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September 25, 2017

BROWSE NEWS RESULTS

42 Results | Page 1 | 2 | 3 | Last | Next
 
StartupExchange
August 7, 2017

Lexumo Helps BT Probe Software Security

Innovative collaboration identifies and fixes vulnerabilities in open source code for the internet of things.


Steve Roge
CRO & VP Customer Success
Lexumo

“Any organization that is developing software is probably using open source code,” says Jonathan Tate, a solution architecture lead for BT Global Services. “Our internal development projects use a lot of open source products and libraries because their quality is very high, they are well established in the industry, and there's no point in reinventing the wheel.”

However, open source code can open up security vulnerabilities, not just for traditional computing systems but the vast wave of the Internet of Things (IoT) devices now flooding into the market. Applications running on these embedded products are getting increased attention from the “black hat” hackers who capitalize on gaps in security. “The black hats innovate very quickly, and we want to make sure that the development of our security offerings is equally rapid,” Tate says.

That’s the role targeted by Lexumo Inc., an MIT STEX25 company, which has begun a proof-of-concept collaboration with BT to spot and correct open source code bugs in IoT devices.

Lexumo’s services continuously monitor the world of open source code for vulnerabilities and help developers to fix these vulnerabilities in their own software. “We can help to secure many types of applications, but our current focus is primarily on the IoT and embedded systems,” says Steve Roge, chief revenue officer.

The partnership was fostered through the MIT Startup Exchange, a program from the Institute’s Office of Corporate Relations that works in close cooperation with the Industrial Liaison Program (ILP).

ILP has worked closely with BT for decades, notes Steve Whittaker, the global telecommunication firm’s head of strategic U.S. university research partnerships.

The BT/Lexumo project began with a December 2016 MIT Startup Exchange showcase hosted at BT headquarters in London that drew a number of European companies and universities. “This event helped to expose our people to some of the innovations and the thinking that are coming from MIT through startups, and it was viewed as being very valuable,” says Whittaker.



Lexumo has begun a
proof-of-concept collaboration
with BT to spot and correct
open source code bugs in IoT devices.


Nathan Shnidman, Lexumo co-founder and chief scientist, presented at the event, and the startup was introduced to the BT security group soon afterwards.

Kicked off this May, the project analysis will test Lexumo’s offering on applications that are in use or in development at BT. “This should give us a feel not only for how useful the Lexumo service is, and how easy it is to use, but will also tell us something about our own product source code,” says Tate. If the service makes it through BT’s extensive vendor onboarding process, it potentially could prove useful both in monitoring a broad range of products and in BT’s managed security service portfolio.

“The big players in the security industry have very comprehensive portfolios of products, but we also find it very useful to work with startups,” Tate says. “Some of the new techniques coming out of universities can come very quickly into startups, which helps us to keep up with the rapid progress in the black hat world.”

Tate also appreciates the chance to have direct access to developers at Lexumo who performed the research underlying the software’s capabilities. “It’s easy to get a view of how the software is actually working,” he says.

This early cooperation highlights the value that MIT Startup Exchange and ILP bring to corporations such as BT, Whittaker says.

“MIT's increased focus on the larger innovation ecosystem helps us to understand the emerging patterns of the innovation economy look, the roles we want to play in it, and our opportunities,” he comments. “We’ve been very supportive of MIT Startup Exchange from the beginning. When MIT decides to do something like this, it does it properly, with a supported professional framework for doing it at scale and over the long term.”

On the startup side, Lexumo enjoys major benefits from being selected as a STEX25 firm. “We get high access to ILP members and events,” says Roge. “We’ve been exposed to many great relationships and premiere accounts, including some of the biggest companies in the world.”

About Lexumo
Lexumo enables developers to securely adopt the best open source available — so they can ship great products faster. Based in Burlington, Massachusetts, the company was formed by a team of computer scientists who developed the company's core technology for the Defense Advanced Research Projects Agency. Lexumo saves time and reduces risk by helping developers quickly eliminate open source vulnerabilities in their code, while also ensuring they're in compliance with licensing requirements. Built on a massively-scalable cloud stack, the service uses patent-pending graph analytics and machine learning technology to precisely identify vulnerable code. The company is privately held and funded by leading cyber-security investors .406 Ventures and Accomplice. Lexumo’s platform is being used by leading Global 2000 brands including global service providers and industrial IoT manufacturers


About BT
BT is one of the world’s leading communications services companies, serving the needs of customers in the UK and across the world, where it provides fixed-line services, broadband, mobile and TV products and services as well as networked IT services. In the UK BT is a leading communications services provider, selling products and services to consumers, small and medium sized enterprises and the public sector. The company also sells wholesale products and services to communications providers in the UK and around the world. Globally, BT supplies managed networked IT services to multinational corporations, domestic businesses and national and local government organizations.



About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
July 28, 2017

Akselos: Maintaining Assets for an Energy Leader

MIT Startup Exchange helps advanced simulation software firm partner with one of the world's biggest oil and gas companies.


David Knezevic
CTO
Akselos
In June of 2015, Akselos had under 20 employees. But it also had simulation algorithms developed at MIT that it had turned into a core product for engineering modeling. Today, the MIT spin-off is growing beyond 20 employees and is working on a two-year digital twin initiative with Royal Dutch Shell.

The union came about through the MIT Startup Exchange and MIT Industrial Liaison programs. Before that introduction, Thomas Leurent, Akselos CEO, says that his company had long-range plans to work in the energy field, but, at the time, its experience was in power systems and was focused on breaking into the mining industry. Shell executives came to campus for two days in July 2015, with the intent to find disruptive technologies for the future of construction and engaged with a select set of MIT experts and spin-offs.

Akselos had one hour to make its pitch, Leurent says. In December, the two companies signed their first contract, with Akselos testing its technology on an extensive use case. The findings were delivered in January 2017, and Lourens Post, Shell Global Fluid Flow & Reactor Engineering manager, says that they were “great results” adding that what the company offers “is a great fit for our strategy.”

In February 2017, the two-year project started, with an initial focus on assessing a Shell asset in the Southern North Sea. In the first year, Akselos’ technology will produce a condition-based model, analyzing the structural integrity with more accuracy and detail than was previously capable, Leurent says. In the second year, Akselos will combine this information with sensor data to allow operators to monitor the asset’s health in real-time. Ultimately, the technology will be able to identify looming mechanical problems, estimate the remaining life, determine when parts need to repaired, without having to inspect and test on a scheduled basis. All of this, Leurent says, can mean extending the life of equipment by 20 years and prevent downtime, which in the oil and gas industry can cost $25 million per day.

Leurent says that the jump to such large scale work wasn’t a worry. Oil and gas is an engineering-based industry, and it is common for large companies to outsource projects to smaller ones, but, he adds that the strong start is due in large part to the ILP. MIT is a good credential. It drew Shell to campus in the first place, but the right connection still has to be made. ILP officers know what’s happening throughout the MIT landscape, have decades of industry experience, and are skilled at pairing up a start-up’s innovation with an established company’s need, so momentum is already established. “You know if you get called for a meeting, there’s a good chance there’s a match,” Leurent says.

