Is a customer who has been gone a few months a lost cause? Not according to Alan Ringvald, SF ’16, founder and CEO of the startup Relativity6. Ringvald believes that the time lapsed is not actually the most helpful metric. The focus, he says, should be less on how long they’ve been gone and more on why they went and what you need to do to get them back.
Ringvald and company cofounder and CTO Abraham Rodriguez, SF ’16, share a long obsession with decoding the behavior of lapsed customers. The seasoned entrepreneurs launched Relativity6 while collaborating on their Sloan Fellows’ master’s thesis, which explored the reactivation of unresponsive customers. Their research points to one silver bullet: machine learning. “We are trying to teach a machine to think like a human, to conclude from a customer’s past purchasing actions when and what they might purchase next.”
Relativity6 looks for the hidden variables that will reveal why a customer has been inactive. “Companies lose a lot of customers, and they won’t get them all back. We’re looking for the ones with the highest likelihood of returning. We examine customers’ historical transactions and purchasing behavior. Over time, we find behavioral similarities.”
Not your grandmother’s demographics
Ringvald also believes that the marketplace has been guilty of an over-reliance on demographics. “Our culture is no longer so rigidly segmented by age. Game of Thrones might be the favorite TV show of a 25-year-old student in Michigan and a 70-year-old retiree in San Diego—and both might have downloaded a related feature. Their shared interests may well be more illuminating than their disparate ages when analyzing purchasing trends.”
Relativity6 is poised to help any organization with a sufficient customer database that has been collecting data for more than two or three years. The founders are so confident in their premise that they set up the company using a pay-by-performance model, reducing the risk for prospective customers. Establishing a 90 percent accuracy rate hasn’t hurt either, nor does the 5 percent average increase in revenue streams they’ve been delivering. And the model works as well for business-to-business as it does for business-to-consumer challenges.
Although a young company, Relativity6 has worked with small businesses and mega-companies representing a wide range of markets, including retailers, financial institutions, insurance agencies, hospitals, political organizations, universities, and nonprofits. NutraClick, a technology-driven company that provides leading health and wellness products, engaged Relativity6 to reactivate subscription customers and tripled their ROI in just one month.
The startup’s MIT roots run deep. In addition to Ringvald and Rodriguez, the team includes two additional Sloan Fellows alumni, Silvana Lopez Diaz, SF ’16, and Aaron Howell, SF ’15. MIT Sloan professor Duncan Simester sits on the board. MIT’s Industrial Liaison Program and the MIT Sandbox Innovation Fund have provided pivotal support.
Every day, four thousand children die because they don’t have access to clean water. That stark fact is what drove the winning innovation at this year’s MIT $100K Entrepreneurship Competition on May 14. “The water crisis is only getting worse,” says Maher Damak, PhD ’17, cofounder of Infinite Cooling, the grand-prize winner. “Our mission is to help solve the water crisis and save power plants $10 billion a year.”
Nearly 40 percent of all the water drawn from lakes and rivers in the United States goes to thermoelectric power plants. Water is continuously dumped into cooling towers, where some evaporates to cool the remaining water. A 250-megawatt power plant spends $5 million on water every year and consumes an amount equivalent to 100,000 residential users.
Infinite Cooling is developing a system—based on Damak’s mechanical engineering thesis—that captures and recycles the vaporized water from thermoelectric power plants. The recycled water would be reused continuously in the plant’s cooling system
saving millions of gallons—and dollars—annually. The team estimates that its collector could capture 80 percent of the liquid water droplets in the air and cut a power plant’s water consumption by 20 to 30 percent. And the newly potable water could be shipped to water-scarce areas.
2018 Clean Energy Prize winner
Backed, in part, by funding from the MIT Tata Center for Technology and some of the country’s leading startup competitions—including the Clean Energy Prize—Infinite Cooling has developed a system that can be retrofitted on top of cooling towers, where it captures escaping water vapor. The system also eliminates the need for treating the water with thousands of gallons of chemicals before it’s recycled.
Cofounder and co-inventor Karim Khalil, PhD ’17, noted that because their device is able to collect this pure, recondensed water, “not only do we reduce the evaporated losses, but also [reduce] costly water-treatment requirements.” The startup is planning a seed round by the end of the year and a Series A in 2020. It is also exploring applications of its technology in refineries and chemical plants.
