The design of industrial processes

When organic chemists identify a useful chemical compound — a new drug, for instance — it’s up to chemical engineers to determine how to mass-produce it.
There could be 100 different sequences of reactions that yield the same end product. But some of them use cheaper reagents and lower temperatures than others, and perhaps most importantly, some are much easier to run continuously, with technicians occasionally topping up reagents in different reaction chambers.
Historically, determining the most efficient and cost-effective way to produce a given molecule has been as much art as science. But MIT researchers are trying to put this process on a more secure empirical footing, with a computer system that’s trained on thousands of examples of experimental reactions and that learns to predict what a reaction’s major products will be.
The researchers’ work appears in the American Chemical Society’s journal Central Science. Like all machine-learning systems, theirs presents its results in terms of probabilities. In tests, the system was able to predict a reaction’s major product 72 percent of the time; 87 percent of the time, it ranked the major product among its three most likely results.
“There’s clearly a lot understood about reactions today,” says Klavs Jensen, the Warren K. Lewis Professor of Chemical Engineering at MIT and one of four senior authors on the paper, “but it’s a highly evolved, acquired skill to look at a molecule and decide how you’re going to synthesize it from starting materials.”
With the new work, Jensen says, “the vision is that you’ll be able to walk up to a system and say, ‘I want to make this molecule.’ The software will tell you the route you should make it from, and the machine will make it.”
With a 72 percent chance of identifying a reaction’s chief product, the system is not yet ready to anchor the type of completely automated chemical synthesis that Jensen envisions. But it could help chemical engineers more quickly converge on the best sequence of reactions — and possibly suggest sequences that they might not otherwise have investigated.

Increases processing speed while reducing energy consumption

For decades, computer chips have increased efficiency by using “caches,” small, local memory banks that store frequently used data and cut down on time- and energy-consuming communication with off-chip memory.
Today’s chips generally have three or even four different levels of cache, each of which is more capacious but slower than the last. The sizes of the caches represent a compromise between the needs of different kinds of programs, but it’s rare that they’re exactly suited to any one program.
Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have designed a system that reallocates cache access on the fly, to create new “cache hierarchies” tailored to the needs of particular programs.
The researchers tested their system on a simulation of a chip with 36 cores, or processing units. They found that, compared to its best-performing predecessors, the system increased processing speed by 20 to 30 percent while reducing energy consumption by 30 to 85 percent.
“What you would like is to take these distributed physical memory resources and build application-specific hierarchies that maximize the performance for your particular application,” says Daniel Sanchez, an assistant professor in the Department of Electrical Engineering and Computer Science (EECS), whose group developed the new system.
“And that depends on many things in the application. What’s the size of the data it accesses? Does it have hierarchical reuse, so that it would benefit from a hierarchy of progressively larger memories? Or is it scanning through a data structure, so we’d be better off having a single but very large level? How often does it access data? How much would its performance suffer if we just let data drop to main memory? There are all these different tradeoffs.”

Power consumption could help make the systems portable

In recent years, the best-performing artificial-intelligence systems — in areas such as autonomous driving, speech recognition, computer vision, and automatic translation — have come courtesy of software systems known as neural networks.
But neural networks take up a lot of memory and consume a lot of power, so they usually run on servers in the cloud, which receive data from desktop or mobile devices and then send back their analyses.
Last year, MIT associate professor of electrical engineering and computer science Vivienne Sze and colleagues unveiled a new, energy-efficient computer chip optimized for neural networks, which could enable powerful artificial-intelligence systems to run locally on mobile devices.
Now, Sze and her colleagues have approached the same problem from the opposite direction, with a battery of techniques for designing more energy-efficient neural networks. First, they developed an analytic method that can determine how much power a neural network will consume when run on a particular type of hardware. Then they used the method to evaluate new techniques for paring down neural networks so that they’ll run more efficiently on handheld devices.
The researchers describe the work in a paper they’re presenting next week at the Computer Vision and Pattern Recognition Conference. In the paper, they report that the methods offered as much as a 73 percent reduction in power consumption over the standard implementation of neural networks, and as much as a 43 percent reduction over the best previous method for paring the networks down.