About Akselos
Akselos enables your engineers to design and assess critical infrastructure via advanced simulation software. We focus on making powerful, highly-customized simulation tools that can be widely used within your company.

The company was founded after 12 years of research at MIT. We license proprietary technology issued from research conducted in Prof. A.T. Patera's group(*) at MIT and supported primarily by the Air Force Office of Scientific Research/Office of Secretary of Defense and the Office of Naval Research. The research led to the award of the largest Deshpande Innovation grant at MIT in 2011 and the company was subsequently founded and secured major industrial firms as customers within a year.



About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
July 25, 2017

MIT Startup Exchange names top 25 startups

MIT Startup Exchange is pleased to announce the complete roster of STEX25 companies. STEX25 is a startup accelerator focused on fostering startup and industry collaboration.


STEX25 companies participated in a startup exhibit during the 2017 MIT Startup Ecosystem Conference.


MIT Startup Exchange is pleased to announce a complete roster of STEX25 companies, with the addition of six MIT-connected startups in June 2017. Recently named to STEX25 are 24m, Affectiva, Cogito, C2Sense, Ginkgo Bioworks, and Neuromesh.

STEX25 is a startup accelerator within MIT Startup Exchange focused on an elite group of startups deemed “industry-ready,” having proved themselves with early use cases, clients, demos, or partnerships. Since its launch in September 2016, STEX25 has added startups on a roughly quarterly basis, culled from the over 1200 startups in the MIT Startup Exchange database. The list includes startups from a number of important fields including artificial intelligence, automation, energy, healthcare, internet of things (IoT), life science, manufacturing, materials, nanotech, sensors, and more. MIT Startup Exchange and the Industrial Liaison Program (ILP) are integrated programs of MIT Corporate Relations.

According to MIT Startup Exchange Program Director, Trond Undheim, “MIT Startup Exchange was launched to help top corporations and MIT-connected startups bring new technology to the world through creative partnerships and collaboration. The inaugural group of STEX25 companies have strong roots in MIT’s entrepreneurial ecosystem, and are infused with high-caliber talent and cutting-edge technology, key assets for industry partners searching for innovation.”

Karl Koster, executive director of the ILP, pointed out that helping MIT-connected startups get traction with large corporate players is a crucial step in technology commercialization. “Our corporate members are very interested in meeting with the MIT Startup Exchange company founders, and these kinds of connections are vital to growing MIT’s innovation ecosystem.”

View the full list of STEX25 startups.

StartupExchange
July 16, 2017

Luminoso Joins with Leading Carmaker to Drive Automated Analysis of Buyer Complaints

MIT Startup Exchange helps deep learning analytics firm partner with an Industrial Liaison Program member and break into the Japanese market.


Catherine Havasi
Cofounder & CEO
Luminoso

Customers offer their opinions and complaints in informal and disorganized ways, which makes these responses famously difficult to analyze. Conventional analytic software tools need considerable expert attention, and all too often, they sort customer responses into the wrong categories or unwieldy “uncategorized” buckets.

Luminoso Technologies, a startup from MIT, targets these problems with software that combines deep learning and natural language processing to help companies rapidly and accurately understand the concepts within their unstructured, text-based data—without requiring massive sets of training data.

During a pilot project for a Japanese carmaker, and Industrial Liaison Program (ILP) member, Luminoso used its software-as-a-service analytics system to examine a database of customer complaints to car dealers, where the carmaker’s existing tools struggled to properly sort out the complaints. “We found buckets that should be created, buckets that should be merged, and buckets related to problems in specific types of cars,” says Catherine Havasi, Luminoso co-founder and chief executive officer. “We helped them figure out how they could minimize the number of uncharacterized complaints and maximize the number of things that could be dealt with automatically.”

Luminoso software detected two concepts about one car model. One concept described the car smell in colorful language (such as an “attic” or a “dog in the car”) while the other concept mentioned finding dew inside the car. After reviewing these two concepts, it was discovered that the complaints reflected the same problem. The automaker then tracked down the common defect: a disconnected air-conditioning hose that allowed mold to develop. Conventional software with preset taxonomies would never have found this connection, because they would not have thought to write a taxonomy around mold inside a car, or known that there were so many ways to discuss a musty smell.

Given the success of this project, Luminoso has continued its relationship with the automaker and is talking with other Japanese car manufacturers. “Being in this market with this experience became really valuable to us,” Havasi says.

Getting into the Japanese market at all is very challenging for small U.S. companies, she notes. Luminoso made its initial connection through the MIT Startup Exchange.

Initially, MIT Startup Exchange chose Luminoso to participate in a 2015 Tokyo conference partly because the company’s software works natively in Japanese, among many other languages.

“We talked a lot with ILP before we headed over to Tokyo,” Havasi says. “We wanted to find people who had business questions we could help answer and were looking to get something done with relative speed.” ILP staff helped to target the car company and get to know key individuals within it. After meetings at the conference and the company’s headquarters, the project kicked off.

MIT Startup Exchange and ILP have continued to lend assistance as a matchmaker for Luminoso, “not just with companies that become customers but with companies that help us formulate our strategies for particular vertical markets,” Havasi says. “For the average startup company coming out of MIT, there’s a lot to learn about how to work with a Fortunate 1000 company, and ILP also is great for that.

About Luminoso
Luminoso Technologies is a leading natural language understanding company that allows clients to rapidly discover value in their unstructured text data. With roots at the MIT Media Lab, Luminoso’s artificial intelligence-based software uniquely produces the most accurate and unbiased, real-time understanding of what people are saying, including insights that were not anticipated. These insights are used to increase marketing performance and build better customer experiences. Luminoso provides multilingual, flexible software that can be deployed to meet client needs in either a standalone Cloud or On Premise solution or integrated into an end-to-end client platform via an API solution. Luminoso serves clients such as Staples, Sprint, and Scotts Miracle-Gro, as well as a growing set of channel partners such as Publicis.Sapient and Basis Technologies. Luminoso is privately held with headquarters in Cambridge, MA.


About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
July 14, 2017

Re-Imagining Lithium Ion Batteries

At 24M, Yet-Ming Chiang has revamped the way lithium ion batteries are designed and manufactured, making them a viable low-cost, highly-efficient green energy option.


Yet-Ming Chiang
Cofounder and
Chief Scientist, 24m (L)
Rick Feldt
President, 24m (R)

For nearly 25 years, Yet-Ming Chiang has been designing and building new battery technologies in the Department of Materials Science and Engineering at MIT. Hand-in-hand with his research endeavors, he has always been active moving that science from the lab to industry having co-founded several companies, including American Superconductor Corporation, A123Systems, SpringLeaf Therapeutics, and his latest, 24M, which is in the business of designing highly-efficient, lower-cost lithium ion batteries.

Developed in the late 1980s in Japan, lithium ion batteries are today’s most advanced battery technology dominating battery applications from hand-held devices to electric vehicles, and increasingly, grid energy storage. But Dr. Chiang believes the technology is being held back due to quarter century-old methods of battery design and manufacturing that persist today.

