In her quest to become a tech entrepreneur, Stacy Chin has been an ace at tackling thorny intellectual challenges, mastering everything from molecules to manufacturing.
These mostly female leaders of firms with products addressing women's health concerns are winning in a big way, raising about $1.1 billion in startup funds over the past few years.
But the 28-year-old founder of HydroGlyde Coatings, based in Worcester, Mass., admitted to being momentarily stumped recently when pitching her product – a new kind of self-lubricating condom – to venture capitalists.
"Being a young female scientist and going into that sexual healthcare space, it was definitely a little bit challenging to learn how to navigate during presentations and pitches when there were a lot of older males in the audience," said Chin, whose product is of special appeal to older women suffering from vaginal dryness. "I eventually figured it out, but it wasn't easy."
Chin is at the vanguard of a new generation of "femtech" entrepreneurs heading companies with names like LOLA Tampons, Prelude Fertility, and Peach, bringing once-taboo topics like menstruation, ovulation, incontinence, breastfeeding, pelvic pain and, yes, female sexual pleasure to the highest chambers of finance. These mostly female leaders of firms with products addressing women's health concerns are winning in a big way, raising about $1.1 billion in startup funds over the past few years, according to the New York data analytics firm CB Insights.
"We are definitely at a watershed moment for femtech. But we need to remember that [it's] an overnight sensation that is decades in the making."
If the question is "Why now?", the answer may be that femtech leaders are benefiting from the current conversations around respect for women in the workplace, and long-term efforts to achieve gender equality in the male-dominated tech industry.
"We are definitely at a watershed moment for femtech," said Rachel Braun Scherl, a self-described "vaginepreneur" whose new book, "Orgasmic Leadership," profiles femtech leaders. "But we need to remember that femtech is an overnight sensation that is decades in the making."
In contrast with earlier and perhaps less successful generations of women in tech, these pioneers can point to mentors who are readily accessible, as well as more female VC and corporate heads they can directly address when making pitches. There's also a changing cultural landscape where sexual harassment is in the news and women who talk openly about sex in a business context can be taken seriously.
"Change is definitely in the air," said Kevin O'Sullivan, the president and CEO of Massachusetts Biomedical Initiatives, who sponsored Chin and has helped launch more than a hundred biotech companies in his home state since the 1980s.
Like a pinprick bursting a balloon, the #MeToo social movement and its focus on the prevalence of sexual harassment and assault is a factor in the success of femtech, some experts believe, provoking heightened awareness about the role of women in society -- including equal access to start-up capital.
"If such a difficult topic is being discussed in the open, that means more and more people are speaking out and are no longer afraid about sharing their own concerns," said Debbie Hart, president and CEO of BioNJ, a business trade group she founded in 1994. "That's empowering the whole women's movement."
The power of programs that allow young women to witness successful older women in leadership cannot be overstated.
Observers like Hart say that femtech's advent is also due to a payoff from longer-term investments in a slew of programs encouraging girls to pursue STEM careers and women to be hired as leaders, as well as changing social norms to allow female health to be part of the public discourse.
The power of programs that allow young women to witness successful older women in leadership cannot be overstated, according to Susan Scherreik of the Stillman School of Business at Seton Hall University in New Jersey.
"What I have found in entrepreneurship is that it's all about two things: role models and mentoring," said Scherreik, director of the university's Center for Entrepreneurial Studies.
One of Scherreik's top students, Madison Schott, is convinced that the availability of female mentors has been instrumental to her success and will remain so in her future. "It definitely is very encouraging," said Schott, who won the "Pirates Pitch" university-wide business start-up competition in April for an app she is developing that uses AI to guide readers to reliable news sources. "Woman to woman," she added, "you can be more open when you have questions or problems."
Programs that showcase successful females in leadership positions are beginning to bear fruit, inspiring a new generation of females in business, according to Susan Scherreik (at left), director of Seton Hall University's Center for Entrepreneurial Studies at the Stillman School of Business. Her student, Madison Schott (right), is the winner of a university-wide business start-up competition for an app she is developing.
While femtech entrepreneurs may be the beneficiaries of change, they also may be its agents. Scherl, the author, who has been working in the female healthcare sector for more than a decade, believes in persistence. In 2010, organizers of a major awards show banned a product she was marketing, Zestra Essential Arousal Oils*, from a gift bag for honorees. Two years ago, however, times changed and femtech prevailed. The company making goodie bags for Academy Awards nominees included another one of her products, Nuelle's Fiera, a $250 vibrator.
"We come from so many different perspectives when it comes to sex, whether it is cultural, religious, age-related, or even from a trauma, so we never have created a common language," Scherl said. "But we in femtech are making huge progress. We are not only selling products now, we are selling conversation, and we are selling a comfort with sexuality in all its complex forms."
[*Correction: Due to a reporting error, the product that was banned in 2010 was initially identified as Nuelle's Fiera, not Zestra Essential Arousal Oils. The article has been updated for accuracy. --Editor]
The Friday Five covers five stories in health research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
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.”