Provides readers with detailed summaries

From Reddit to Quora, discussion forums can be equal parts informative and daunting. We’ve all fallen down rabbit holes of lengthy threads that are impossible to sift through. Comments can be redundant, off-topic or even inaccurate, but all that content is ultimately still there for us to try and untangle.
Sick of the clutter, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed “Wikum,” a system that helps users construct concise, expandable summaries that make it easier to navigate unruly discussions.
“Right now, every forum member has to go through the same mental labor of squeezing out key points from long threads,” says MIT Professor David Karger, who was senior author on a new paper about Wikum. “If every reader could contribute that mental labor back into the discussion, it would save that time and energy for every future reader, making the conversation more useful for everyone.”
The team tested Wikum against a Google document with tracked changes that aimed to mimic the collaborative editing structure of a wiki. They found that Wikum users completed reading much faster and recalled discussion points more accurately, and that editors made edits 40 percent faster.
Karger wrote the new paper with PhD students Lea Verou and Amy Zhang, who was lead author. The team presented the work last week at ACM’s Conference on Computer-Supported Cooperative Work and Social Computing in Portland, Oregon.
How it works
While wikis can be a good way for people to summarize discussions, they aren’t ideal because users can’t see what’s already been summarized. This makes it difficult to break summarizing down into small steps that can be completed by individual users, because it requires that they spend a lot of energy figuring out what needs to happen next. Meanwhile, forums like Reddit let users “upvote” the best answers or comments, but lack contextual summaries that help readers get detailed overviews of discussions.
Wikum bridges the gap between forums and wikis by letting users work in small doses to refine a discussion’s main points, and giving readers an overall “map” of the conversation.
Readers can import discussions from places such as Disqus, a commenting platform used for publishers like The Atlantic. Then, once users create a summary, readers can examine the text and decide if they want to expand the topic to read more. The system uses color-coded “summary trees” that show topics at different levels of depth and lets readers jump between original comments and summaries.

Help make a ubiquitous model of decision processes

Markov decision processes are mathematical models used to determine the best courses of action when both current circumstances and future consequences are uncertain. They’ve had a huge range of applications — in natural-resource management, manufacturing, operations management, robot control, finance, epidemiology, scientific-experiment design, and tennis strategy, just to name a few.
But analyses involving Markov decision processes (MDPs) usually make some simplifying assumptions. In an MDP, a given decision doesn’t always yield a predictable result; it could yield a range of possible results. And each of those results has a different “value,” meaning the chance that it will lead, ultimately, to a desirable outcome.
Characterizing the value of given decision requires collection of empirical data, which can be prohibitively time consuming, so analysts usually just make educated guesses. That means, however, that the MDP analysis doesn’t guarantee the best decision in all cases.
In the Proceedings of the Conference on Neural Information Processing Systems, published last month, researchers from MIT and Duke University took a step toward putting MDP analysis on more secure footing. They show that, by adopting a simple trick long known in statistics but little applied in machine learning, it’s possible to accurately characterize the value of a given decision while collecting much less empirical data than had previously seemed necessary.
In their paper, the researchers described a simple example in which the standard approach to characterizing probabilities would require the same decision to be performed almost 4 million times in order to yield a reliable value estimate.

Database queries could prevent customer profilin

Most website visits these days entail a database query — to look up airline flights, for example, or to find the fastest driving route between two addresses.
But online database queries can reveal a surprising amount of information about the people making them. And some travel sites have been known to jack up the prices on flights whose routes are drawing an unusually high volume of queries.
At the USENIX Symposium on Networked Systems Design and Implementation next week, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and Stanford University will present a new encryption system that disguises users’ database queries so that they reveal no private information.
The system is called Splinter because it splits a query up and distributes it across copies of the same database on multiple servers. The servers return results that make sense only when recombined according to a procedure that the user alone knows. As long as at least one of the servers can be trusted, it’s impossible for anyone other than the user to determine what query the servers executed.
“The canonical example behind this line of work was public patent databases,” says Frank Wang, an MIT graduate student in electrical engineering and computer science and first author on the conference paper. “When people were searching for certain kinds of patents, they gave away the research they were working on. Stock prices is another example: A lot of the time, when you search for stock quotes, it gives away information about what stocks you’re going to buy. Another example is maps: When you’re searching for where you are and where you’re going to go, it reveals a wealth of information about you.”
Honest broker
Of course, if the site that hosts the database is itself collecting users’ data without their consent, the requirement of at least one trusted server is difficult to enforce.
Wang, however, points to the increasing popularity of services such as DuckDuckGo, a search engine that uses search results from other sites, such as Bing and Yahoo, but vows not to profile its customers.
“We see a shift toward people wanting private queries,” Wang says. “We can imagine a model in which other services scrape a travel site, and maybe they volunteer to host the information for you, or maybe you subscribe to them. Or maybe in the future, travel sites realize that these services are becoming more popular and they volunteer the data. But right now, we’re trusting that third-party sites have adequate protections, and with Splinter we try to make that more of a guarantee.”

