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Category: Innovation

Thinking inside the box: Students on two continents embark on an entrepreneurial experiment

Let’s just say it’s not your typical hackathon. On Thursday, September 20, five students, each from a different discipline, will enter a glass cube on the MIT campus and spend the next four days inventing together. As soon as they convene, they will be presented with a real-world challenge that they must attempt to address. MIT’s cube will be located on the North Court between Vassar and Main Streets facing the Stata Center; passersby are encouraged to interact with the inventors inside.

InCube will take place simultaneously at MIT and in four glass cubes across Switzerland—two in Zurich, one in Bern, and one at the Crans-Montana ski resort. Each team will be presented with a different dilemma. On the final day, the five teams will present their prototypes, competing against one another to convince a jury that they have the most actionable solution and, perhaps, a viable startup. The MIT team will pitch its idea remotely to the jury in Zurich, where the Swiss teams will pitch in front of a live audience.

Conceived by the ETH Entrepreneur Club, a student association in Zurich, the event will be the second annual InCube experiment. The first took place in Zurich in 2017. The MIT team, sponsored by The MIT Innovation Initiative, will be participating for the first time. The five MIT students represent a diverse range of disciplines and experience. Undergraduates and PhD candidates alike, they come to the hackathon from the realms of computer science, economics, chemistry, biology, and medical engineering.

A glass cube is not an ivory tower

The idea behind the tiny, glass-walled think tanks is to draw the public into the process and provide a platform for interactive engagement. The transparent laboratories encourage passersby to interact with the teams, providing feedback and serving as sounding boards for ideas. Organizers say they want to foster entrepreneurship among students and the larger society but also erase boundaries—among people, disciplines, cultures, and nations.

The teams will eat, sleep, and work for four straight days in their cubes. The glass abodes are portable and don’t contain bathrooms, but facilities are available nearby. Each of the cubes is being supported by a company, institution, or foundation that will define a problem for the team to solve. Stryker, a Fortune 500 medical technology firm based in Michigan, is sponsoring the MIT cube and will devise the challenge for MIT students.

Learn more about the InCube hackathon.

Tapping data to gain an analytic edge

Competitive companies have been dutifully gathering data for years, many of them amassing an extensive and revealing body of analytics. The reality, however, is that a shocking number of those organizations just aren’t quite sure what to do with that information. As a result, the data often remains untouched, untapped, and uninterpreted says Taylor Reynolds, SF ’15, Technology Policy Director of MIT’s Internet Policy Research Initiative (IPRI).

“AI has been around for a long time, but the recent advances in scale open an almost infinite range of new possibilities,” Reynolds says. “The bottomless storage available through cloud computing as well as the complexity of calculations we can do now make it possible to store data and crunch numbers on a scale we never knew possible.”

Reynolds notes the importance of tapping this new avenue of information. “There’s so much low-hanging fruit out there in terms of revealing data. And there’s power in that data. Companies leveraging that information have an advantage over those that don’t. In fact, if we were to freeze technological development right here and now, and we had to live with any advances that have already taken place, we’d still likely have ten years of productivity gains we could make with our untapped data.”

And data analytics aren’t just a matter of due diligence, Reynolds says. They can be the key to transformational innovations. He points to work being done at MIT at the Laboratory for Social Machines, the Moral Machine, and the Machine Understanding Group, which is part of MIT’s Internet Policy Research Initiative. “Researchers at MIT are working on projects like a self-driving car that can explain itself. If it gets into an accident, the vehicle will be able to provide a detailed analysis of why it made the decisions it made: ‘I was starting to make a left turn but took evasive action because I saw a pedestrian.’ That’s critical information in the development of systems that will hold life-or-death responsibility. We’re not quite there, yet, but that’s where we’re headed.”

Can data be biased?

Reynolds, who often helps policymakers address cybersecurity and Internet public policy challenges, notes that data also poses dangers for society—for example, when inherent biases are built into algorithms. He cites the work of investigative tech reporter and machine bias expert Julia Angwin. Angwin and her team at ProPublica revealed that an algorithm employed by the criminal justice system to predict repeat criminals had been designed with inherent racial biases, consistently assigning high risk scores to blacks who did not merit that distinction. “People aren’t perfect,” Reynolds says, “and if people aren’t perfect, neither are the algorithms they design. If a person is biased, the algorithm may be built with that bias. That’s an authentic risk of AI that we, as a society, have to guard against.”

Reynolds, in his role at IPRI, is pulling together researchers and students from departments and labs across the Institute to increase the trustworthiness and effectiveness of interconnected digital systems. The initiative just made news by awarding $1.5 million to researchers across campus working on Internet policy and cybersecurity-related research projects.

Read the IPRI blog.

