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.
Scientists Are Working to Decipher the Puzzle of ‘Broken Heart Syndrome’
Elaine Kamil had just returned home after a few days of business meetings in 2013 when she started having chest pains. At first Kamil, then 66, wasn't worried—she had had some chest pain before and recently went to a cardiologist to do a stress test, which was normal.
"I can't be having a heart attack because I just got checked," she thought, attributing the discomfort to stress and high demands of her job. A pediatric nephrologist at Cedars-Sinai Hospital in Los Angeles, she takes care of critically ill children who are on dialysis or are kidney transplant patients. Supporting families through difficult times and answering calls at odd hours is part of her daily routine, and often leaves her exhausted.
She figured the pain would go away. But instead, it intensified that night. Kamil's husband drove her to the Cedars-Sinai hospital, where she was admitted to the coronary care unit. It turned out she wasn't having a heart attack after all. Instead, she was diagnosed with a much less common but nonetheless dangerous heart condition called takotsubo syndrome, or broken heart syndrome.
A heart attack happens when blood flow to the heart is obstructed—such as when an artery is blocked—causing heart muscle tissue to die. In takotsubo syndrome, the blood flow isn't blocked, but the heart doesn't pump it properly. The heart changes its shape and starts to resemble a Japanese fishing device called tako-tsubo, a clay pot with a wider body and narrower mouth, used to catch octopus.
"The heart muscle is stunned and doesn't function properly anywhere from three days to three weeks," explains Noel Bairey Merz, the cardiologist at Cedar Sinai who Kamil went to see after she was discharged.
"The heart muscle is stunned and doesn't function properly anywhere from three days to three weeks."
But even though the heart isn't permanently damaged, mortality rates due to takotsubo syndrome are comparable to those of a heart attack, Merz notes—about 4-5 percent of patients die from the attack, and 20 percent within the next five years. "It's as bad as a heart attack," Merz says—only it's much less known, even to doctors. The condition affects only about 1 percent of people, and there are around 15,000 new cases annually. It's diagnosed using a cardiac ventriculogram, an imaging test that allows doctors to see how the heart pumps blood.
Scientists don't fully understand what causes Takotsubo syndrome, but it usually occurs after extreme emotional or physical stress. Doctors think it's triggered by a so-called catecholamine storm, a phenomenon in which the body releases too much catecholamines—hormones involved in the fight-or-flight response. Evolutionarily, when early humans lived in savannas or forests and had to either fight off predators or flee from them, these hormones gave our ancestors the needed strength and stamina to take either action. Released by nerve endings and by the adrenal glands that sit on top of the kidneys, these hormones still flood our bodies in moments of stress, but an overabundance of them could sometimes be damaging.
Elaine Kamil
A study by scientists at Harvard Medical School linked increased risk of takotsubo to higher activity in the amygdala, a brain region responsible for emotions that's involved in responses to stress. The scientists believe that chronic stress makes people more susceptible to the syndrome. Notably, one small study suggested that the number of Takotsubo cases increased during the COVID-19 pandemic.
There are no specific drugs to treat takotsubo, so doctors rely on supportive therapies, which include medications typically used for high blood pressure and heart failure. In most cases, the heart returns to its normal shape within a few weeks. "It's a spontaneous recovery—the catecholamine storm is resolved, the injury trigger is removed and the heart heals itself because our bodies have an amazing healing capacity," Merz says. It also helps that tissues remain intact. 'The heart cells don't die, they just aren't functioning properly for some time."
That's the good news. The bad news is that takotsubo is likely to strike again—in 5-20 percent of patients the condition comes back, sometimes more severe than before.
That's exactly what happened to Kamil. After getting her diagnosis in 2013, she realized that she actually had a previous takotsubo episode. In 2010, she experienced similar symptoms after her son died. "The night after he died, I was having severe chest pain at night, but I was too overwhelmed with grief to do anything about it," she recalls. After a while, the pain subsided and didn't return until three years later.