Programming language and online community

Many of the children taking part in Scratch Day 2017 at the MIT Media Lab on May 6 were not even born when the Scratch programming language was released in 2007.
“It’s exceeded our expectations,” said MIT LEGO Papert Professor of Learning Research Mitchel Resnick, head of the Media Lab’s Lifelong Kindergarten research group, which develops Scratch. “We’re really excited about the way Scratch has enabled kids around the world to experiment, explore, and express themselves with computational tools. As children create and share Scratch projects, they’re learning to think creatively, reason systematically, and work collaboratively — essential skills for everyone in today’s society.”
Scratch is a free programming tool for children aged 8-16 to create animations, games, music, and interactive stories. It’s also an online community where children can share their projects and collaborate with one another. Over the past decade, more than 18 million people have joined the Scratch online community, from every country in the world except on the continent of Antarctica. Scratchers have shared more than 22 million projects, with 30,000 new ones every day.
Each year in May, children, parents, and educators gather at Scratch Day events to meet in person and to celebrate Scratch and ScratchJr, a simplified version for children aged 5-7, released in 2014. This month, on the 10th anniversary of Scratch, there are more than 1,100 Scratch Day events in almost 70 countries.
The May 6 event at the Media Lab drew 300 children, parents, and teachers from across the Boston area and beyond. When tickets were made available online last month, they sold out in just three hours.
The first to arrive was 16-year-old Jocelyn from Richmond, Virginia, whose Scratch username is CrazyNimbus. “Scratch was on our computers at school, and I discovered it just when I was looking for ways to learn how to code,” she said. Jocelyn started using the language offline when she was 11 and joined the online community the following year. “I originally signed up because I wanted to make a game, but then I found out how exciting and supportive the community was. I create all kinds of things — animations, stories, interactive games, whatever comes to mind. And the constructive feedback I get from other Scratchers inspires me to add more to my projects.”
“Jocelyn is essentially an ‘artsy’ kid,” said her father, Don Marencik. “But Scratch has helped her use her analytical side to learn computer science as a way to express her creative side.” Another benefit, Marencik said, is that gender, race, and other “labels” have no place in Scratch: “Everybody’s equal.” Jocelyn also runs Scratch camps, and last year she set up Got Tec Richmond to provide technology equipment to underserved students and teachers in the Richmond area.
“All of you have been part of how Scratch has changed over the past 10 years,” Scratch co-creator and Media Lab research scientist Natalie Rusk told the children as they sat on bean bags, laughing at pictures of how the Scratch Cat mascot has also evolved in that time. “Scratch really builds on the Logo programming language that came out of the work of Seymour Papert, who was a founding faculty member of the Media Lab,” Rusk explained. “The research has shown that the best way for kids to learn is by constructing something that’s personally meaningful to them. It’s by constructing something that you really start to think about your own ideas, and reflect on them. Kids try making something and see ‘Does that work or not?’ Then they fix it and get feedback from others. It’s by creating something that they care about that motivates them to problem solve and learn.”

Viral video created to combat media stereotypes

Layla Shaikley SM ’13 began her master’s in architecture at MIT with a hunger to redevelop nations recovering from conflict. When she decided that data and logistics contributed more immediately to development than architecture did, ­Shaikley switched to the Media Lab to work with Professor Sandy ­Pentland, and became a cofounder of Wise Systems, which develops routing software that helps companies deliver goods and services.
“There’s nothing more creative than building a company,” Shaikley says. “We plan the most effective routes and optimize them in real time using driver feedback. Better logistics can dramatically reduce the number of late deliveries, increase efficiency, and save fuel.”
But Shaikley is perhaps better known for a viral video, “Muslim Hipsters: #mipsterz,” that she and friends created to combat the media stereotypes of Muslim women. It reached hundreds of thousands of viewers and received vigorous positive and negative feedback.
The video “is a really refreshing, jovial view of an underrepresented identity: young American Muslim women with alternative interests in the arts and culture,” Shaikley says. “The narrow media image is so far from the real fabric of Muslim-­American life that we all need to add our pieces to the quilt to create a more accurate image.”
Shaikley’s parents moved from Iraq to California in the 1970s, and she and her five siblings enjoyed a “quintessentially all-­American childhood,” she says. “I grew up on a skateboard, and I love to surf and snowboard.” She feels deeply grateful to her parents, who “always put our needs first,” she adds. “When we visited relatives in Iraq, we observed what life is like when people don’t have the privilege of a free society. Those experiences really shaped my understanding of the world and also my sense of responsibility to give back.”
Shaikley says the sum of her diverse life experiences has helped her as a professional with Wise Systems and as a voice for underrepresented Muslim women.
“My work at MIT under [professors] Reinhard Goethert and Sandy ­Pentland was critical to my career and understanding of data as it relates to developing urban areas,” she says. “And every piece of my disparate experiences, which included the coolest internship of my life with NASA working on robotics for Mars, has played a huge role.”