Boeing secures its spot on the world’s most innovative square mile

Artist rendering of 314 Main Street
Image: Perkins + Will

Kendall Square was dubbed the most innovative square mile on earth a decade ago by Boston Consulting Group. That honorific has only been reinforced by the steady stream of goliaths putting down roots in the community—multinational powerhouses like Microsoft, Biogen, Google, Akamai, and Facebook. Now the world’s largest aerospace company is joining the mix. Boeing has leased 100,000 square feet of the real estate being developed as part of MIT’s new Kendall Square Initiative, six mixed-use sites dedicated to research, retail, housing, office, and academic pursuits.

Boeing acquired the mature MIT spinout Aurora Flight Sciences in 2017. The enterprise has been developing advanced aerospace platforms and autonomous systems at its primary research and development center at 90 Broadway in Kendall Square for more than a decade. In the new facility at 314 Main St., Boeing’s Aerospace and Autonomy Center will focus on advancing technologies for autonomous aircraft. The first major tenant to join MIT’s Kendall Square Initiative, Boeing will open its new center by the end of 2020.

The power of proximity

MIT Executive Vice President and Treasurer Israel Ruiz, MOT ’01, told MIT News, “Our focus on advancing the Kendall Square innovation ecosystem includes a deep and historic understanding of what we call the power of proximity to address pressing global challenges.” He noted that MIT President L. Rafael Reif is dedicated to efforts that reduce the time it takes to move ideas from the classroom and lab out to the marketplace. “Just as pharmaceutical, biotech, and tech sector scientists in Kendall Square work closely with their nearby MIT colleagues, Boeing and MIT researchers will be able to strengthen their collaborative ties to further chart the course of the aerospace industry.”

Greg Hyslop, Boeing’s CTO, agrees that the power of proximity is a leading motivator for setting down roots in Kendall Square.  “Boeing is leading the development of new autonomous vehicles and future transportation systems that will bring flight closer to home. By investing in this new research facility, we are creating a hub where our engineers can collaborate with other Boeing engineers and research partners around the world and leverage the Cambridge innovation ecosystem.”

Boeing’s commitment to innovation

The productive relationship between MIT and Boeing extends back a century. Both institutions opened their doors in 1916. Many of Boeing’s founding leaders as well as generations of engineers, executives, and interns with MIT connections have joined its ranks. And Boeing announced recently that it will serve as the lead donor for MIT’s effort to replace the 80-year-old Wright Brothers Wind Tunnel with what promises to be the world’s most advanced academic wind tunnel. The project is estimated to cost $18M.

The new 17-story building at 314 Main Street will accommodate additional tenants, including MIT Museum, which will occupy more than 57,000 square feet on the building’s ground, second, and third floors. The building also will feature 6,000 square feet of retail space and an all new MIT Press Bookstore.

Read more about Boeing’s new presence in Kendall Square.

Navigating the car insurance maze

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.”

Read more about Insurify in Disruptor Daily.

Kidney-matching by algorithm

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

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.

Nikos Trichakis

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.

Find out more about their research.

Read the abstract.

 

Generative design is changing our relationships with machines

When we suspend our fears and fantasies of robotic minds replicating or surpassing our own, we increase the likelihood of turning the differences between human intelligence (HI) and AI into productive collaborations. The resulting whole could be much greater than the sum of the parts—a whole that offers a compelling counterpoint to the zero-sum scenarios many technology pessimists envision.

The revolutionary Live Parts™ software in development at Desktop Metal may foreshadow ways in which we will relate to artificial intelligence in a variety of settings. “AI can process ideas for functional parts in ways that humans can’t,” explains Desktop Metal CEO and company cofounder Ric Fulop SF ’06. “Our vision for Live Parts™ is to allow engineers and manufacturers to efficiently capitalize on the full potential of additive manufacturing, including material and cost efficiencies and immense design flexibility.”

Live Parts™ is just one of a collection of ingenious technology solutions emerging from the young company, which was founded in 2015 to address a challenge—how to make 3D printing in metal accessible to engineering teams. Back in 2013, Fulop began collaborating with global experts in materials science, engineering, and 3D printing. Over the course of two years, those collaborations generated multiple inventions that now define Desktop Metal’s printing frontier.

Technology inspired by nature

Desktop Metal’s experimental technology auto-generates part designs in minutes using morphogenetic principles and advanced simulation. “Because Live Parts is driven by nature-inspired algorithms, a part can grow and adapt like a plant or bone without a pre-existing design,” Fulop says. “Components change shape in real time to find the best form for their environment and function. Humans define forces, constraints, and load conditions—linear, radial, rotational, and dynamic—and view the progress in visual simulations.”