Now in its 29th year, MIT’s iconic entrepreneurship competition is run by MIT students and supported by the Martin Trust Center for MIT Entrepreneurship and the MIT Sloan School of Management. In the final round, eight teams pitched concepts to a crowded audience and to a judging panel of entrepreneurs and industry experts. Steve Conine, cofounder and co-chairman of e-commerce giant Wayfair was the keynote speaker.
If you’re tracking what you eat with a calorie-counting app, you’re only fulfilling one narrow aspect of nutritional health. A new app in development at CSAIL (MIT’s Computer Science and Artificial Intelligence Lab) takes a more in-depth approach to meal monitoring. Researchers Jim Glass and Mandy Korpusik lead a team that has developed a nutrition analyzer that uses pioneering speech and language understanding technology to track dietary intake more easily and efficiently than popular apps like MyFitnessPal.
They envision that the consumer will sit down at the breakfast table, for example, and simply speak or write a sentence describing the meal in their natural language: “Good morning, I have just finished eating a bowl of Kellogg’s corn flakes.” The system will automatically determine the corresponding nutrient database entries: “cereals; ready-to-eat; Kellogg’s; Kellogg’s Corn Flakes” and processes quantities: “a bowl.”
The team is exploring dialogue mechanisms that will allow the app to quiz the consumer on important details of the meal: “Did you use whole, two-percent, or nonfat milk?” The app then could provide personalized nutrition advice, perhaps noting the nutritional benefits of two-percent over whole milk and mentioning the fiber content (or lack thereof) of corn flakes.
Using AI to advance healthcare
The new app is the undertaking of the Spoken Language Systems Group at CSAIL, which is led by Glass. The goal of the project is part of the group’s larger mission—to create technology that makes it possible for everyone in the world to interact with computers via natural spoken language. SLS researchers believe that conversational interfaces will enable people to converse with machines much in the same way that we converse with one another and will play a fundamental role in advancing our information-based society.
As always, of course, motivation is key to following advice of any kind, human or machine, but researchers are banking on the fact that an easy, conversational app will be an incentive to use.
The Spoken Language Systems Group is using speech and language understanding technology in other healthcare realms as well. The group is working to extract and identify audio and text features from recordings of 5,000 subjects undergoing neuropsychological evaluations collected over the last 10 years to identify language characteristics that are the most predictive of cognitive impairment diseases like Alzheimer’s and dementia.
Language, these researchers feel, could be the password to many frontiers, and healthcare is among the most crucial for improving the human condition.
Many consumers look at their car insurance choices and see an MC Escher drawing of mazes leading into the unknown. Using advanced artificial intelligence, however, Insurify is streamlining the historically convoluted process. Winner of the 2016 ACORD Insurance Innovation Challenge Startup Disruptor, the company has wowed industry traditionalists and customers alike with its reinvention of the client experience.
Entrepreneurs have attempted to tackle the insurance industry before, but no new venture in this space has taken off as robustly as Insurify. “Insurance—the industry that nobody wanted to touch for generations—is now super hot,” says Snejina Zacharia, SF ’13, founder and CEO. “Because it’s a data-driven industry, it can be transformed by the inspired use of artificial intelligence.”
Only four-years old, the company is now the largest insurance marketplace in the US, growing profitably with two million customers and a 42% increase in closed policies month after month. Its virtual insurance agent uses AI and natural language processing to simplify the shopping experience, creating a virtual insurance agent who delivers a quote in under three minutes—by far, the fastest tool in the industry.
Zacharia and her team opted not to develop an app, given the infrequency with which people make decisions about insurance. Instead, customers simply text a photo of their license plate and converse with a well-informed bot. Messaging is personal and asynchronous. Consumers can initiate and complete the transaction while watching television or waiting in line for take-out.
Educating robots to become super agents
Insurify has partnered with the largest agencies in the country and is available in 48 states. Its bots are able to quote 102 insurance carriers in real time with more than 800 agents working on the platform. The advanced recommendation engine helps customers select the best coverage for their needs given their personal risk profiles.
Insurify’s mobile-first platform is powered by advanced analytics that continuously optimize the user experience. That platform is the work of a remarkably adept and experienced team, which includes key talent from top tech companies. Cofounder Giorgos Zacharia, for example, holds a handful of MIT degrees and was the chief technology officer at Kayak.
“The goal of this technical dream team,” says Zacharia, “is to educate our robots so well that they can take—and ace—the insurance licensing exam. Basically, we are developing the brain of a super agent, a super agent who is getting smarter every day.”