Chiang and colleagues formed 24M in 2010 to remedy those deficiencies. They have developed a cell design that makes much more efficient use of the materials that go into a lithium ion battery. Specifically, their designs decrease the amount of material that does not store energy by 40% or more. By maximizing the amount of active, energy storage material and decreasing all other materials, 24M reduces the bill of materials by 25-30% compared to conventional lithium ion batteries.


“24M is the culmination of a lot of things that we’ve learned both in research and through the industrialization of new battery technologies,” says Chiang. “Having earlier developed a battery technology that was a new chemistry and was put into commercialization but manufactured the conventional way, I had learned a lot about what the weaknesses of the conventional manufacturing were.”

Novel Manufacturing Method

“Our vision for the company is that the way that we manufacture lithium ion batteries will become the preferred way for making batteries around the world,” Chiang says. 24M’s manufacturing method strips out about 1/3 of the steps, or unit operations, of previous manufacturing methods. It also eliminates the need for any organic solvents which are used in conventional lithium ion manufacturing that have to be evaporated and re-condensed. “By avoiding these steps that were used earlier, we’ve also decreased the energy consumption of our manufacturing method.” Chiang estimates 24M’s battery design and manufacturing methods provide a 25% reduction in cost of goods versus conventional lithium ion batteries.

“What impresses me about what Yet has done is that he hasn’t come up with a radically new chemistry for the battery, but he has modified its design and radically changed the manufacturing process,” says Rick Feldt, 24M President. “We use a lot less stuff and it takes us half as many steps to actually produce the cell. When you have less materials, fewer steps, smaller building, fewer people, less equipment, a faster process – it all adds up to creating a lot of savings.”

Partnerships, not Plants
24M’s business model is to partner with those that want to produce their own batteries. “In a sense we are trying to democratize the production of lithium ion batteries so that any company can do it – not just a few select companies around the world,” Chiang explains. Companies can license 24M’s technology without having to invest in gigawatt hour sized plants. Companies can more accurately match supply with demand as their business grows, rather than investing significant capital for capacity in advance of demand. As an additional benefit, the licensing agreements allow 24M’s partners to modify the battery design to more specifically suit their applications.

24M sees three main applications for LI batteries today – portable devices, transportation, and energy storage for the grid or to smooth renewable energy. They are avoiding the hand-held market at this point, and targeting the large-scale applications.

Their first product, now ready for manufacturing, is a battery for grid energy storage. 24M signed its first partnership agreement with Thailand’s GPSC, part of the country’s largest oil and gas company, PTT. They are in discussions with a large industrial Japanese company now for a similar type of deal.

Some of their potential partners in this space are other countries concerned about grid energy storage solutions. They see it as a national resource, a national priority, to be in the position of producing their own batteries for energy storage. “We offer them an alternative way, a lower cost battery, a manufacturing method that we think is the future,” Chiang says, that removes reliance on other countries and companies for their battery supply.

24M is also very close to marketing a higher energy density lithium ion battery for transportation. “The goals for battery technology are to get the costs of batteries down and the driving range up to where it’s easy for anyone to use an electric vehicle with minimal limitations on user behavior,” Chiang says, who adds that getting the cost of a lithium ion battery pack down to about $100 per kilowatt hour is what is required. “What we are aiming to do is accelerate the adoption of electric transportation by providing the lowest cost lithium ion batteries that anyone can produce because of the greater design and efficiency of our manufacturing method.”

The company is in discussion with a number of global organizations for electric vehicle applications. “In all cases, these partners will rely on our technology and we will be the technology provider,” says Feldt. “They will build the factories, buy the equipment, and operate those factories with our help and we will share in the economics of those factories.”

Chiang emphasizes that lithium ion technology is not a single technology, though lithium is the key chemical component. “There is a lot of effort today, and we’re involved in that effort ourselves, in developing a lithium-metal electrode based rechargeable battery.” Lithium ion currently does not use lithium metal, but Chiang explains that using lithium metal as one of the battery’s electrodes would allow a 2-3-fold increase in the energy density of today’s batteries.

“There are certainly a lot of different chemistries being explored all the time,” he says. “What we are focused on is the fact that as other chemistries get developed, if the chemistries prove to be useful and successful and low cost, we will have a way of dropping them into 24M’s approach.”


About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
July 6, 2017

Humanizing Technology with Emotion AI

Rana el Kaliouby envisions a future where all our digital devices have a chip that senses and reacts to our every emotion in real time. As CEO and cofounder of Affectiva, one of the leading developers of emotion AI technologies, she is well positioned to help make this a reality.


Rana el Kaliouby
CEO & Cofounder
Affectiva

Rana el Kaliouby envisions a future where all our digital devices have a chip that senses and reacts to our every emotion in real time. As CEO and cofounder of Affectiva, one of the leading developers of emotion AI technologies, she is well positioned to help make this a reality. She has been recognized by Entrepreneur as one of the “7 Most Powerful Women to Watch In 2014,” inducted into the “Women in Engineering” Hall of Fame and is a recipient of Technology Review’s “Top 35 Innovators Under 35” award. The seed for the venture was planted while el Kaliouby was pursuing her PhD in computer science at Cambridge University. “I realized I was spending more time with my laptop than with other human beings,” she says. Yet despite the intimacy she shared with this machine, it had no idea how she was feeling. She began to wonder, “What if computers could understand our emotions?”

Before long el Kaliouby was doing postdoctoral work at the MIT Media Lab alongside founder and director of the Affective Computing Group and eventual Affectiva co-founder Rosalind Picard. Picard’s publication, Affective Computing, which gave name to a new field of research, proposed that in the future computers will need to understand human emotion. “If you look at human intelligence,” says el Kaliouby, “people who have higher emotional intelligence tend to be more likeable, they’re more persuasive and more effective in their lives. We at Affectiva think this is true of artificial intelligence as well.” She continues, “As more and more of our interactions with technology become conversational, perceptual, relational, the social and emotional awareness of these interfaces will become critical.”



Today Affectiva is backed by leading investors including Kleiner Perkins Caufield & Byers, Horizon Ventures, Fenox Venture Capital, and WPP. The MIT spinout whose mission is to humanize technology also boasts one third of Fortune Global 100 and more than 1,400 brands as users of their technology. For three years at MIT Media Lab, el Kaliouby and Picard worked to develop what she calls an “emotional hearing aid” for those with autism spectrum disorder. It was called MindReader, and it involved reading glasses with a camera connected to a device that analyzed facial expressions and provided real time feedback to the user. The pilot program at a Rhode Island school for children with autism was extremely successful. El Kaliouby recalls seeing the subjects reacting to the feedback, making eye contact, engaging in meaningful human interactions and generally becoming more curious about the expression of emotion.

When exhibiting their work to Media Lab member companies, corporations like Proctor & Gamble, Toyota, and Samsung recognized the genius of the technology but wondered whether it might be applied to various use cases outside the realm of autism and mental health. The initial thought, according to el Kaliouby, was to hire more researchers. But it was Frank Moss, the Media Lab’s director at the time, who suggested this was no longer a research problem but rather a commercial opportunity. “I was intrigued by this idea of taking emotion recognition technology in new directions, applying it to different industries and ultimately fulfilling my vision of an emotional digital world,” says el Kaliouby.