Person of the world who wants to learn something

Raul Boquin, now an MIT senior, remembers the assignment from his freshman year as if it were yesterday. During a leadership workshop, he was asked to write a headline for a newspaper in his imagined future. The words that came to mind resonated so strongly that they now hang on the walls of his dorm room: “Equal opportunities in education for all.”
“I realized that I didn’t come to MIT because it was the best engineering school, but because it was the best place to discover what I was truly passionate about,” he says. “MIT pushed me to my limits and made me able to say ‘I don’t have to be the number one math person, or the number one computer science person, to make a difference’ with the passion I ended up having, which is education.”
Boquin, who is majoring in mathematics with computer science, predicts his life’s work will be to “find a way to adapt education to every person of the world who wants to learn something.”
More to education than teaching
Boquin’s first forays into education followed a relatively traditional path. As part of the undergraduate coursework he needed for his education concentration, he spent time observing teachers in local middle and high schools.
“But at the end of sophomore year, I realized that there was a lot more to education than just teaching.
The summer before his junior year, Boquin worked as a counselor and teaching assistant at Bridge to Enter Advanced Mathematics (BEAM). “It originally started as just a math camp for students in the summer, teaching them things like topology and number theory,” Boquin says. “These were seventh grade Hispanic and black children, and they loved it. And they were amazing at it.”
On a campus in upstate New York, Boquin taught classes by day and talked to students about his own work in mathematics by night. He also designed parts of the BEAM curriculum and came up with fun ways of teaching the lessons. “It was inspiring because it was like I wasn’t only a teacher, but I was a mentor and a friend,” he says.
Back at MIT, with the guidance of Eric Klopfer, professor and director of the Scheller Teacher Education Program and the Education Arcade, Boquin joined lead developer Paul Medlock-Walton to work on Gameblox, through MIT’s Undergraduate Research Opportunities Program (UROP).

Diamond optical circuits could work at large scales

Quantum computers are experimental devices that offer large speedups on some computational problems. One promising approach to building them involves harnessing nanometer-scale atomic defects in diamond materials.
But practical, diamond-based quantum computing devices will require the ability to position those defects at precise locations in complex diamond structures, where the defects can function as qubits, the basic units of information in quantum computing. In today’s of Nature Communications, a team of researchers from MIT, Harvard University, and Sandia National Laboratories reports a new technique for creating targeted defects, which is simpler and more precise than its predecessors.
In experiments, the defects produced by the technique were, on average, within 50 nanometers of their ideal locations.
“The dream scenario in quantum information processing is to make an optical circuit to shuttle photonic qubits and then position a quantum memory wherever you need it,” says Dirk Englund, an associate professor of electrical engineering and computer science who led the MIT team. “We’re almost there with this. These emitters are almost perfect.”
The new paper has 15 co-authors. Seven are from MIT, including Englund and first author Tim Schröder, who was a postdoc in Englund’s lab when the work was done and is now an assistant professor at the University of Copenhagen’s Niels Bohr Institute. Edward Bielejec led the Sandia team, and physics professor Mikhail Lukin led the Harvard team.
Appealing defects
Quantum computers, which are still largely hypothetical, exploit the phenomenon of quantum “superposition,” or the counterintuitive ability of small particles to inhabit contradictory physical states at the same time. An electron, for instance, can be said to be in more than one location simultaneously, or to have both of two opposed magnetic orientations.
Where a bit in a conventional computer can represent zero or one, a “qubit,” or quantum bit, can represent zero, one, or both at the same time. It’s the ability of strings of qubits to, in some sense, simultaneously explore multiple solutions to a problem that promises computational speedups.
Diamond-defect qubits result from the combination of “vacancies,” which are locations in the diamond’s crystal lattice where there should be a carbon atom but there isn’t one, and “dopants,” which are atoms of materials other than carbon that have found their way into the lattice. Together, the dopant and the vacancy create a dopant-vacancy “center,” which has free electrons associated with it. The electrons’ magnetic orientation, or “spin,” which can be in superposition, constitutes the qubit.