More women are entering science and tech-related fields than ever before, but the number occupying the executive suite still lags far behind men. The Massachusetts Life Sciences Center (MLSC) and Takeda Pharmaceuticals have launched a new initiative to help right the balance. MassNextGen is a five-year program that will fund and support early stage biotech companies run by women.
A recent report by the Massachusetts Biotechnology Council (MassBio) and the executive recruiting firm Liftstream found growing gender disparities in the state’s life-sciences industry. The report integrated the responses of 70 companies and more than 900 professionals and revealed that while women enter the industry in equal proportion to men, their numbers decline in the early stages of their careers. As a result, they account for just 24 percent of C-suite executives in biotech—the gap is even greater at the board level. Between 2011 and 2013, only 15% of the companies receiving venture capital investment included a woman on the executive team.
A support system for women founders and leaders
The cause of this disparity? The report notes fewer opportunities to advance, a perceived bias in evaluations and promotions, and a paucity of opportunities for mentoring and career development. Jennifer Griffin, Vice President for Industry Programs and Relations at MLSP, says MassNextGen will “encourage and support more women entrepreneurs in the life sciences industry and provide them with the skills, the tools, and the network they need to go out and successfully raise funds for their small, innovative companies.”
Seed stage money is the hardest for women executives to come by. Only 3% of the total venture capital dollars in the U.S. went to companies with a woman CEO, according to “Women Entrepreneurs 2014: Bridging the Gender Gap in Venture Capital,” a report produced by Babson College in 2014. To address this issue, MassNextGen will support annually two women-owned companies with $50,000 and executive coaching that will include mentoring and access to a network of entrepreneurs, investors, and industry experts.
Catalyst for change
Takeda was the first private partner to support the program. The pharma giant provided $250,000 in support to match MLSC’s $250,000. “It’s one initiative,” Takeda CEO Christophe Weber noted at the launch of the initiative, “but it creates some visibility and allows us to express our willingness to improve the situation.”
Griffin’s intention is that MassNextGen will prove to be a catalyst for change over time. “We’re targeting young entrepreneurs, but certainly those women entrepreneurs will someday become board members of larger companies and advise those companies.”
What are the stumbling blocks of blockchain? How can AI strengthen cybersecurity? Are cryptocurrencies the future of the marketplace? Members of the MIT Sloan faculty bring in-depth discussion of these pivotal fintech issues—and a good many more—to Buenos Aires at the end of this month. The MIT Sloan Latin America Office in collaboration with the Institute for Business Development of Argentina (IDEA) will hold a summit called “Transforming the Fintech Revolution” at the Hilton Buenos Aires on Tuesday, May 29.
The all-day conference will spotlight emerging trends in financial technology and examine how fintech inventions are turning global commerce upside down. MIT Sloan Professor of Applied Economics, Roberto Rigobon, faculty director of the MIT Sloan Latin American Office, has been a key force in organizing the event. “Over the past decade,” he says, “fintech has emerged as one of the fastest-growing sectors in the technology industry and today is at the forefront of innovation.” The goal of the conference, he added, is to “shine a light on the promise of fintech to lead to more transparent, secure, and inclusive financial services for millions around the world.”
Rigobon and his team expect the conference to draw hundreds of business leaders, policymakers, regulators, academics, and entrepreneurs from across Latin America. The event will include presentations and workshops led by leading economists, computer scientists, and development experts. The faculty contingent from MIT includes Rigobon, applied economics professor Tavneet Suri, engineering professor Silvio Micali, information engineering professor John Williams, and Christian Catalini from MIT Sloan’s Technological Innovation, Entrepreneurship, and Strategic Management (TIES) Program.
The evolution of fintech
The conference, Rigobon says, will showcase “the most current and cutting-edge fintech applications and charts a course for its future evolution in Latin America and beyond.” Fintech, he notes, “is about using technology to solve pressing financial problems. This includes everything from helping investors make better decisions on where to put their money, to employing data analytics to drive business efficiency, to accelerating entrepreneurship through blockchain, to expanding the use of mobile payments in the developing world to make the economic system more fair.”
Transforming the Fintech Revolution’s packed agenda includes such topics as Cyber Security and The Future Web; AI Applied Now; Fintech and Argentina; Some Simple Economics of Blockchain; Digital Finance and Economic Lives in Africa; Fintech and Financial Regulation; Why Blockchain is the Key for Financial Inclusion; and Fin Tech: Solving the Macro Development Problems.