In the realm of deep learning, effective algorithms are only part of the puzzle. The data powering these networks is essential. To date, Affectiva has collected 5.5 million face videos from 75 different countries, which amounts to approximately 2.5 billion facial frames. These frames are used to train Affectiva’s machine learning and deep learning algorithms to understand human emotions, and the sheer volume of data is part of what separates Affectiva from their competitors. Thus far, their emotion recognition technology has garnered significant attention in the media and advertising industries. Their product, Affdex for Market Research, is a cloud-based solution that allows advertisers to measure unfiltered and unbiased consumer emotional responses to digital content from anywhere in the world.

Thanks to Affectiva, traditional focus groups are quickly becoming a thing of the past. “Affdex captures the emotional journeys of thousands of viewers as they unfold,” says el Kaliouby. The data is then aggregated, compiled, and presented in a dashboard provided for clients. Currently fourteen different market research partners, including leading firms like Millward Brown and Nielsen, all use the technology to measure consumer emotion responses to digital content. A powerful outcome of these partnerships is that the data collected allows Affectiva to fundamentally improve the technology and advance the state of the art with their proprietary machine learning algorithms.

Affectiva’s core emotion engine analyzes any video stream and maps it to an emotional state. And for the benefit of application developers, they’ve packaged it as software development kits (SDKs) and cloud-based APIs. “Our own device SDKs run in real time and don’t send any videos to the cloud, which is important for privacy reasons,” explains el Kaliouby. “It allows any developer to very quickly emotion-able their very own digital experience.” With the idea of ubiquitous emotion technology in mind, they’ve shrunk the machine learning models to enable them to run on any device, including iOS, Linux, mac OS, Windows, Unity and even Raspberry Pi. A large part of why el Kaliouby and her team built the SDKs was to allow them to diversify and explore new verticals.

The automotive industry is a perfect example. “As we transition into semi-autonomous and fully-autonomous vehicles, it is going to be imperative that cars understand the mental state of their drivers,” explains el Kaliouby. “As cars redefine themselves as conversational, infotainment interfaces that want to understand the emotional engagement of the user to personalize the experience—the lighting in the car, the music—this has the potential to be a big market for Affectiva.” They have just finished a proof of concept with a large Japanese car manufacturer, which involved installing cameras and Affectiva’s Emotion AI in cars in Tokyo and Boston, and collecting driver data. El Kaliouby also mentions that Affectiva’s tech is used in a number of social robots.

Throughout this diversification process, MIT ILP has played a substantial role in connecting Affectiva to new industry partners. El Kaliouby says, “One of the reasons that we are so excited to join the STEX25 program is that we are constantly looking to diversify into new markets. And this is where we can tap into the MIT ILP network.” She is also in the process of organizing the first ever Emotion AI Summit at the MIT Media Lab (September 13, 2017). “Emotion AI is a core capability that is growing into a multibillion dollar industry, and it is transformative to many different verticals. We at Affectiva are excited to bringing together business and thought leaders who are interested in exploring artificial emotional intelligence for their own data platforms, devices, and technologies. And we’re very much looking forward to the opportunity to expose ILP members to this type of technology.” Consider it another step towards Rana el Kaliouby’s vision of ubiquitous emotion AI.


About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
July 6, 2017

Bringing a Sense of Smell to the Digital World

Jan Schnorr has seen sensor technologies come and go through the years. But despite promising ideas backed by solid tech, there is a common theme among them: a struggle to transition from the lab to the real world where fluctuating temperatures, humidity, the presence of new compounds and a host of other unforeseeable variables wreak havoc on a sensor’s ability to function properly.

Jan Marcus Schnorr
CEO
C2Sense

Jan Schnorr has seen sensor technologies come and go through the years. But despite promising ideas backed by solid tech, there is a common theme among them: a struggle to transition from the lab to the real world where fluctuating temperatures, humidity, the presence of new compounds and a host of other unforeseeable variables wreak havoc on a sensor’s ability to function properly. Schnorr explains this as a problem of specificity. “For example, you have a sensor that is supposed to pick up one part per million ethylene gas in a fruit storage facility in the presence of 10,000 parts per million of water. It needs to be incredibly specific for the compounds you care about. That is the main challenge we set out to solve with our patented chemiresistive technologies.” C2Sense achieves this by combining their carbon nanotube-based network with what they refer to as a selector. “Think of it as a simplified version of an enzyme that is designed to interact specifically with the compounds you care about,” says Schnorr, “thereby eliminating false positives.” In the case of C2Sense, they are interested in detecting gases that can be destructive to our food and harmful to our health.

Schnorr moved from Germany to complete both his PhD and postdoctoral work in the MIT Chemistry department with Tim Swager, who has been working on sensing technologies for over 30 years. When he arrived, the group was hard at work developing the next generation of the technology. The aim was to create a small, relatively simple and affordable product, all while maintaining specificity. “I was fortunate enough to join the Swager Laboratory at a time when we were working on a product for ethylene detection,” says Schnorr. The results, published in a 2012 paper, were very promising and led to their initial funding from MIT’s Deshpande Center for Technological Innovation, with whom Schnorr and C2Sense maintain a close relationship. This was followed by a significant government grant from the National Science Foundation in 2014. And while C2Sense has moved out of MIT into their own Cambridge offices, Schnorr says they very much remain a part of the MIT startup ecosystem and rely on the institution for advice and industry contacts among other things: “The quality of contacts we’ve reached through MIT ILP has been amazing,” he says. “Due to their extensive knowledge of what is useful for their member companies it has been very important for us.”



It’s an exciting time for the young startup that spun out of MIT just three years ago. They’re on the verge of completing their Series A financing and are preparing to launch their first product. It’s a small, lightweight and cost-effective sensor that detects ethylene in even trace amounts, thereby ensuring optimal storage conditions for produce. According to the Food and Agriculture Organization of the United Nations, approximately one third of the food produced in the world for human consumption is lost or wasted every year, which amounts to roughly one trillion dollars. Not to mention the resulting negative social and environmental impacts. C2Sense aims to make a massive dent in those numbers.

Schnorr stresses that the team at C2Sense has prioritized industry partnerships since the beginning. “We sought to work with industry partners very early on to avoid the fate of so many groups and individuals who spend years developing a technology only to discover there is not enough customer interest.” One such partner is AgroFresh, an industry leader that provides innovative food storage solutions to enable growers and packers of fresh produce to preserve and enhance the freshness, quality and value of their produce. “We started with lab experiments and preliminary tests before launching our big pilot project last year,” says Schnorr. At this point C2Sense, in conjunction with AgroFresh, has tested their ethylene sensor in a wide variety of facilities spanning 12 different countries across the Northern and Southern hemispheres. The success of the pilot is evident in the fact that a global, industry giant is now C2Sense’s first client.

