Testing the latest network protocol

The transmission control protocol, or TCP, which manages traffic on the internet, was first proposed in 1974. Some version of TCP still regulates data transfer in most major data centers, the huge warehouses of servers maintained by popular websites.

That’s not because TCP is perfect or because computer scientists have had trouble coming up with possible alternatives; it’s because those alternatives are too hard to test. The routers in data center networks have their traffic management protocols hardwired into them. Testing a new protocol means replacing the existing network hardware with either reconfigurable chips, which are labor-intensive to program, or software-controlled routers, which are so slow that they render large-scale testing impractical.

At the Usenix Symposium on Networked Systems Design and Implementation later this month, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory will present a system for testing new traffic management protocols that requires no alteration to network hardware but still works at realistic speeds — 20 times as fast as networks of software-controlled routers.

The system maintains a compact, efficient computational model of a

Ransomware WannaCry has limited impact

The ransomware program WannaCry, launched on May 12, targets the Microsoft Windows operating system. While this malware has infected over 200,000 computers worldwide, the attack affected around 100 computers across the 50,000 devices on the MIT network.

This limited impact is due to the many security services provided to the community by MIT Information Systems and Technology (IS&T).

“MIT values an open network to foster research, innovation and collaborative learning,” says IS&T Associate Vice President Mark Silis. “We continuously strive to balance potential security risks with the benefits of our open network environment by offering a number of security services to our community, including Sophos anti-virus, CrowdStrike anti-malware, andCrashPlan backup.

“IS&T staff are working with faculty, staff, and students to secure their devices and address any remaining issues related to WannaCry. In the weeks ahead, our department will continue to educate and advise the MIT community.”

A post on the CISCO Talos blog provides in-depth technical details about the WannaCry ransomware attack.

Preventive measures

IS&T strongly recommends that community members take this opportunity to make sure their

3-D Chip Has combined computing and data storage in Computer

As embedded intelligence is finding its way into ever more areas of our lives, fields ranging from autonomous driving to personalized medicine are generating huge amounts of data. But just as the flood of data is reaching massive proportions, the ability of computer chips to process it into useful information is stalling.

Now, researchers at Stanford University and MIT have built a new chip to overcome this hurdle. The results are published today in the journal Nature, by lead author Max Shulaker, an assistant professor of electrical engineering and computer science at MIT. Shulaker began the work as a PhD student alongside H.-S. Philip Wong and his advisor Subhasish Mitra, professors of electrical engineering and computer science at Stanford. The team also included professors Roger Howe and Krishna Saraswat, also from Stanford.

Computers today comprise different chips cobbled together. There is a chip for computing and a separate chip for data storage, and the connections between the two are limited. As applications analyze increasingly massive volumes of data, the limited rate at which data can be moved between different

The Founder dropped Dropbox to inspire and provoke collaboration

Like MIT’s campus computing environment, Athena, a pre-cloud solution for enabling files and applications to follow the user, Dropbox’s Drew Houston ’05 brings his alma mater everywhere he goes.

After earning his bachelor’s in electrical engineering and computer science, Houston’s frustration with the clunky need to carry portable USB drives drove him to partner with a fellow MIT student, Arash Ferdowsi, to develop an online solution — what would become Dropbox.

Dropbox, which now has over 500 million users, continues to adapt. The file-sharing company recently crossed the $1-billion threshold in annual subscription revenue. It’s expanding its business model by selling at the corporate level — employees at companies with Dropbox can use, essentially, one big box.

True to his company’s goal of using technology to bring people (and files) together, Houston is keen to share his own wisdom with others, especially those at MIT. Houston gave the 2013 Commencement address, saying “The hardest-working people don’t work hard because they’re disciplined. They work hard because working on an exciting problem is fun.”

He has also been a guest speaker in ‘The Founder’s Journey,” a course designed to demystify entrepreneurship, and at the MIT Enterprise

Learn to make good decisions when the results are uncertain

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

Explanation of artificial neural network

In the past 10 years, the best-performing artificial-intelligence systems — such as the speech recognizers on smartphones or Google’s latest automatic translator — have resulted from a technique called “deep learning.”

Deep learning is in fact a new name for an approach to artificial intelligence called neural networks, which have been going in and out of fashion for more than 70 years. Neural networks were first proposed in 1944 by Warren McCullough and Walter Pitts, two University of Chicago researchers who moved to MIT in 1952 as founding members of what’ssometimes called the first cognitive science department.

