Scientists Want to Make Robots with Genomes that Help Grow their Minds
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
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.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Bacterial antibiotic resistance has been a concern in the medical field for several years. Now a new, similar threat is arising: drug-resistant fungal infections. The Centers for Disease Control and Prevention considers antifungal and antimicrobial resistance to be among the world’s greatest public health challenges.
One particular type of fungal infection caused by Candida auris is escalating rapidly throughout the world. And to make matters worse, C. auris is becoming increasingly resistant to current antifungal medications, which means that if you develop a C. auris infection, the drugs your doctor prescribes may not work. “We’re effectively out of medicines,” says Thomas Walsh, founding director of the Center for Innovative Therapeutics and Diagnostics, a translational research center dedicated to solving the antimicrobial resistance problem. Walsh spoke about the challenges at a Demy-Colton Virtual Salon, one in a series of interactive discussions among life science thought leaders.
Although C. auris typically doesn’t sicken healthy people, it afflicts immunocompromised hospital patients and may cause severe infections that can lead to sepsis, a life-threatening condition in which the overwhelmed immune system begins to attack the body’s own organs. Between 30 and 60 percent of patients who contract a C. auris infection die from it, according to the CDC. People who are undergoing stem cell transplants, have catheters or have taken antifungal or antibiotic medicines are at highest risk. “We’re coming to a perfect storm of increasing resistance rates, increasing numbers of immunosuppressed patients worldwide and a bug that is adapting to higher temperatures as the climate changes,” says Prabhavathi Fernandes, chair of the National BioDefense Science Board.
Most Candida species aren’t well-adapted to our body temperatures so they aren’t a threat. C. auris, however, thrives at human body temperatures.
Although medical professionals aren’t concerned at this point about C. auris evolving to affect healthy people, they worry that its presence in hospitals can turn routine surgeries into life-threatening calamities. “It’s coming,” says Fernandes. “It’s just a matter of time.”
An emerging global threat
“Fungi are found in the environment,” explains Fernandes, so Candida spores can easily wind up on people’s skin. In hospitals, they can be transferred from contact with healthcare workers or contaminated surfaces. Most Candida species aren’t well-adapted to our body temperatures so they aren’t a threat. C. auris, however, thrives at human body temperatures. It can enter the body during medical treatments that break the skin—and cause an infection. Overall, fungal infections cost some $48 billion in the U.S. each year. And infection rates are increasing because, in an ironic twist, advanced medical therapies are enabling severely ill patients to live longer and, therefore, be exposed to this pathogen.
The first-ever case of a C. auris infection was reported in Japan in 2009, although an analysis of Candida samples dated the earliest strain to a 1996 sample from South Korea. Since then, five separate varieties – called clades, which are similar to strains among bacteria – developed independently in different geographies: South Asia, East Asia, South Africa, South America and, recently, Iran. So far, C. auris infections have been reported in 35 countries.
In the U.S., the first infection was reported in 2016, and the CDC started tracking it nationally two years later. During that time, 5,654 cases have been reported to the CDC, which only tracks U.S. data.
What’s more notable than the number of cases is their rate of increase. In 2016, new cases increased by 175 percent and, on average, they have approximately doubled every year. From 2016 through 2022, the number of infections jumped from 63 to 2,377, a roughly 37-fold increase.
“This reminds me of what we saw with epidemics from 2013 through 2020… with Ebola, Zika and the COVID-19 pandemic,” says Robin Robinson, CEO of Spriovas and founding director of the Biomedical Advanced Research and Development Authority (BARDA), which is part of the U.S. Department of Health and Human Services. These epidemics started with a hockey stick trajectory, Robinson says—a gradual growth leading to a sharp spike, just like the shape of a hockey stick.
Another challenge is that right now medics don’t have rapid diagnostic tests for fungal infections. Currently, patients are often misdiagnosed because C. auris resembles several other easily treated fungi. Or they are diagnosed long after the infection begins and is harder to treat.
The problem is that existing diagnostics tests can only identify C. auris once it reaches the bloodstream. Yet, because this pathogen infects bodily tissues first, it should be possible to catch it much earlier before it becomes life-threatening. “We have to diagnose it before it reaches the bloodstream,” Walsh says.
The most alarming fact is that some Candida infections no longer respond to standard therapeutics.
“We need to focus on rapid diagnostic tests that do not rely on a positive blood culture,” says John Sperzel, president and CEO of T2 Biosystems, a company specializing in diagnostics solutions. Blood cultures typically take two to three days for the concentration of Candida to become large enough to detect. The company’s novel test detects about 90 percent of Candida species within three to five hours—thanks to its ability to spot minute quantities of the pathogen in blood samples instead of waiting for them to incubate and proliferate.
Unlike other Candida species C. auris thrives at human body temperatures
Adobe Stock
Tackling the resistance challenge
The most alarming fact is that some Candida infections no longer respond to standard therapeutics. The number of cases that stopped responding to echinocandin, the first-line therapy for most Candida infections, tripled in 2020, according to a study by the CDC.