“The first step, where we can have the biggest impact, is in the food supply chain,” says Schnorr. With that in mind, C2Sense has also applied their technology to develop ammonia sensors. According to a recent study, the poultry industry loses approximately half a billion dollars per year due to high ammonia concentrations in chicken grow-out houses. Schnorr says, “It just so happens, we’ve been working on our ammonia sensors, and they work really well in that type of environment.” C2Sense is also exploring options to apply their technology to meat and fish, further impacting the food supply chain. This expansion into new arenas proves how far reaching the technology has the potential to be.

Aside from the food and agriculture industries, environmental monitoring and industrial safety are application areas with huge potential. C2Sense is currently working with the Department of Energy to develop wearable sensors that detect toxic compounds to protect workers on site. “Imagine a wearable sensor that can smell hazardous gases and alert workers if a toxic compound is spiking, to what degree and whether or not it is time to put on a respirator and evacuate the area,” says Schnorr. This alert system highlights an aspect of what makes C2Sense so special: the dual-purpose nature of their applications. “In the food industry we help avoid waste, which is beneficial for people and also saves money. In industrial safety we reduce liabilities for an employer while protecting workers simultaneously.”

As every facet of the human experience becomes digitized, from audio sensing and voice recognition to physical sensors like accelerometers, Schnorr and C2Sense insist that instilling our computers with a sense of smell is essential. “It’s far from trivial and it’s an aspect that has yet to be fully explored or embraced,” says Schnorr. “Step by step we are creating more and more capabilities, and once we have a suite of different capabilities we can bring it into your home in the form of smart, simple gas sensors built into our everyday devices.” Imagine the advantage of a sensor built in to your refrigerator that can not only tell you when it is time to use your produce but also sends a message to an integrated application on your phone with recipe suggestions. In other words, C2Sense intends to build convenience into our everyday lives in the not-too-distant future.



About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
July 6, 2017

Charm offensive: Cogito delivers live conversation coaching in the call center

Cogito has built an AI-driven coaching application that analyzes conversational dynamics within phone calls and provides live guidance reducing customer churn and employee churn during calls.


Joshua Feast
CEO & Cofounder
Cogito

“This call may be monitored or recorded for quality assurance purposes.”

Customer service calls often begin like this, but in practice only a small percentage of calls are analyzed. “Call center calls are recorded, but on average supervisors only have time to review one to five calls per month per agent, which represents only a small percentage of calls” says Cogito cofounder and CEO Joshua Feast, a graduate of MIT’s Sloan School of Management. “Agents may go weeks without feedback, and it’s often subjective, making it difficult for agents to improve their performance”

Cogito’s solution is an AI-driven coaching application that analyzes conversational dynamics within phone calls and provides live guidance. The application extends agent intelligence, helping them better recognize and respond to the subtle behavioral cues expressed by customers. It also delivers an instant measure of customer perception for every phone interaction.

“The software helps agents become more charming and emotionally intelligent – to listen better and build rapport,” says Feast. “It addresses the most challenging part of being a front-line service professional: dealing with difficult, emotional customers.”

Cogito reduces both customer churn and employee churn, says Feast. “If agents don’t get timely feedback or help build rapport with customers, they can burn out very easily,” he says. “With Cogito, they have a window into the customer’s sentiment and live guidance to help them properly adapt. The employee feels reassured that they have a means to improve, and the customers are happier.”



Video Link Coming Soon

Sharing the caring

Feast didn’t start out with the goal of improving call centers, but after growing up in friendly New Zealand, he felt the world could use a bit more caring and charm. “When I came to MIT, I was interested in the notion of caring, and how can we have more of it,” he says. “How can technology help create better relationships and help each of us be a better version of ourselves? I grew up in an entrepreneurial environment, and was interested in building a business that combines the best ideas in science and technology to drive positive human impact.”

The MIT Media Lab was the ideal place to advance these goals. There, Feast learned about research on relationship dynamics that had been under development for years by Professor Alex (Sandy) Pentland and his Human Dynamics Lab. Feast was intrigued by Pentland’s “Honest Signals” research into understanding human behavior and interpreting psychological states.

Pentland, who eventually co-founded Cogito with Feast, “had shown it was possible to analyze voice and understand the markers of distress,” says Feast. “The research indicated voice and other behavioral feedback provided excellent insight into a person’s intent; for example to detect if someone was experiencing distress or losing interest.”

Based on this research, Feast and Pentland received funding from DARPA and the National Institute of Mental Health to launch Cogito into R&D mode in 2007. Four years later after extensive development and the capturing of millions of data points, the first version Cogito’s commercial software was released.

The initial focus was to analyze conversations to offer real-time coaching for clinical use cases. “We wanted to help nurses and psychologists recognize distress in vulnerable patient populations,” says Feast. To help commercialize the software, Feast called upon the MIT Venture Mentoring Service and the Martin Trust Center for MIT Entrepreneurship.

After an initial roll-out in healthcare, Feast decided in 2015 to extend the business to sales and service conversations in call centers. Today, Cogito is used by a variety of large banks and insurance companies. “Our customers have seen very substantial improvements in customer and employee satisfaction,” says Feast. “We have also demonstrated efficiencies like shorter call times and fewer repeat calls.”

The Boston-based startup was recently named as one of the prestigious MIT Startup Exchange STEX25. “MIT ILP and STEX25 are helping us build relationships with large customers,” says Feast. “Cogito sits on the shoulders of giants in more ways than one.”

Conversations are like a dance

Every day Cogito streams millions of calls into its high performance computing cloud platform, and scans for behavioral signals based on hundreds of measures across the voice spectrogram. The signals are synthesized into behavioral models, or as Feast puts it, “specific things that are psychologically relevant.” The application then presents in-call guidance to help agents modify their behavior for better outcomes.

The Cogito software can detect pressured speech based on agitated, accelerated speech patterns, or it can detect a voice under distress. It can also identify and encourage positive indicators such as tones and patterns that reflect empathy. One goal is to guide agents toward speaking with consistency “which helps you come across as confident and in control of your topic,” says Feast. “You also need to control the tension in your vocal cords -- relaxing them makes a big difference.”

Cogito scans for keywords as part of the analysis, but these are far less indicative of a conversation’s success than “interaction patterns,” says Feast. In part, this is because reps often follow scripts that have been carefully vetted for maximum impact. “The reps are generally focused on the words and lose track of how they’re coming across,” adds Feast. “If you go to a café in another country and observe people speaking, you can probably tell how the conversation is going even if you don’t understand the words.”

Cogito’s AI algorithms not only analyze each voice in isolation, but also evaluate the conversational dynamics. “A conversation is like a dance,” says Feast. “If you are out of sync with your partner, it is very observable.” One example is that neither side should dominate the conversation. “It’s very important to ensure both parties participate in an effective conversation.”

The software can also help sales and service reps improve their “person perception” – the ability to recognize and respond to social signals. “We all think we’re great at our ability to effectively perceive others, but a lot of us are not,” says Feast. “To be more charming, you need to recognize social signals, correctly interpret them, and respond to them appropriately. The most important thing is the recognition – realizing when something is happening and acknowledging it to the other party. Even if you are not exactly correct, it engenders trust and builds rapport.”