Fulop expects his company’s new technology to change the way metal products are designed. Clearly, the tech world agrees. Popular Science just named Desktop Metal’s production system “2017 Best of What’s New” in the engineering category. The magazine’s coveted awards honor “innovations that shape the future, from life-saving technology…to gadgets that are just breathtakingly cool.” Desktop Metal qualifies on both counts. The company was also selected as one of the world’s 30 most promising technology pioneers by the World Economic Forum and was recently named to MIT Technology Review’s list of the “50 Smartest Companies.”

The use of the artificial intelligence in Desktop Metal’s Live Parts™ is tantalizing when considered as a template for how humans can interact with machines going forward. With that frame of reference, we can understand AI as different and complementary—rather than superior to—human intelligence. And with that understanding, we can begin to view robots not as servants or masters but as collaborators in myriad areas of our lives.

Digital solutions for Africa: The 2018 MIT Sloan Africa Innovate Conference convenes at the MIT Media Lab April 7

Africa. In many ways it has a long way to travel to compete as a peer in the contemporary global marketplace. But from another perspective, the population is highly motivated to find solutions to crippling problems and incentivized to reinvent those systems that are barriers to progress. The MIT Sloan Africa Innovate Conference is an annual touchstone for just how far Africa has come and where it goes next.

Ismail Ahmed, WorldRemit founder & CEO, one of the keynote speakers at the 2018
MIT Africa Innovate Conference.

“Digitization for Inclusive Growth” is the theme of the 2018 conference, which is organized by the MIT Africa Business Club and takes place at the MIT Media Lab on April 7. Workshops and panels will evaluate the lessons of the last decade of technological advancement and explore how to leverage digitization to ensure that Africa’s progress is as inclusive as possible.

The conference will feature a Solveathon led by the MIT Solve Center. Teams of entrepreneurs will develop and pitch solutions related to coastal communities, healthcare, education, and the future of work. In addition, panels will delve into the most intractable challenges that countries on the African continent still face—challenges that require strategic innovation on a grand scale. Those panels will include investigations into:

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MIT and China partner to plot the growth of future cities

Where is the city going? What is the future of “urban?” How can we increase quality of life, solve transportation and energy issues, and provide affordable housing for millions of forthcoming city dwellers? MIT and China are partnering to find answers with the new Future City Innovation Connector (FCIC), which will be headquartered in a new space called the MIT China Future City Lab.

MIT and Tsinghua University in Beijing have established this revolutionary collaboration to support research and startup teams that will develop leading-edge ideas that address the challenges presented by China’s rapidly growing cities. As a result, the partners hope to develop new models for urban living and infrastructure that address issues of urban resilience, health, housing, environmental sustainability, responsive urban management, and the development of smart cities.

The FCIC will draw upon MIT research to identify innovative concepts and technologies that can be implemented in China. The program’s founder and faculty director Siqi Zheng is the Samuel Tak Lee Associate Professor of Real Estate Development and Entrepreneurship in MIT’s Department of Urban Studies and Planning and Center for Real Estate. She is also a visiting professor at Tsinghua University.

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Shaping the Commerce of Sport: MIT Sloan Sports Analytics Conference starts February 23

What is the secret to building a team around a superstar? What is the future of ticket selling at sporting events? What’s the best way to engage the modern sports fan? These are just three of the dozens of topics to be explored by leaders in the realm of sport at the upcoming MIT Sloan Sports Analytics Conference February 23 and 24 at the Boston Convention and Exhibition Center in Boston.

A limited number of tickets are still available for this annual event, which has grown over the last decade to become the premier confab of sports movers, shakers, and innovators. Founded in 2006 by Daryl Morey ’00 and HBS alumna Jessica Gelman, the conference is chaired by Gelman and organized by MIT Sloan students. Its goal is to provide a forum for industry professionals and students to discuss the increasing role of analytics in the global sports industry. Now more than ten years old, the conference delivers rich opportunities to learn about and innovate the sports business world.

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Will a robot be delivering your next pizza?

Robots have their limits. They’re not good, for example, at thinking outside the box. Humans have it all over robots when it comes to discernment and adapting to changing circumstances, but a team of engineers at MIT is working to improve a robot’s soft skills. One of those soft skills is learning to be a good pedestrian.

Yu Fan Chen, the graduate student at LIDS (MIT’s Laboratory for Information and Decision Systems) who is heading the research, says that socially aware navigation is critical for robots moving around in environments that require frequent interactions with pedestrians. The challenge is that pedestrians are a highly unpredictable force. Robots are programmed to adapt to certainties, as a rule, and are not traditionally equipped to deal with chaotic conditions.

Chen and his team are developing a robot designed to navigate and blend in with the crowd. The squat, waist-high robot sports a LIDAR array on top for high-resolution environment sensing. LIDAR (light detection and ranging) works on the principle of radar, but uses lasers to measure distances. The robot also uses webcams and a depth sensor to understand—literally—its place in the world.

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