For weeks after her second attack, she felt exhausted, listless and anxious. "You lose confidence in your body," she says. "You have these little twinges on your chest, or if you start having arrhythmia, and you wonder if this is another episode coming up. It's really unnerving because you don't know how to read these cues." And that's very typical, Merz says. Even when the heart muscle appears to recover, patients don't return to normal right away. They have shortens of breath, they can't exercise, and they stay anxious and worried for a while.
Women over the age of 50 are diagnosed with takotsubo more often than other demographics. However, it happens in men too, although it typically strikes after physical stress, such as a triathlon or an exhausting day of cycling. Young people can also get takotsubo. Older patients are hospitalized more often, but younger people tend to have more severe complications. It could be because an older person may go for a jog while younger one may run a marathon, which would take a stronger toll on the body of a person who's predisposed to the condition.
Notably, the emotional stressors don't always have to be negative—the heart muscle can get out of shape from good emotions, too. "There have been case reports of takotsubo at weddings," Merz says. Moreover, one out of three or four takotsubo patients experience no apparent stress, she adds. "So it could be that it's not so much the catecholamine storm itself, but the body's reaction to it—the physiological reaction deeply embedded into out physiology," she explains.
Merz and her team are working to understand what makes people predisposed to takotsubo. They think a person's genetics play a role, but they haven't yet pinpointed genes that seem to be responsible. Genes code for proteins, which affect how the body metabolizes various compounds, which, in turn, affect the body's response to stress. Pinning down the protein involved in takotsubo susceptibility would allow doctors to develop screening tests and identify those prone to severe repeating attacks. It will also help develop medications that can either prevent it or treat it better than just waiting for the body to heal itself.
Researchers at the Imperial College London found that elevated levels of certain types of microRNAs—molecules involved in protein production—increase the chances of developing takotsubo.
In one study, researchers tried treating takotsubo in mice with a drug called suberanilohydroxamic acid, or SAHA, typically used for cancer treatment. The drug improved cardiac health and reversed the broken heart in rodents. It remains to be seen if the drug would have a similar effect on humans. But identifying a drug that shows promise is progress, Merz says. "I'm glad that there's research in this area."
This article was originally published by Leaps.org on July 28, 2021.
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.
Did Anton the AI find a new treatment for a deadly cancer?
Bile duct cancer is a rare and aggressive form of cancer that is often difficult to diagnose. Patients with advanced forms of the disease have an average life expectancy of less than two years.
Many patients who get cancer in their bile ducts – the tubes that carry digestive fluid from the liver to the small intestine – have mutations in the protein FGFR2, which leads cells to grow uncontrollably. One treatment option is chemotherapy, but it’s toxic to both cancer cells and healthy cells, failing to distinguish between the two. Increasingly, cancer researchers are focusing on biomarker directed therapy, or making drugs that target a particular molecule that causes the disease – FGFR2, in the case of bile duct cancer.
A problem is that in targeting FGFR2, these drugs inadvertently inhibit the FGFR1 protein, which looks almost identical. This causes elevated phosphate levels, which is a sign of kidney damage, so doses are often limited to prevent complications.
In recent years, though, a company called Relay has taken a unique approach to picking out FGFR2, using a powerful supercomputer to simulate how proteins move and change shape. The team, leveraging this AI capability, discovered that FGFR2 and FGFR1 move differently, which enabled them to create a more precise drug.
Preliminary studies have shown robust activity of this drug, called RLY-4008, in FGFR2 altered tumors, especially in bile duct cancer. The drug did not inhibit FGFR1 or cause significant side effects. “RLY-4008 is a prime example of a precision oncology therapeutic with its highly selective and potent targeting of FGFR2 genetic alterations and resistance mutations,” says Lipika Goyal, assistant professor of medicine at Harvard Medical School. She is a principal investigator of Relay’s phase 1-2 clinical trial.
Boosts from AI and a billionaire
Traditional drug design has been very much a case of trial and error, as scientists investigate many molecules to see which ones bind to the intended target and bind less to other targets.
“It’s being done almost blindly, without really being guided by structure, so it fails very often,” says Olivier Elemento, associate director of the Institute for Computational Biomedicine at Cornell. “The issue is that they are not sampling enough molecules to cover some of the chemical space that would be specific to the target of interest and not specific to others.”