Cogito’s staff spends a lot of time optimizing the presentation of tips to agents. “Our cognitive psychologists work to understand what behaviors are relevant, and how best to present feedback in real-time,” says Feast. “Since we have united the measurement system with the means to improve, we always know the impact of our guidance has on behavior. We try to offer advice in a positive and consumable fashion, and experiment with different notification strategies to ensure we always optimize impact without overwhelming the agent.”

Cogito’s analysis of different conversational strategies and outcomes not only helps the software continually improve via machine learning, but it also provides key insights into customer behavior and their perception of an interaction. Objective behavioral analysis of conversations is far more comprehensive and timely then what can be gleaned from a traditional survey.

Cogito’s analysis is language independent, and has been deployed in a number of countries. “Most of the important signals in a conversation are universal properties of humans rather than of language and culture,” says Feast. “The communication of attitude or distress is rooted in ancient brain systems that were developed long before modern language.”

Cogito’s goal of encouraging relaxed, yet professional conversations sometimes conflicts with pre-existing call center scripts. “Existing call center tools are focused on helping agents follow policies and procedures and capture customer data, which can often make them appear as if they are just a database on the phone,” says Feast. “If you’re calling customer service, you’ve got a complex problem, and you’re looking for a trusted human interaction. Often, the agent can’t create a connection because of the structure placed around them. The best companies empower front line employees to deliver more human, empathic experiences.”

When asked if Cogito can remain relevant in a world where chat bots are starting to replace human agents, Feast argues that today’s AI is not sufficiently advanced. “The problems our customers deal with typically concern complex health or finance issues, and the current AI can’t handle that on its own. Many customer service problems are solved by a question answer coevolution process, which computers aren’t great at yet. Even if an AI could eventually handle this, I believe we will always prefer talking to fellow humans about complex or emotional issues.”

Cogito mainly targets service, but it can also be used for sales, usually with little modification. “The line between sales and service is very blurred,” says Feast. “We’ve had tremendous success on inbound sales, such as customers calling in to buy an insurance policy or for existing customers wishing to add new services to their existing plans.”

Cogito may eventually release specialized versions of the software optimized for negotiations, meetings or counseling sessions. People often ask Feast if Cogito could develop a personal assistant to advise them on speeches or phone conversations.

When asked if Cogito could eventually expand to integrate facial recognition for use in video conferencing, potentially even in a Google Glass like encounter, Feast suggests it’s possible: “At its base, Cogito is an extremely high performing behavioral signals processing platform that is agnostic to the type of signal. Our research suggests that voice is the most data rich source of behavioral signals, but our platform can consume signals, execute models, and present feedback in many forms.”

Yet, more than technological challenges are involved. “Ultimately, we believe that people should have a real-time coach for all their important business and personal conversations,” says Feast. “But the key questions to ask for each use case are what positive behavioral changes can we drive and what is the best way to deliver information so people can easily make use of it? The potential for expanding to personal use cases is enormous, but right now we are focused on an application that is incredibly impactful for millions of phone professionals and the hundreds of millions of customers they serve.”



About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
July 6, 2017

Engineering Microbes for Manufacturing

For a group of former MIT graduate students-turned-entrepreneurs, the future of programming has little to do with silicon. Instead, they are focused on engineering biology; specifically, manipulating the DNA of various organisms like yeast to become micro-manufacturers of products ranging from perfumes to nutritional supplements.


Austin Che
Startup Founder
Ginkgo Bioworks

For a group of former MIT graduate students-turned-entrepreneurs, the future of programming has little to do with silicon. Instead, they are focused on engineering biology; specifically, manipulating the DNA of various organisms like yeast to become micro-manufacturers of products ranging from perfumes to nutritional supplements. Together, they founded Ginkgo Bioworks in 2008 to commercialize their synthetic biology technology and ideas.

Starting with a five-person team of MIT grad students and their advisor, Tom Knight, formerly of the MIT Computer Science and Artificial Intelligence Laboratory, Ginkgo’s mission is to radically scale up engineered organisms to make an extensive variety of products.

“When we started the company synthetic biology was a pretty new field and we wanted to take it to the next level to see if we could commercialize some of the ideas that we had,” says Austin Che, PhD, Ginkgo co-founder, who was convinced by Knight that the next big technology era involved programming biology instead of silicon. The team did not have a specific technology they planned to use in 2008 but after several years of exploring the field, the company has found its technical feet and opened its doors – and vats of simmering designer organisms—to customers in 2014 when it simultaneously received its first funding. Now, Ginkgo is enjoying explosive growth and interest in the company.



DNA as Code
Ginkgo uses DNA as its programming code instead of typical programming language and silicon. Che acknowledges that while silicon has been great at processing information it fails when interacting with the physical world. By comparison, biology is great at manipulating atoms.

By writing specific DNA code into the genetics of its manufacturing organisms, Ginkgo programmers can precisely direct them to produce the compounds of interest. “We just have to learn which letters to put into the organism,” Che says, adding that figuring out what DNA combinations to use – the string of A, T,G, C bases that pair up to make DNA—is the essential first step of any project. The second step is to add that DNA into the organisms which, in the third step, hopefully make the compounds the company is interested in for a given client.

Ginkgo claims to be the world’s largest writer of DNA. In one year, the company generates 500 million base pairs of DNA.

Biological Foundry
Their two main production facilities, called foundries or Bioworks, house the engineered organisms to churn out the goods. The company recently demonstrated scale-up capacity of 50,000 liters. A third foundry is in the building phase now.

Che explains the Bioworks concept is to use the microbes as a systematic platform that makes it easy to make many different molecules. “When I was in grad school, this kind of synthetic biology was done by highly-trained scientists at the bench pipetting. A lot of manual labor,” he says. “We don’t think that’s a very good use of a scientist’s time.”

Instead, within each Bioworks, robotics and equipment automate each step of engineering an organism through to manufacturing and product testing. “We try to batch things together and take advantage of cost, scale and automation so that the PhD scientist can spend their time thinking about how to design new organisms rather than pipetting,” Che adds. “The way we put them together is kind of our secret sauce for how to design each foundry.”

Ginkgo is currently working with about 20 different customers producing approximately 40 different products. Most are in the chemical industry involving flavors and fragrances. Other partners produce cosmetics and nutritional supplements but Ginkgo sees its manufacturing platform can be used in many areas – some not so obvious. One of its projects involves reviving extinct scents by examining the genomes of extinct flowers and bringing them back to see what scents they could have made.

“We hope to find partners we can work with in pharma, agriculture, or others where we can apply our biological tools for manufacturing or organism engineering to bring value to new partners,” Che adds. “We view biology as a manufacturing platform for making a wide variety of molecules; so anything that you can imagine – anything chemical or physical – we think that biology should be able to do it.”



About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
June 28, 2017

Predictive Analytics for Retailers

Celect is helping retailers reveal true demand, leverage existing data, and optimize their stock using predictive analytics and machine learning technology.