Now, each of the first four clades shows varying levels of resistance to all three commonly prescribed classes of antifungal medications, such as azoles, echinocandins, and polyenes. For example, 97 percent of infections from C. auris Clade I are resistant to fluconazole, 54 percent to voriconazole and 30 percent of amphotericin. Nearly half are resistant to multiple antifungal drugs. Even with Clade II fungi, which has the least resistance of all the clades, 11 to 14 percent have become resistant to fluconazole.
Anti-fungal therapies typically target specific chemical compounds present on fungi’s cell membranes, but not on human cells—otherwise the medicine would cause damage to our own tissues. Fluconazole and other azole antifungals target a compound called ergosterol, preventing the fungal cells from replicating. Over the years, however, C. auris evolved to resist it, so existing fungal medications don’t work as well anymore.
A newer class of drugs called echinocandins targets a different part of the fungal cell. “The echinocandins – like caspofungin – inhibit (a part of the fungi) involved in making glucan, which is an essential component of the fungal cell wall and is not found in human cells,” Fernandes says. New antifungal treatments are needed, she adds, but there are only a few magic bullets that will hit just the fungus and not the human cells.
Research to fight infections also has been challenged by a lack of government support. That is changing now that BARDA is requesting proposals to develop novel antifungals. “The scope includes C. auris, as well as antifungals following a radiological/nuclear emergency, says BARDA spokesperson Elleen Kane.
The remaining challenge is the number of patients available to participate in clinical trials. Large numbers are needed, but the available patients are quite sick and often die before trials can be completed. Consequently, few biopharmaceutical companies are developing new treatments for C. auris.
ClinicalTrials.gov reports only two drugs in development for invasive C. auris infections—those than can spread throughout the body rather than localize in one particular area, like throat or vaginal infections: ibrexafungerp by Scynexis, Inc., fosmanogepix, by Pfizer.
Scynexis’ ibrexafungerp appears active against C. auris and other emerging, drug-resistant pathogens. The FDA recently approved it as a therapy for vaginal yeast infections and it is undergoing Phase III clinical trials against invasive candidiasis in an attempt to keep the infection from spreading.
“Ibreafungerp is structurally different from other echinocandins,” Fernandes says, because it targets a different part of the fungus. “We’re lucky it has activity against C. auris.”
Pfizer’s fosmanogepix is in Phase II clinical trials for patients with invasive fungal infections caused by multiple Candida species. Results are showing significantly better survival rates for people taking fosmanogepix.
Although C. auris does pose a serious threat to healthcare worldwide, scientists try to stay optimistic—because they recognized the problem early enough, they might have solutions in place before the perfect storm hits. “There is a bit of hope,” says Robinson. “BARDA has finally been able to fund the development of new antifungal agents and, hopefully, this year we can get several new classes of antifungals into development.”
New elevators could lift up our access to space
Story by Big Think
When people first started exploring space in the 1960s, it cost upwards of $80,000 (adjusted for inflation) to put a single pound of payload into low-Earth orbit.
A major reason for this high cost was the need to build a new, expensive rocket for every launch. That really started to change when SpaceX began making cheap, reusable rockets, and today, the company is ferrying customer payloads to LEO at a price of just $1,300 per pound.
This is making space accessible to scientists, startups, and tourists who never could have afforded it previously, but the cheapest way to reach orbit might not be a rocket at all — it could be an elevator.
The space elevator
The seeds for a space elevator were first planted by Russian scientist Konstantin Tsiolkovsky in 1895, who, after visiting the 1,000-foot (305 m) Eiffel Tower, published a paper theorizing about the construction of a structure 22,000 miles (35,400 km) high.
This would provide access to geostationary orbit, an altitude where objects appear to remain fixed above Earth’s surface, but Tsiolkovsky conceded that no material could support the weight of such a tower.
We could then send electrically powered “climber” vehicles up and down the tether to deliver payloads to any Earth orbit.
In 1959, soon after Sputnik, Russian engineer Yuri N. Artsutanov proposed a way around this issue: instead of building a space elevator from the ground up, start at the top. More specifically, he suggested placing a satellite in geostationary orbit and dropping a tether from it down to Earth’s equator. As the tether descended, the satellite would ascend. Once attached to Earth’s surface, the tether would be kept taut, thanks to a combination of gravitational and centrifugal forces.
We could then send electrically powered “climber” vehicles up and down the tether to deliver payloads to any Earth orbit. According to physicist Bradley Edwards, who researched the concept for NASA about 20 years ago, it’d cost $10 billion and take 15 years to build a space elevator, but once operational, the cost of sending a payload to any Earth orbit could be as low as $100 per pound.
