, originally roaming where Kenya, Ethiopia and Eritrea are today. Having evolved in the harsh and arid mountainous terrains where food and water were scarce, they are extremely adaptable and hardy. Research finds that they can go without water for 72 hours and then drink their fill without any negative consequences. Their big jaws let them chew tough desert shrubs, which horses can’t exist on. Their large ears help dissipate heat. Their little upright hooves are a perfect fit for the uneven rocky or other dangerous grounds. Accustomed to the mountain desert climate with hot days and cold nights, they don’t mind temperature flux.
“The donkey is the most supremely adapted animal to deal with hostile conditions,” Burden says. “They can survive on much lower nutritional quality food than a cow, sheep or horse. That’s why communities living in some of the most inhospitable places will often have donkeys with them.” And that’s why losing a donkey to an illegal skin trade can devastate a family in places like Eritrea. Suddenly everything from water to firewood to produce must be carried by family members—and often women.
Workers unloading donkeys at the Shinyanga slaughterhouse in Tanzania. Fearing a future in which donkeys go extinct, scientists have found ways to cryopreserve a donkey embryo in liquid nitrogen.
TAHUCHA
One can imagine a time when worldwide donkey populations may dwindle to the point that they would need to be restored. That includes their genetic variability too. That’s where the frozen embryos may come in handy. We may be able to use them to increase the genetic variability of donkeys, which will be especially important if they get closer to extinction, Gambini says. His team had already created frozen embryos for horses and zebras, an idea similar to a seed bank. “We call this concept the Frozen Zoo.”
Creating donkey embryos proved much harder than those of zebras and horses. To improve chances of fertilization, Gambini used the intracytoplasmic sperm injection or ICSI, in which he employed a tiny needle called a micropipette to inject a donkey sperm into an egg. That was a step above the traditional IVF method, in which the egg and a sperm are left floating in a test tube together. The injection took, but during the incubating week, one after the other, the embryos stopped dividing. Finally, on day seven, Gambini finally spotted the exact sight he was hoping to see. One of the embryos developed into a burgeoning ball of cells.
“That stage is called a blastocyst,” Gambini says. The clump of cells had a lot of fluids mixed within them, which indicated that they were finally developing into a viable embryo. “When we see a blastocyst, we know we can transfer that into a female.” He was so excited he immediately called all his collaborators to tell them the good news, which they later published in the journal of Theriogenology.
The one and only embryo to reach that stage, the blastocyst was cryopreserved in liquid nitrogen. The team is waiting for the next breeding season to see if a female donkey may carry it to term and give birth to a healthy foal. Gambini’s team is hoping to polish the process and create more embryos. “It’s our weapon in the conservation ass-enal,” he says.