According to the National Kidney Foundation, thirteen people die every day while awaiting a kidney transplant. More than 3,000 new patients are added to the waiting list every month—a new name every 14 minutes. But the length of the waiting list and the insufficient supply aren’t the only issues in those deaths. The entire system is slowed by a time-consuming decision-making process that relies on individual discernment. “Who might be best suited to this kidney?” “Is this kidney the best possible match?” “Will a better match be coming in the next few months?”
Dimitris Bertsimas, the Boeing Leaders for Global Operations Professor of Management and the co-director of the MIT Sloan Operations Research Center, is cutting through red tape with an elegant algorithm designed to streamline the waiting list process, getting the right kidney to the right recipient in the shortest amount of time. In a new paper, he and MIT Sloan Assistant Professor of Operations Management Nikos Trichakis describe a pioneering model that applies machine-learning to historical data about all kidney transplants over the last decade to guide future donations.
At present, when a kidney is offered to a wait-listed candidate, the decision to accept or decline the organ relies primarily upon a surgeon’s experience and intuition. The physician might take into consideration the location and condition of the kidney. And might there be a higher-quality kidney or a better match available in the future? The authors maintain that the current experience-based paradigm lacks scientific rigor and is subject to the inaccuracies that plague anecdotal decision-making. As a result, as many as 20% of all kidneys obtained are discarded as unsuitable—when, in fact, they might well have been the best option.
Bertsimas’ and Trichakis’ data-driven analytics-based model predicts whether a patient will receive an offer for a deceased-donor kidney at KDPI thresholds of 0.2, 0.4, and 0.6, and at time frames of 3, 6, and 12 months. The model accounts for OPO, blood group, wait time, DR antigens, and prior offer history to provide accurate and personalized predictions. They tested datasets spanning various lengths of time to understand the adaptability of the method.
The pair is working with surgeons at Massachusetts General Hospital to create a support tool that leverages their model. They hope to give surgeons a reality check about kidneys, providing them with hard evidence of whether they can realistically expect a better donation if they decline a kidney—ultimately reducing the number of kidneys that are discarded because physicians are pessimistic about the match.
Erik Brynjolfsson, Schussel Family Professor of Management and director of the MIT Initiative on the Digital Economy, and Andrew McAfee, principle research scientist at the MIT Center for Digital Business, urge us to move beyond questions of what technology will do to us and instead ask: What do we want to do with technology? What matters more than ever before, they say, is thinking deeply about what we want the future to be. Having more choices means that our values are more important than ever.
Fredric Abramson, SF ’77, has an extensive background in genetics, biology, entrepreneurship, and the law. All paths converge at his most recent startup, Digital Nutrition, which is using AI and genetics to revolutionize the concept of illness prevention.
Abramson is building Digital Nutrition, still in its startup phase, to be a $100 million-dollar-business that taps the very latest genetic science and technology to promote wellness and wellbeing. “With advanced AI and machine learning analytics,” he says, “we can deliver genetic data tools that will improve the life of anyone who uses our app.”
The idea: shape preventive health behavior with DNA-based personal nutrition feedback using a simple phone app. Well, maybe not so simple—at least in what’s behind the firewall—but the app itself, as Abramson’s team is creating it, will be second nature for the consumer. “The world is moving more and more toward personalization, and that’s not going to change—nor should it. Digital Nutrition is the ultimate in personalization. It puts consumers in touch with their genetic roots and coaches them on how to make choices based on that information.”
The mobile app is designed to be a sort of digital nutritionist, allowing users to identify the foods and supplements that are optimal for their own genetic makeups based on a simple swab DNA test. They will be able to scan bar codes from food, beverage, or supplement packages and receive an instant AI-generated score that reflects how well the ingredients match their genetic profile in terms of metabolism, physiology, and neurology.
A very personal nutrition app
What will set this platform apart is the science behind the app’s affable interface. Digital Nutrition will tap the massive amount of published genetic science to map areas where genetic data can have a positive impact on a user’s quality of life. “In effect, we are using technology to deliver deep science to the average person. The app will be an exceptionally brainy weight-loss coach, fitness guru, and counselor rolled into one. Eventually, as the Digital Nutrition app is adopted on a global scale, we envision that the marketplace will respond by developing nutritional products that work in concert with it, strengthening and broadening its ability to serve consumers.”
