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.”
As gene therapies and small molecule drugs are being studied in clinical trials, companies increasingly see the value in hiring patients to help explain the potential benefits.
Biomedical corporations and government research agencies are now incorporating patient advocacy more than ever, says Alice Lara, president and CEO of the Sudden Arrhythmia Death Syndromes Foundation in Salt Lake City, Utah. These organizations have seen the effectiveness of including patient voices to communicate and exemplify the benefits that key academic research institutions have shown in their medical studies.
“From our side of the aisle,” Lara says, “what we know as patient advocacy organizations is that educated patients do a lot better. They have a better course in their therapy and their condition, and understanding the genetics is important because all of our conditions are genetic.”
Founded in 2016, Tenaya is advancing gene therapies and small molecule drugs in clinical trials for both prevalent and rare forms of heart disease, says Ali, the CEO.
The firm's first small molecule, now in a Phase 1 clinical trial, is intended to treat heart failure with preserved ejection fraction, where the amount of blood pumped by the heart is reduced due to the heart chambers becoming weak or stiff. The condition accounts for half or more of all heart failure in the U.S., according to Ali, and is growing quickly because it's closely associated with diabetes. It’s also linked with metabolic syndrome, or a cluster of conditions including high blood pressure, high blood sugar, excess body fat around the waist, and abnormal cholesterol levels.
“We have a novel molecule that is first in class and, to our knowledge, best in class to tackle that, so we’re very excited about the clinical trial,” Ali says.
The first phase of the trial is being performed with healthy participants, rather than people with the disease, to establish safety and tolerability. The researchers can also look for the drug in blood samples, which could tell them whether it's reaching its target. Ali estimates that, if the company can establish safety and that it engages the right parts of the body, it will likely begin dosing patients with the disease in 2024.
Tenaya’s therapy delivers a healthy copy of the gene so that it makes a copy of the protein missing from the patients' hearts because of their mutation. The study will start with adult patients, then pivot potentially to children and even newborns, Ali says, “where there is an even greater unmet need because the disease progresses so fast that they have no options.”
Although this work still has a long way to go, Ali is excited about the potential because the gene therapy achieved positive results in the preclinical mouse trial. This animal trial demonstrated that the treatment reduced enlarged hearts, reversed electrophysiological abnormalities, and improved the functioning of the heart by increasing the ejection fraction after the single-dose of gene therapy. That measurement remained stable to the end of the animals’ lives, roughly 18 months, Ali says.
He’s also energized by the fact that heart disease has “taken a page out of the oncology playbook” by leveraging genetic research to develop more precise and targeted drugs and gene therapies.
“Now we are talking about a potential cure of a disease for which there was no cure and using a very novel concept,” says Melind Desai of the Cleveland Clinic.
Tenaya’s second program focuses on developing a gene therapy to mitigate the leading cause of hypertrophic cardiomyopathy through a specific gene called MYPBC3. The disease affects approximately 600,000 patients in the U.S. This particular genetic form, Ali explains, affects about 115,000 in the U.S. alone, so it is considered a rare disease.
“There are infants who are dying within the first weeks to months of life as a result of this mutation,” he says. “There are also adults who start having symptoms in their 20s, 30s and 40s with early morbidity and mortality.” Tenaya plans to apply before the end of this year to get the FDA’s approval to administer an investigational drug for this disease humans. If approved, the company will begin to dose patients in 2023.
“We now understand the genetics of the heart much better,” he says. “We now understand the leading genetic causes of hypertrophic myopathy, dilated cardiomyopathy and others, so that gives us the ability to take these large populations and stratify them rationally into subpopulations.”
Melind Desai, MD, who directs Cleveland Clinic’s Hypertrophic Cardiomyopathy Center, says that the goal of Tenaya’s second clinical study is to help improve the basic cardiac structure in patients with hypertrophic cardiomyopathy related to the MYPBC3 mutation.
“Now we are talking about a potential cure of a disease for which there was no cure and using a very novel concept,” he says. “So this is an exciting new frontier of therapeutic investigation for MYPBC3 gene-positive patients with a chance for a cure.
Neither of Tenaya’s two therapies address the gene mutation that has affected Borsari and her family. But Ali sees opportunity down the road to develop a gene therapy for her particular gene mutation, since it is the second leading cause of cardiomyopathy. Treating the MYH7 gene is especially challenging because it requires gene editing or silencing, instead of just replacing the gene.
Wendy Borsari was diagnosed at age 24 with a commonly inherited heart disease. She joined Tenaya as a patient advocate in 2021.
Wendy Borsari
“If you add a healthy gene it will produce healthy copies,” Ali explains, “but it won’t stop the bad effects of the mutant protein the gene produces. You can only do that by silencing the gene or editing it out, which is a different, more complicated approach.”
Euan Ashley, professor of medicine and genetics at Stanford University and founding director of its Center for Inherited Cardiovascular Disease, is confident that we will see genetic therapies for heart disease within the next decade.
“We are at this really exciting moment in time where we have diseases that have been under-recognized and undervalued now being attacked by multiple companies with really modern tools,” says Ashley, author of The Genome Odyssey. “Gene therapies are unusual in the sense that they can reverse the cause of the disease, so we have the enticing possibility of actually reversing or maybe even curing these diseases.”
Although no one is doing extensive research into a gene therapy for her particular mutation yet, Borsari remains hopeful, knowing that companies such as Tenaya are moving in that direction.
“I know that’s now on the horizon,” she says. “It’s not just some pipe dream, but will happen hopefully in my lifetime or my kids’ lifetime to help them.”