John Andrews
CEO
Celect

“Retail is clearly going through a transformation right now,” says John Andrews, CEO of Celect, a predictive analytics machine learning technology company focused on retail. “The reality is that stores are not going away. Customers are looking for experiences, and part of that experience is to touch the product and to try the product on,” he says. Improving the overall customer experience means understanding at a more precise and granular level how customers choose between an assortment of products. The Celect Choice Engine helps retailers identify and predict what a customer faced with an assortment of products is likely to buy.

Customer Choice Modeling
“The context of every customer’s decision delivers a very rich signal in terms of how individual customers choose,” says Andrews. At the core of this is customer choice modeling. When a customer walks into a store and buys a product, retailers use transaction-level information to personalize the experience and to optimize operations within their store. “But what if in addition to the customer’s purchase, you also knew what their options were?” asks Andrews. Said another way: What if you knew what customers didn’t buy?


That’s where the predictive piece comes in. One of the key challenges retailers have is around the problem of sparse data. In terms of identifying buying patterns of an individual customer over the course of a year, a retailer may only have one or two data points. Gathering data on a customer’s buying patterns, their browse history, and what they put in or remove from their shopping cart produces a very robust model that allows Celect to predict the likelihood of future behavior. “Based on this,” says Andrews, “what are the right products to put in front of an individual customer and in what quantity?”

Inventory Portfolio Optimization Challenge
At the highest level, the inventory portfolio optimization challenge is the problem Celect is solving: How much of an individual product does a retailer need to buy and how is that product going to interact with another product? “The complexity of that model can be baffling,” says Andrews. Until Celect came along, there was no real system that could handle such complexity. “We have a solution that can help merchants and planners identify what products they should be bringing into their assortment, and where they should be putting those particular products,” says Andrews. One of the core capabilities of the inventory portfolio is being able to identify how well a product will sell in the future based on history and purchases.

Inventory Portfolio Challenge
Around the idea of Inventory Portfolio Optimization is Celect’s longer-term vision. Be it online, direct, wholesale, or retail in-store experiences, Andrews sees a much bigger opportunity across the entire supply chain, from brand and manufacturers to distribution and retail. “At each step across that supply chain, we identify how much a retailer should be buying, at which distribution centers or fulfillment centers the product should be brought, how much of that product should go to each individual store, and in what assortment,” says Andrews.

Plan. Buy. Allocate. Fulfill.
Under the umbrella of Inventory Portfolio Optimization, Celect is focused on four core solutions, mapping directly to the process most retailers live by. The first, Plan Optimization, used in strategic planning and in merchandise financial planning, helps retailers identify how much they should be spending on specific departments, brands or styles, the demand for those products within their customer base, and in which stores they can sell those products.
The next module, Buy Optimization, helps retailers determine the demand for a product, whether they should be going big or buying small. “Getting that right early in the decision process is incredibly important in terms of what final revenue and markdown numbers are going to look like for a retailer at the end of the season,” says Andrews.

The third piece of optimizing inventories is Allocation Optimization. “Now, I’ve got an assortment of products. I know how much of each product I have. Where should I be allocating those products? Get the product into each store, in the right assortment and in the right number based on the buying patterns of customers in those stores,” says Andrews.

The final piece is the Order Fulfillment Optimization solution – the process of intelligently leveraging store inventories to fulfill online orders. Here, the retailer is trying to push as much of the inventory into their stores, use their stores as fulfillment centers, and then intelligently identify from which stores they should be shipping that product. Andrews says understanding the demand for a product over a course of a season can make for a much smarter decision in terms of which store to ship products from.

Using Your Data for Better Decisions
“Omni-channel—it’s probably an overused term—but it’s a real issue and challenge for retailers to figure out how to leverage every interaction point, every channel with a customer, and then be able to optimize across all of those different channels to provide the best experience to customers,” says Andrews. Whether customers want to buy something online and return it to a store, buy something online and pick it up in a store, or buy something in a store and mail it back, involves an enormous amount of complexity from an operational perspective. “At the end of the day,” he says, “it all comes down to getting the right product in front of the right customer at the right time.” As part of this transformation, retail is going evolve and change. Some retailers will have fewer stores; others will open more stores.

Andrews says you don’t need to be Amazon to use your data and make smarter decisions. “Predictive analytics and leveraging machine learning to supplement the decision-making is at the top of every retail executive’s priority list. They quite simply want to understand how to use it, how it gets integrated within their environment,” he says. As Celect has grown, so have the data points on how different retailers use information and science to help supplement decision-making, to help retailers make better decisions, to increase revenue, reduce stock-outs, and reduce markdowns within the customer experience. “The retailers who are able to truly understand how their customers are interacting with products and how the products are interacting with each other, and are then able to optimize on that are the ones who are going to win.”




About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
June 28, 2017

WiTricity and IHI Partner to Bring Wireless Charging to Electric Vehicles

Industrial Liaison Program helps to launch successful long-term technology collaboration.


David Schatz
WiTricity Vice President of Sales
and Business Development Automotive
Back in 2009, WiTricity Corporation was an MIT spinoff company with a novel wireless-charging technology and a need to find early commercial partners. At an Industrial Liaison Program (ILP) event at MIT, the startup’s dramatic desktop demonstration of wireless power caught the eye of Yoshi Iso, a technology scout for IHI Corp., a major international technology company.

The two companies began to talk, and IHI examined the WiTricity charging technology at its corporate research and development facilities in Tokyo. In 2012, IHI and WiTricity entered into a long-term collaboration and commercialization agreement.

Under the agreement, IHI is licensed by WiTricity to manufacture and supply wireless charging systems for automotive and industrial applications on a global basis. In addition, the companies collaborate to accelerate the development of the technology and to promote international standards for wireless charging systems.

“IHI is a heavy industry company and a leading supplier of aerospace engines and vehicle turbochargers, along with resource, energy and environmental products,” says Toshiro Fujimori, general manager of the New Products Incubation Center in the IHI corporate research and development organization in Tokyo. “To expand our business, we search for spinout companies that have competent technologies and fit our business plan.

WiTricity and IHI
partnered to offer wireless
charging stations around the globe. The MIT Startup Exchange has been very helpful in this regard, and we chose WiTricity to collaborate in the growing market of electric vehicles, and we are working together to introduce our first wireless-charging products using WiTricity technologies in a few years.”

“As a newly formed startup spun out of MIT, we benefited tremendously from the chance to meet potential customers at ILP-sponsored events and by introductions made by ILP staff to their member companies,” says David Schatz, WiTricity vice president of sales and business development. “At the time, IHI was unfamiliar to WiTricity. As a result of meeting its U.S. technology scout, we were able to engage with IHI, and we have since formed a lasting and mutually beneficial business relationship that has been exceptionally valuable to us.”
An early member of ILP’s Startup Exchange, WiTricity continues to draw on ILP’s connections and expertise to explore potential business arrangements with major automotive and industrial suppliers around the globe.

IHI is now testing electric vehicles equipped with wireless charging systems, for residential settings in a garage or carport, as well as in public facilities. IHI is very active in public infrastructure for transportation and power generation and distribution, and it will utilize its expertise in wireless charging technology to improve the efficiency, safety and environmental friendliness of future transportation systems.