“Once you reduce the cost to almost a Fed-Ex kind of level, it opens the doors to lots of people, lots of countries, and lots of companies to get involved in space,” Edwards told Space.com in 2005.
In addition to the economic advantages, a space elevator would also be cleaner than using rockets — there’d be no burning of fuel, no harmful greenhouse emissions — and the new transport system wouldn’t contribute to the problem of space junk to the same degree that expendable rockets do.
So, why don’t we have one yet?
Tether troubles
Edwards wrote in his report for NASA that all of the technology needed to build a space elevator already existed except the material needed to build the tether, which needs to be light but also strong enough to withstand all the huge forces acting upon it.
The good news, according to the report, was that the perfect material — ultra-strong, ultra-tiny “nanotubes” of carbon — would be available in just two years.
“[S]teel is not strong enough, neither is Kevlar, carbon fiber, spider silk, or any other material other than carbon nanotubes,” wrote Edwards. “Fortunately for us, carbon nanotube research is extremely hot right now, and it is progressing quickly to commercial production.”Unfortunately, he misjudged how hard it would be to synthesize carbon nanotubes — to date, no one has been able to grow one longer than 21 inches (53 cm).
Further research into the material revealed that it tends to fray under extreme stress, too, meaning even if we could manufacture carbon nanotubes at the lengths needed, they’d be at risk of snapping, not only destroying the space elevator, but threatening lives on Earth.
Looking ahead
Carbon nanotubes might have been the early frontrunner as the tether material for space elevators, but there are other options, including graphene, an essentially two-dimensional form of carbon that is already easier to scale up than nanotubes (though still not easy).
Contrary to Edwards’ report, Johns Hopkins University researchers Sean Sun and Dan Popescu say Kevlar fibers could work — we would just need to constantly repair the tether, the same way the human body constantly repairs its tendons.
“Using sensors and artificially intelligent software, it would be possible to model the whole tether mathematically so as to predict when, where, and how the fibers would break,” the researchers wrote in Aeon in 2018.
“When they did, speedy robotic climbers patrolling up and down the tether would replace them, adjusting the rate of maintenance and repair as needed — mimicking the sensitivity of biological processes,” they continued.Astronomers from the University of Cambridge and Columbia University also think Kevlar could work for a space elevator — if we built it from the moon, rather than Earth.
They call their concept the Spaceline, and the idea is that a tether attached to the moon’s surface could extend toward Earth’s geostationary orbit, held taut by the pull of our planet’s gravity. We could then use rockets to deliver payloads — and potentially people — to solar-powered climber robots positioned at the end of this 200,000+ mile long tether. The bots could then travel up the line to the moon’s surface.
This wouldn’t eliminate the need for rockets to get into Earth’s orbit, but it would be a cheaper way to get to the moon. The forces acting on a lunar space elevator wouldn’t be as strong as one extending from Earth’s surface, either, according to the researchers, opening up more options for tether materials.
“[T]he necessary strength of the material is much lower than an Earth-based elevator — and thus it could be built from fibers that are already mass-produced … and relatively affordable,” they wrote in a paper shared on the preprint server arXiv.
After riding up the Earth-based space elevator, a capsule would fly to a space station attached to the tether of the moon-based one.
Electrically powered climber capsules could go up down the tether to deliver payloads to any Earth orbit.
Adobe Stock
Some Chinese researchers, meanwhile, aren’t giving up on the idea of using carbon nanotubes for a space elevator — in 2018, a team from Tsinghua University revealed that they’d developed nanotubes that they say are strong enough for a tether.
The researchers are still working on the issue of scaling up production, but in 2021, state-owned news outlet Xinhua released a video depicting an in-development concept, called “Sky Ladder,” that would consist of space elevators above Earth and the moon.
After riding up the Earth-based space elevator, a capsule would fly to a space station attached to the tether of the moon-based one. If the project could be pulled off — a huge if — China predicts Sky Ladder could cut the cost of sending people and goods to the moon by 96 percent.
The bottom line
In the 120 years since Tsiolkovsky looked at the Eiffel Tower and thought way bigger, tremendous progress has been made developing materials with the properties needed for a space elevator. At this point, it seems likely we could one day have a material that can be manufactured at the scale needed for a tether — but by the time that happens, the need for a space elevator may have evaporated.
Several aerospace companies are making progress with their own reusable rockets, and as those join the market with SpaceX, competition could cause launch prices to fall further.
California startup SpinLaunch, meanwhile, is developing a massive centrifuge to fling payloads into space, where much smaller rockets can propel them into orbit. If the company succeeds (another one of those big ifs), it says the system would slash the amount of fuel needed to reach orbit by 70 percent.
Even if SpinLaunch doesn’t get off the ground, several groups are developing environmentally friendly rocket fuels that produce far fewer (or no) harmful emissions. More work is needed to efficiently scale up their production, but overcoming that hurdle will likely be far easier than building a 22,000-mile (35,400-km) elevator to space.