Neural nets were a major area of research in both neuroscience and computer science until 1969, when, according to computer science lore, they were killed off by the MIT mathematicians Marvin Minsky and Seymour Papert, who a year later would become co-directors of the new MIT Artificial Intelligence Laboratory.

The technique then enjoyed a resurgence in the 1980s, fell into eclipse again in the first decade of the new century, and has returned like gangbusters in the second, fueled largely by the increased processing power of graphics chips.

“There’s this idea that ideas in science are a

Learn computer languages while waiting for WiFi

Hyper-connectivity has changed the way we communicate, wait, and productively use our time. Even in a world of 5G wireless and “instant” messaging, there are countless moments throughout the day when we’re waiting for messages, texts, and Snapchats to refresh. But our frustrations with waiting a few extra seconds for our emails to push through doesn’t mean we have to simply stand by.

To help us make the most of these “micro-moments,” researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a series of apps called “WaitSuite” that test you on vocabulary words during idle moments, like when you’re waiting for an instant message or for your phone to connect to WiFi.

Building on micro-learning apps like Duolingo, WaitSuite aims to leverage moments when a person wouldn’t otherwise be doing anything — a practice that its developers call “wait-learning.”

“With stand-alone apps, it can be inconvenient to have to separately open them up to do a learning task,” says MIT PhD student Carrie Cai, who leads the project. “WaitSuite is embedded directly into your existing tasks, so that you can easily learn without leaving what you were already doing.”

WaitSuite covers five common

Software developers are sueorang muslim women

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

Quantum computers that can be mass-produced

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

This easy-to-use system can help users with visual impairments

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

Towards optical quantum computing

Ordinarily, light particles — photons — don’t interact. If two photons collide in a vacuum, they simply pass through each other.

An efficient way to make photons interact could open new prospects for both classical optics and quantum computing, an experimental technology that promises large speedups on some types of calculations.

In recent years, physicists have enabled photon-photon interactions using atoms of rare elements cooled to very low temperatures.

But in the latest issue of Physical Review Letters, MIT researchers describe a new technique for enabling photon-photon interactions at room temperature, using a silicon crystal with distinctive patterns etched into it. In physics jargon, the crystal introduces “nonlinearities” into the transmission of an optical signal.

“All of these approaches that had atoms or atom-like particles require low temperatures and work over a narrow frequency band,” says Dirk Englund, an associate professor of electrical engineering and computer science at MIT and senior author on the new paper. “It’s been a holy grail to come up with methods to realize single-photon-level nonlinearities at room temperature under ambient conditions.”

Joining Englund on the paper are Hyeongrak Choi, a graduate student in electrical engineering and computer science,

Systems In today’s computers can predict chemical reaction products

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

Using chip memory is more efficient and Faster

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

Digital design is very wide

Virtually any modern information-capture device — such as a camera, audio recorder, or telephone — has an analog-to-digital converter in it, a circuit that converts the fluctuating voltages of analog signals into strings of ones and zeroes.

Almost all commercial analog-to-digital converters (ADCs), however, have voltage limits. If an incoming signal exceeds that limit, the ADC either cuts it off or flatlines at the maximum voltage. This phenomenon is familiar as the pops and skips of a “clipped” audio signal or as “saturation” in digital images — when, for instance, a sky that looks blue to the naked eye shows up on-camera as a sheet of white.

Last week, at the International Conference on Sampling Theory and Applications, researchers from MIT and the Technical University of Munich presented a technique that they call unlimited sampling, which can accurately digitize signals whose voltage peaks are far beyond an ADC’s voltage limit.

The consequence could be cameras that capture all the gradations of color visible to the human eye, audio that doesn’t skip, and medical and environmental sensors that can handle both long periods of low activity and the sudden signal spikes that are often the events

Designing microstructures

Today’s 3-D printers have a resolution of 600 dots per inch, which means that they could pack a billion tiny cubes of different materials into a volume that measures just 1.67 cubic inches.

Such precise control of printed objects’ microstructure gives designers commensurate control of the objects’ physical properties — such as their density or strength, or the way they deform when subjected to stresses. But evaluating the physical effects of every possible combination of even just two materials, for an object consisting of tens of billions of cubes, would be prohibitively time consuming.

So researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new design system that catalogues the physical properties of a huge number of tiny cube clusters. These clusters can then serve as building blocks for larger printable objects. The system thus takes advantage of physical measurements at the microscopic scale, while enabling computationally efficient evaluation of macroscopic designs.