Working with multiple automotive manufacturers, IHI has showcased protoype wireless-charging automotive systems at a number of public demonstrations of electric car concepts, such as a Honda Fit displayed at the automotive manufacturer’s Smart Home” in Saitama, Japan.

In addition to its partnership with IHI, WiTricity is working with numerous other automotive makers and their leading suppliers. No licensees have announced specific product details and timetables, but the first automobiles embodying the wireless charging technology are expected to appear this fall.

About WiTricity
WiTricity Corporation provides technology to enable wireless power transfer over distance using magnetic resonance. Through deep domain expertise, semiconductor offerings, a strong intellectual property portfolio and an extensive reference design library, WiTricity works with innovative companies to incorporate WiTricity technology in their products and solutions. With a growing list of global customers in the consumer electronics, automotive, medical devices and industrial markets, the company has emerged as the leader in wireless power transfer over distance. For more information, visit www.witricity.com, or follow WiTricity on Facebook, Twitter and LinkedIn.

About IHI
IHI Corporation (IHI) is a global engineering, construction and manufacturing company that provides a broad range of products in four business areas: Resources, Energy and Environment; Social Infrastructure and Offshore Facilities; Industrial System and General-Purpose Machinery; and Aero Engine, Space and Defense. IHI was established in Tokyo as Ishikawajima Shipyard in 1853, and currently employs more than 27,000 people around the world. The company's consolidated revenues for fiscal 2015 (ended March 31, 2016) totaled 1,539 billion yen. For more information, visit http://www.ihi.co.jp/en/.


About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.

StartupExchange
June 28, 2017

Tulip and Merck KGaA Partner to Accelerate Operator Training for Complex Assembly

Internet-of-Things-enabled manufacturing apps reduce Merck’s training cost by 57 percent.


Natan Linder
Founder, Tulip


At a Merck KGaA factory, fully training new operators on the assembly of a highly complicated lab equipment took a trainer over 200 hours. Using manufacturing apps in a joint project with Tulip of Somerville, Massachusetts, Merck engineers have cut that time by over 90 percent.

In addition to speeding operator training, the proof-of-concept collaboration between the startup and the giant manufacturer successfully employed Tulip software to begin measuring and analyzing assembly procedures on the production line.

“This proof of concept was a huge success story,” says Jerry Megaro, Merck KGaA’s Global Head of Advanced Analytics & Internet of Things (IoT). “Tulip’s technology offers a blend of human-operator-focused technology that takes advantage of the Industrial IoT space, solving problems that we did not have the inhouse expertise to solve on our own.”

Tulip’s manufacturing operating system software allows engineers without programming expertise to create shop floor apps, with interactive step-by-step work instructions that are enabled with sensing and data collection using IoT gateways. The Tulip apps access cloud-based data and real-time analytics to help companies measure and optimize their manufacturing operations.

Tulip is an MIT STEX25 firm, one of an elite cohort of startup companies given priority access to MIT’s Industrial Liaison Program (ILP) member companies. The MIT Startup Exchange and ILP brought Tulip together with Merck.



Tulip creates digital manufacturing
apps that integrate operator
and machine data to decrease
errors and reduce training time.


“ILP made the right introduction, with the right match between what Merck was looking for and what we were doing,” says Natan Linder, Tulip co-founder.

Megaro began discussions with the startup after a Merck digital innovation scout spotted Tulip at an ILP event in 2016. He ended up presenting Tulip with the challenge to improve training for a highly manual assembly process with very stringent quality and performance specifications, on a large production line at a Molsheim, France facility.

“We took a purely paper-based system and automated it,” Megaro says. “We thought it would be a great opportunity to demonstrate how their technology works and how we could use it solve some good problems. We also thought that we could help to influence Tulip’s future product designs, which is one of the advantages of being an early adopter with a startup company.”

The Merck engineers who built these apps “got very little training on the software tool itself, literally hours, and they started building additional apps on their own,” says Linder. Deployment in the plant also went quickly, with the entire project completed in under three months.

Merck and Tulip found that new shopfloor operators could progress through the assembly training almost entirely by themselves, freeing up the seasoned operators who normally were required to lead them through the processes. Merck estimates that seasoned operators have saved over 92% of the time previously spent on training, freeing them up to assemble products. With training apps new operators do not need to wait for trainers to free up to ask questions on assembly and so progress more rapidly through the training, saving approximately 30% of the training time. Merck estimates that with Tulip, total training cost is reduced by 57%.

“The Tulip apps also could capture a lot of ancillary data, like how operators interact with the parts and how fast do they move, and could connect to other devices such as scanners,” Megaro says. “Once you have the ability to measure, you can make procedures run more efficiently—by examining the causes of part failures, for example.”

Merck and Tulip are in ongoing conversations about potential other use of Tulip products.

“The open collaboration between the two companies was critical in validating many of the product and solution promises that our team has been working on since our inception,” says Linder.

“MIT’s Startup Exchange program has been invaluable to us at this stage in our development,” he adds. “We get great introductions, and showcases where we can put on a demo and get a lot of facetime exposure to many companies at once.”

About Tulip
Tulip grew out of a team of PhDs at MIT leading groundbreaking research in augmented reality systems, intelligent hardware sensors, computer vision, assistive user interfaces, and applied machine learning. Each team member had manufacturing experience and recognized that their research collectively had the potential to radically transform the manufacturing industry. Tulip was formed to bring these latest technological developments from the lab to the shopfloor. Multiple Fortune 500 customers have implemented Tulip to solve some of manufacturing’s most pressing challenges. We enable the manufacturing workforce to create shopfloor apps to improve work instructions, visualize relevant information real-time and connect existing shopfloor equipment.


About Merck KGaA
Merck KGaA of Darmstadt, Germany, which is known as “Merck” outside the United States and Canada, is a leading science and technology company for innovative and top-quality high-tech products in healthcare, life science and performance materials. Founded in 1668, Merck KGaA is the world’s oldest pharmaceutical and chemical company. In the United States and Canada, the company also operates as EMD Serono in the biopharmaceuticals business, as MilliporeSigma in the life science business, and as EMD Performance Materials in the materials business.




About MIT Startup Exchange, STEX25, and MIT’s Industrial Liaison Program (ILP)
MIT Startup Exchange actively promotes collaboration and partnerships between MIT-connected startups and industry. Qualified startups are those founded and/or led by MIT faculty, staff, or alumni, or are based on MIT-licensed technology. Industry participants are principally members of MIT’s Industrial Liaison Program (ILP).

MIT Startup Exchange maintains a propriety database of over 1,500 MIT-connected startups with roots across MIT departments, labs and centers; it hosts a robust schedule of startup workshops and showcases, and facilitates networking and introductions between startups and corporate executives.

STEX25 is a startup accelerator within MIT Startup Exchange, featuring 25 “industry ready” startups that have proven to be exceptional with early use cases, clients, demos, or partnerships, and are poised for significant growth. STEX25 startups receive promotion, travel, and advisory support, and are prioritized for meetings with ILP’s 230 member companies.

MIT Startup Exchange and ILP are integrated programs of MIT Corporate Relations.