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Intentional analytics

How fresh is your data? Do you know why you gathered it in the first place? Is there a rhyme to your reason when it comes to analytics? Abhi Yadav, SF ’13, launched the MIT spinout ZyloTech because he realized that even the best data-educated personnel at major companies were unable to deal with the continual stream, variety, and mind-bending complexity of omnichannel customer data.

ZyloTech was actually born in the New Enterprise class taught by MIT Sloan Professor Bill Aulet. Yadav then recruited Michael Cusumano, who taught his Business of Software class, to the company’s board. Along with a team of data scientists, engineers, and digital marketers from the Cambridge ecosystem, Yadav wanted to make it possible for companies to leverage all their customer data in near real time so as to continuously access advanced customer analytics that deliver vastly more accurate and actionable insights.

“It’s futile to try and get good results from a marketing campaign when you’re working off old, incomplete data and ad-hoc analytics,” Yadav says. “What we’re doing is bottom-up analytics. We are unifying and curating a customer’s identity, which includes past behavior, intent-based data points, and basic contact info. We continuously track each existing customer action as it’s happening to determine what that customer likes an doesn’t like and what their signature behaviors are.”

Leveraging MIT research

Yadav and his team tapped MIT research in consumer science and automated machine learning to create a proprietary technology that performs entity resolution while integrating a probabilistic and a deterministic data unification approach. “When you combine these two approaches with deep-learning (AI) to discover patterns,” he explains, “you attain an unprecedented level of knowledge about your customer from raw data.”

Setting aside the technical terms, what Yadav and his team are doing is distilling all that information to get the real juice out of it, to take timely action, and to discover what a company really needs to know about the individualized motivations, habits, and predilections of its customers. As a result, they will be able to offer individualized promotions at the right time and through the right channel.

Given the volume and variety of data getting generated every second, Yadav says, it’s essential to make the most of it through timely insights. “We see businesses getting frustrated with the classic modern challenge of big data versus big insights,” he notes. “They don’t see where it’s getting them, because running after IT or hiring lots of engineers has not furthered their objectives. My goal is to help a business go beyond the lip service on customer centricity with real customer-centric marketing that unlocks the riches that lie in customer data. The result: a better, smarter experience for consumers—and for the companies that hope to win them.”

 

Pioneering water recycling technology wins MIT $100K grand prize

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.

Watch the Infinite Cooling video.

Read the MIT News article about Infinite Cooling’s 100K win.

Read MIT Sloan’s coverage of the event.

AI pioneers MIT and IBM partner for a smarter future

Two of the world’s leading artificial intelligence pioneers are joining forces in a formal collaboration to advance AI hardware and software. The new MIT-IBM Watson AI Lab, which is staffing up now, will be one of the largest university-industry AI partnerships ever forged.

IBM will make a 10-year, $240 million investment to create the partnership, which will integrate the talent of MIT professors and students and more than 100 MIT and IBM scientists. Together, they will pursue joint research at IBM’s Kendall Square research lab, near the MIT campus. The complex is also the headquarters of the IBM Watson Health Lab and IBM Security headquarters.

MIT President L. Rafael Reif and John Kelly III, Senior VP, Cognitive Solutions and Research at IBM

 

Dario Gil, IBM Research VP of AI and IBM Q, and Anantha Chandrakasan, dean of MIT’s School of Engineering, will co-chair the lab. The team is planning to issue a call for proposals to researchers at the two institutions to submit their ideas for joint research that pushes the boundaries in AI science and technology. One objective of the partnership is to encourage MIT faculty and students to launch companies that will focus on commercializing AI inventions developed in the new lab.

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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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AI: The quiet revolution

Increasingly artificial intelligence drives every tool and every service we encounter in our daily lives. Leaders who don’t fully appreciate how to harness its value are not tapping the full potential of their organizations. But AI also has its limitations. The phrase Moravec’s Paradox was coined in the 1980s by artificial intelligence pioneers Rodney Brooks and Marvin Minsky of MIT and Hans Moravec of Stanford to capture the irony of AI—it’s as clueless, in some ways, as it is brilliant.

Computers can out-think most adults at playing chess, but ask it to join you at the dinner table, and it will be flummoxed. A toddler, on the other hand, would simply pull out a chair and sit down. High-level reasoning requires only basic computation from robots, but low-level sensory motor skills demand extraordinarily complex computational resources that robots have yet to master. So the moral of the story is know what to expect from AI. Its benefits are remarkable when it comes to mining and manipulating data, but it can’t perform simple tasks that require deft movement, intuition, or empathy.

(Image: SMART’s self-driving golf carts)

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Machine. Platform. Crowd. The three most influential words in the new economy?

Over the last decade, MIT Sloan researchers Erik Brynjolfsson and Andrew McAfee have become adept navigators of our digital future, and their most recent book, Machine Platform Crowd: Harnessing our Digital Future pretty much guarantees their place at the helm. The best selling authors of The Second Machine Age (2014) have taken the lead in making sense of the technological advances that are confounding the rest of the world.

In their new work, McAfee and Brynjolfsson, codirectors of the MIT Initiative on the Digital Economy, help the average citizen understand what the integration of machines, platforms, and crowds will mean to our collective tomorrow. Robots are front and center in that digital future-scape. The authors talk about restaurants in which customers order, pay for, and receive meals without interacting with human employees. Ordering, they point out, is something that a robot—or a computer interface—can accomplish very adeptly if the programming is smart enough.