“Conventionally, people design 3-D prints manually,” says Bo Zhu, a postdoc at CSAIL and first author on the paper. “But when you want to have some higher-level goal — for example, you want to design a chair with maximum

Phytoplankton and chips on Computer

Microbes mediate the global marine cycles of elements, modulating atmospheric carbon dioxide and helping to maintain the oxygen we all breathe, yet there is much about them scientists still don’t understand. Now, an award from the Simons Foundation will give researchers from MIT’s Darwin Project access to bigger, better computing resources to model these communities and probe how they work.

The simulations of plankton populations made by Darwin Project researchers have become increasingly computationally demanding. MIT Professor Michael “Mick” Follows and Principal Research Engineer Christopher Hill, both affiliates of the Darwin Project, were therefore delighted to learn of their recent Simons Foundation award, providing them with enhanced compute infrastructure to help execute the simulations of ocean circulation, biogeochemical cycles, and microbial population dynamics that are the bread and butter of their research.

The Darwin Project, an alliance between oceanographers and microbiologists in the MIT Department of Earth, Atmospheric and Planetary Sciences (EAPS) and the Parsons Lab in the MIT Department of Civil and Environmental Engineering, was conceived as an initiative to “advance the development and application of novel models of marine microbes and microbial communities, identifying the relationships of individuals and communities to their environment, connecting cellular-scale processes to

The new AI algorithm monitors with radio waves

More than 50 million Americans suffer from sleep disorders, and diseases including Parkinson’s and Alzheimer’s can also disrupt sleep. Diagnosing and monitoring these conditions usually requires attaching electrodes and a variety of other sensors to patients, which can further disrupt their sleep.

To make it easier to diagnose and study sleep problems, researchers at MIT and Massachusetts General Hospital have devised a new way to monitor sleep stages without sensors attached to the body. Their device uses an advanced artificial intelligence algorithm to analyze the radio signals around the person and translate those measurements into sleep stages: light, deep, or rapid eye movement (REM).

“Imagine if your Wi-Fi router knows when you are dreaming, and can monitor whether you are having enough deep sleep, which is necessary for memory consolidation,” says Dina Katabi, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science, who led the study. “Our vision is developing health sensors that will disappear into the background and capture physiological signals and important health metrics, without asking the user to change her behavior in any way.”

Katabi worked on the study with Matt Bianchi, chief of the Division of Sleep Medicine

40 years of internet, the world changed forever

Towards the end of the summer of 1969 – a few weeks after the moon landings, a few days after Woodstock, and a month before the first broadcast of Monty Python’s Flying Circus – a large grey metal box was delivered to the office of Leonard Kleinrock, a professor at the University of California in Los Angeles. It was the same size and shape as a household refrigerator, and outwardly, at least, it had about as much charm. But Kleinrock was thrilled: a photograph from the time shows him standing beside it, in requisite late-60s brown tie and brown trousers, beaming like a proud father.

Had he tried to explain his excitement to anyone but his closest colleagues, they probably wouldn’t have understood. The few outsiders who knew of the box’s existence couldn’t even get its name right: it was an IMP, or “interface message processor”, but the year before, when a Boston company had won the contract to build it, its local senator, Ted Kennedy, sent a telegram praising its ecumenical spirit in creating the first “interfaith message processor”. Needless to say, though, the box that arrived outside Kleinrock’s office wasn’t a machine capable of fostering understanding

The Terminal Bloomberg Professional Services

Creation Myth by Malcolm Gladwell

Xerox PARC, Apple, and the truth about innovation.

1.

In late 1979, a twenty-four-year-old entrepreneur paid a visit to a research center in Silicon Valley called Xerox PARC. He was the co-founder of a small computer startup down the road, in Cupertino. His name was Steve Jobs.

Xerox PARC was the innovation arm of the Xerox Corporation. It was, and remains, on Coyote Hill Road, in Palo Alto, nestled in the foothills on the edge of town, in a long, low concrete building, with enormous terraces looking out over the jewels of Silicon Valley. To the northwest was Stanford University’s Hoover Tower. To the north was Hewlett-Packard’s sprawling campus. All around were scores of the other chip designers, software firms, venture capitalists, and hardware-makers. A visitor to PARC, taking in that view, could easily imagine that it was the computer world’s castle, lording over the valley below—and, at the time, this wasn’t far from the truth. In 1970, Xerox had assembled the world’s greatest computer engineers and programmers, and for the next ten years they had an unparalleled run of innovation and invention. If you were obsessed with the future in the seventies, you were