The company is actually a business unit of Abramson’s other enterprise AlphaGenics, the first bio-consumer company to exclusively use non-medical genetic data to provide lifestyle solutions. The field has been a driving interest of Abramson’s for nearly two decades. In 2002, he was the sole U.S. representative invited to participate in the European Union’s first framework meeting on nutrigenomics.
Digital Nutrition will allow consumers on a much larger scale to leverage their genetic blueprint for optimal health. “We’re talking about a low-cost scalable app that can improve the nutritional and health status of people worldwide, including populations in developing economies,” Abramson says. “It’s time we employ science to deliver better health, wellness, and wellbeing for everyone on this planet. That goal is just a DNA app away from reality.”
Companies that know how to harness machine learning and artificial intelligence are clear winners in the 21st century economy. And, arguably, few companies on Earth rival Google for its ingenuity in unlocking their powers. Suzanne Frey, SF ’06, Director of Security, Trust, and Privacy at Google, says, in fact, that every area in which Google is advancing relies on the progress of AI and ML.
Frey says that a game-changer was Google’s 2014 acquisition of the London-based AI pioneer DeepMind. Now a world leader in artificial intelligence research, DeepMind is developing programs that can learn to solve complex problems without necessarily needing to be taught how. Working closely with subject experts, DeepMind researchers are building tools that augment advances in fields such as healthcare and energy. And, of course, it’s tapping its late-breaking knowledge to enhance Google’s own products and services.
Frey says that DeepMind’s capabilities were best demonstrated recently on the virtual playing field. “The work we’ve done with DeepMind really went big when we won a pivotal GO match against the #1 champion in the world, an accomplishment that most thought was a decade out on the computer science horizon.” Big deal…just a game? Frey explains why not. “In winning that match, DeepMind illustrated the ability to run an exceptional number of deeply complex scenarios in parallel, at scale, and select the best outcome. And that capability is applicable to so many domains—the biosciences, in particular, allowing biotech researchers to do drug testing and create genetic scenarios at scale without testing on animals. Bottom line: the implications of that winning game of GO could have enormous positive impacts on society.”
As a time-challenged tech executive, Frey is understandably somewhat obsessed with time-saving apps. “My twin passions for AI and time collide heavily at Google. Anything that saves time and optimizes energy is important. Google, she says, is using AI to create a suite of indispensable apps like Smart Reply in Gmail, which offers you quick responses to choose from so that you don’t have to compose a message from scratch. Another app will note a meeting on your calendar and queue up related documents in preparation. All these little inventions, Frey says, can save a minute here, five minutes there, minutes that add up by the end of a given day. “Nothing is more precious than time; just think about the total area under the curve saved by each of these features, and I’m excited to say that there’s much more time savings to come.”
On the educational horizon, Frey reports that Google’s search functions have advanced to such an extent that a Google search is almost akin to having a research assistant. Google Scholar helps students find relevant resources across the world of academic research, pulling in articles, theses, books, and abstracts from publishers, universities, professional societies, and other online repositories. Google Scholar ranks documents the way researchers do, weighing the full text of each document, where it was published, who it was written by, as well as how often and how recently it has been cited in other scholarly literature. “The quality of the search,” Frey points out, “is directly correlated to the quality of the AI.”
Google Home Assistant
“Hey, Google. Is Johnny’s Pie in the Sky open? Order me a pizza with pepperoni and mushrooms. And tell me how to get there. Is it on Front Street?” Frey gives this example of a series of tasks that Google Home Assistant could handle for someone returning home from a stressful workday. Again, she says, it’s about conserving that most valuable of all commodities—time. And as the AI becomes more sophisticated, so does the Home Assistant. “One of the most exciting developments in voice-assisted searches is that the ‘trail of thought’ problem has been solved,” Frey says. “We’re teaching AI to realize that your prior query is related to your next query. It understands the pronouns within a string of questions. After you asked if the restaurant was open and you followed it with the phrase ‘How do I get there?’ the Home Assistant knows that you’re asking how to get to the restaurant, even though you haven’t specifically used those words.”
The Home Assistant, Frey says, is an illustration of Google’s intention to reposition itself as a personal assistant rather than a comparatively aloof search function. “There is no part of Google that isn’t directly investing in machine learning and AI,” Frey says. “It’s all connected to our mission to move from searching to assisting. It’s a thrilling space to be working in right now, even in security and data protection, and I’m enjoying every minute of it.