Relay’s unique hardware and software allow simulations that could never be achieved through traditional experiments, Elemento says.
Some scientists have tried to use X-rays of crystallized proteins to look at the structure of proteins and design better drugs. But they have failed to account for an important factor: proteins are moving and constantly folding into different shapes.
David Shaw, a hedge fund billionaire, wanted to help improve drug discovery and understood that a key obstacle was that computer models of molecular dynamics were limited; they simulated motion for less than 10 millionths of a second.
In 2001, Shaw set up his own research facility, D.E. Shaw Research, to create a supercomputer that would be specifically designed to simulate protein motion. Seven years later, he succeeded in firing up a supercomputer that can now conduct high speed simulations roughly 100 times faster than others. Called Anton, it has special computer chips to enable this speed, and its software is powered by AI to conduct many simulations.
After creating the supercomputer, Shaw teamed up with leading scientists who were interested in molecular motion, and they founded Relay Therapeutics.
Elemento believes that Relay’s approach is highly beneficial in designing a better drug for bile duct cancer. “Relay Therapeutics has a cutting-edge approach for molecular dynamics that I don’t believe any other companies have, at least not as advanced.” Relay’s unique hardware and software allow simulations that could never be achieved through traditional experiments, Elemento says.
How it works
Relay used both experimental and computational approaches to design RLY-4008. The team started out by taking X-rays of crystallized versions of both their intended target, FGFR2, and the almost identical FGFR1. This enabled them to get a 3D snapshot of each of their structures. They then fed the X-rays into the Anton supercomputer to simulate how the proteins were likely to move.
Anton’s simulations showed that the FGFR1 protein had a flap that moved more frequently than FGFR2. Based on this distinct motion, the team tried to design a compound that would recognize this flap shifting around and bind to FGFR2 while steering away from its more active lookalike.
For that, they went back Anton, using the supercomputer to simulate the behavior of thousands of potential molecules for over a year, looking at what made a particular molecule selective to the target versus another molecule that wasn’t. These insights led them to determine the best compounds to make and test in the lab and, ultimately, they found that RLY-4008 was the most effective.
Promising results so far
Relay began phase 1-2 trials in 2020 and will continue until 2024. Preliminary results showed that, in the 17 patients taking a 70 mg dose of RLY-4008, the drug worked to shrink tumors in 88 percent of patients. This was a significant increase compared to other FGFR inhibitors. For instance, Futibatinib, which recently got FDA approval, had a response rate of only 42 percent.
Across all dose levels, RLY-4008 shrank tumors by 63 percent in 38 patients. In more good news, the drug didn’t elevate their phosphate levels, which suggests that it could be taken without increasing patients’ risk for kidney disease.
“Objectively, this is pretty remarkable,” says Elemento. “In a small patient study, you have a molecule that is able to shrink tumors in such a high fraction of patients. It is unusual to see such good results in a phase 1-2 trial.”
A simulated future
The research team is continuing to use molecular dynamic simulations to develop other new drug, such as one that is being studied in patients with solid tumors and breast cancer.
As for their bile duct cancer drug, RLY-4008, Relay plans by 2024 to have tested it in around 440 patients. “The mature results of the phase 1-2 trial are highly anticipated,” says Goyal, the principal investigator of the trial.
Sameek Roychowdhury, an oncologist and associate professor of internal medicine at Ohio State University, highlights the need for caution. “This has early signs of benefit, but we will look forward to seeing longer term results for benefit and side effect profiles. We need to think a few more steps ahead - these treatments are like the ’Whack-a-Mole game’ where cancer finds a way to become resistant to each subsequent drug.”
“I think the issue is going to be how durable are the responses to the drug and what are the mechanisms of resistance,” says Raymond Wadlow, an oncologist at the Inova Medical Group who specializes in gastrointestinal and haematological cancer. “But the results look promising. It is a much more selective inhibitor of the FGFR protein and less toxic. It’s been an exciting development.”