Vibrating motors and a Braille interface

Computer scientists have been working for decades on automatic navigation systems to aid the visually impaired, but it’s been difficult to come up with anything as reliable and easy to use as the white cane, the type of metal-tipped cane that visually impaired people frequently use to identify clear walking paths.
White canes have a few drawbacks, however. One is that the obstacles they come in contact with are sometimes other people. Another is that they can’t identify certain types of objects, such as tables or chairs, or determine whether a chair is already occupied.
Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new system that uses a 3-D camera, a belt with separately controllable vibrational motors distributed around it, and an electronically reconfigurable Braille interface to give visually impaired users more information about their environments.
The system could be used in conjunction with or as an alternative to a cane. In a paper they’re presenting this week at the International Conference on Robotics and Automation, the researchers describe the system and a series of usability studies they conducted with visually impaired volunteers.
“We did a couple of different tests with blind users,” says Robert Katzschmann, a graduate student in mechanical engineering at MIT and one of the paper’s two first authors. “Having something that didn’t infringe on their other senses was important. So we didn’t want to have audio; we didn’t want to have something around the head, vibrations on the neck — all of those things, we tried them out, but none of them were accepted. We found that the one area of the body that is the least used for other senses is around your abdomen.”
Katzschmann is joined on the paper by his advisor Daniela Rus, an Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science; his fellow first author Hsueh-Cheng Wang, who was a postdoc at MIT when the work was done and is now an assistant professor of electrical and computer engineering at National Chiao Tung University in Taiwan; Santani Teng, a postdoc in CSAIL; Brandon Araki, a graduate student in mechanical engineering; and Laura Giarré, a professor of electrical engineering at the University of Modena and Reggio Emilia in Italy.

Communication support in disaster zones

In the event of a natural disaster that disrupts phone and Internet systems over a wide area, autonomous aircraft could potentially hover over affected regions, carrying communications payloads that provide temporary telecommunications coverage to those in need.
However, such unpiloted aerial vehicles, or UAVs, are often expensive to operate, and can only remain in the air for a day or two, as is the case with most autonomous surveillance aircraft operated by the U.S. Air Force. Providing adequate and persistent coverage would require a relay of multiple aircraft, landing and refueling around the clock, with operational costs of thousands of dollars per hour, per vehicle.
Now a team of MIT engineers has come up with a much less expensive UAV design that can hover for longer durations to provide wide-ranging communications support. The researchers designed, built, and tested a UAV resembling a thin glider with a 24-foot wingspan. The vehicle can carry 10 to 20 pounds of communications equipment while flying at an altitude of 15,000 feet. Weighing in at just under 150 pounds, the vehicle is powered by a 5-horsepower gasoline engine and can keep itself aloft for more than five days — longer than any gasoline-powered autonomous aircraft has remained in flight, the researchers say.
The team is presenting its results this week at the American Institute of Aeronautics and Astronautics Conference in Denver, Colorado. The team was led by R. John Hansman, the T. Wilson Professor of Aeronautics and Astronautics; and Warren Hoburg, the Boeing Assistant Professor of Aeronautics and Astronautics. Hansman and Hoburg are co-instructors for MIT’s Beaver Works project, a student research collaboration between MIT and the MIT Lincoln Laboratory.
A solar no-go
Hansman and Hoburg worked with MIT students to design a long-duration UAV as part of a Beaver Works capstone project — typically a two- or three-semester course that allows MIT students to design a vehicle that meets certain mission specifications, and to build and test their design.
In the spring of 2016, the U.S. Air Force approached the Beaver Works collaboration with an idea for designing a long-duration UAV powered by solar energy. The thought at the time was that an aircraft, fueled by the sun, could potentially remain in flight indefinitely. Others, including Google, have experimented with this concept, designing solar-powered, high-altitude aircraft to deliver continuous internet access to rural and remote parts of Africa.