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Smart phones are outwitting poverty

Alexander Graham Bell would be astonished at the power of today’s smart phones. Yes, the app that makes it possible to find a Starbucks along an unfamiliar highway can feel like a miracle, but the true revolutionary power of the telephone is felt most in developing countries. In Kenya, for example, the mobile phone has, to some extent, stabilized the economy for many citizens and transformed quality of life.

Nearly all Kenyan households own at least one mobile phone—not state-of-the-art smart phones, but phones “smart” enough to accommodate at least one M-Pesa account. Available to any customer of Safaricom, Kenya’s mobile network leader, M-Pesa is a money transfer service that allows a daughter at one corner of the country to send money safely and securely to her mother in a village seven hours away. Previously, she would have entrusted an envelope of cash to a bus driver heading to her mother’s village (at considerable risk) or relied on a money transfer that took days—and a daunting amount of red tape—to process.

Of course, to withdraw funds through an M-Pesa account you must have access to an agent who can disperse the cash. Happily, in response to the popularity of M-Pesa, the network across Kenya has mushroomed to 150,000 agents. Working with Innovations for Poverty Action, Associate Professor of Applied Economics Tavneet Suri, a native Kenyan, and her colleague William Jack have been tracking incomes in regions where new agents have opened for business. They compared the financial health of those regions with that of regions where agents are not as accessible.

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The future of manufacturing is here, and it’s in 3D

Alan Mulally, SF ’82, the legendary turnaround-artist who resuscitated Ford Motor Company, has always stayed focused on what’s next. An early proponent of 3D printing, he said in an earlier SF Leadership Blog post, “Metal is in the near future. With the level of accuracy that is possible through this process, we are seeing a sudden and dramatic improvement in the quality and manufacturability of parts. It’s both economical and efficient because spare parts don’t have to be warehoused. Almost any part can be produced on demand—and its file can live in the cloud. Three-dimensional printing will revolutionize the manufacturing world.”

The company that arguably is creating the noisiest buzz in the 3D space is Burlington, Massachusetts-based Desktop Metal—one of BostInno’s “17 Boston tech companies to watch in 2017.”  CEO Ric Fulop, SF ’06, launched the startup in October of 2015 to bring metal 3D printing to design and manufacturing companies across the globe. Fulop and his team have raised $97 million in equity funding, including a $45 million round of funding led by Google, BMW, and Lowe’s. Previous investors include NEA, Kleiner Perkins Caufield & Byers, Lux Capital, GE Ventures, Saudi Aramco, and 3D printing leader Stratasys. Desktop Metal is preparing for a product launch in late 2017.

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A robot can drive you to work, but can it advise you on your finances?

The founding father of artificial intelligence Marvin Minsky once said that his ultimate goal was not so much to build a computer he could be proud of as to build one that would be proud of him. MIT Sloan Professor Andrew Lo mentioned this anecdote in a recent piece about financial advisers in The Wall Street Journal. In essence, he poses the question: Can a robot do the job?

Andrew LoLo says that while tech-savvy millennials would be just as happy interacting with an app as with a human adviser, robo advisers can’t take into account the emotion of investors. “When the stock market roils, investors freak out,” Lo explains. “They need comfort and encouragement.” During the recent stock-market rout, he notes that Vanguard Group was so besieged with calls from jittery investors it had to pull staff from across the company to handle the call volume. “Investing is an emotional process,” Lo says, and “robo advisers don’t do emotion.” At least not right now.

Integrating human feeling into the digital advising process is probably the greatest challenge of financial technology. Lo likens the present state of digital financial advising to a rotary phone in an iPhone world. He points out that investing is much more complex and nuanced than tasks like driving, “which is why driverless cars are already more successful than even the best robo advisers.”

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What bumps in the road lie ahead for autonomous vehicles?

Rubber bumpers, airbags, shatterproof windshields—such were the hallmarks of vehicular safety before the advent of the driverless vehicle. For the passenger in a driverless car, however, it’s the software, first and foremost, that must be crash-proof. In a recent editorial in Xconomy, Lou Shipley, a lecturer at the Martin Trust Center for Entrepreneurship at MIT Sloan, cautions that in the production of autonomous vehicles, the management of software supply chains must be as reliable as the rigorously tested supply chains for mechanical parts.

Lou Shipley“Beyond being efficient, software providers for driverless cars will surely face requirements to certify that the code they deliver is free of security vulnerabilities that, if exploited, could enable a hacker to seize control of the vehicle,” Shipley says. “A faulty spark plug is one thing. Suddenly having your steering, acceleration, and braking hijacked is quite another.” He points out that many software fixes will take place remotely, the way that an Apple technician in Cupertino can now patch an iPhone in Sri Lanka—via cyberspace.

Bottom line, Shipley says, the success of autonomous vehicles will depend on whether drivers feel comfortable giving up the wheel. “Motorists’ willingness to hand over that control to software will depend largely on carmakers’ ability to gain their trust.” He notes that consumers have already shown some comfort with automated transportation. “Airline passengers today don’t seem to worry about automatic pilots guiding airplanes through the sky and even landing them when visibility is poor.”

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