Slashdot Mirror

Despite efforts from Tesla, Daimler, Nikola and Siemens to reduce emissions from heavy-duty, diesel-powered trucks, either by producing their own electric- or hydrogen-powered alternatives, "trucking in the U.S. is still driven by diesel-fueled, compression-ignition (CI), internal combustion engines," reports Ars Technica. According to a new paper from MIT researchers, "the best way forward is not to wait for all-electric or hydrogen-powered semis, but to build a plug-in hybrid electric (PHEV) truck with an internal combustion engine/generator that can burn either gasoline or renewable ethanol or methanol." From the report: Such a setup preserves the range and affordability that's expected of diesel long-haul trucks while significantly reducing the emissions associated with diesel. To boot, it's a near-term solution; no waiting for battery weight to fall or hydrogen refueling stations to be installed. [T]here are some distinct problems with all-electric and all-diesel trucks that a hybrid flex-fuel truck could solve. First, freight companies are looking for the cheapest way to transport goods from point A to point B, so expensive electric vehicles don't make short-term economic sense, especially if you're competing with other freight companies using cheaper diesel engines.

Using flex-fuel gasoline-alcohol engines has also been shown to reduce nitrogen oxide emissions by 90 percent, the MIT researchers wrote, if the emissions reduction system on the truck uses a three-way catalyst (TWC) instead of the diesel-focused selective catalytic reduction (SCR). (The paper notes that this isn't theoretical. A 90-percent reduction in tailpipe NOx from diesel has already been achieved in light-duty gas vehicles and in the heavy-duty Cummins Westport 9 liter natural gas engine.) A flex-fuel gasoline-alcohol engine could also help freight companies achieve "both the lowest air pollution and lowest greenhouse gas emissions when the internal combustion engine operates," the paper notes. In addition, "the relative use of battery power, gasoline power, and alcohol power can be optimized for meeting varying prices and availability of these energy sources as a long-haul truck travels through various regions."

Long-time Slashdot reader Rei writes: Friday, the results of a study by the MIT Center for Transport and Logistics on autonomous system driver attentiveness were released, and the results were conclusive: "drivers do not appear to over-trust the system to a degree that results in significant functional vigilance degradation in their supervisory role of system operation".

The study, involving 323,384 miles driven (34,8% on autopilot) and 8682 "tricky situations" identified. Of the "tricky situations", 0% of incidents involved slow driver responses or missed detections; 4,5% rapid/timely responses; 90,6% anticipatory reaction (preventing the situation from occurring); and 4,9% "other". The study suggests that this is the result of two effects: 1) drivers effectively learn the limits of the system through usage; and 2) "tricky situations" are common enough so as to prevent excess trust by the driver in the system — creating the counterintuitive result that the better the systems become, the worse the driver may become.

While the study is limited by the age of the vehicles (under a quarter were even running HW2, vs HW3 which is being released now — and due to the length of the study, most of the miles were accumulated on older software versions), it offers positive conclusions — but also a precaution — about the integration of humans and driver assist systems.

In other news, Tesla has announced an April 22 Autonomy Investor Day to showcase the capability of its development versions of the software in city driving, and has started rolling out stoplight detection, no-confirmation automated lane changes and exits, and a limited rollout of advanced summon (navigates through parking lots without a driver).

Long-time Slashdot reader Rei writes: Friday, the results of a study by the MIT Center for Transport and Logistics on autonomous system driver attentiveness were released, and the results were conclusive: "drivers do not appear to over-trust the system to a degree that results in significant functional vigilance degradation in their supervisory role of system operation".

The study, involving 323,384 miles driven (34,8% on autopilot) and 8682 "tricky situations" identified. Of the "tricky situations", 0% of incidents involved slow driver responses or missed detections; 4,5% rapid/timely responses; 90,6% anticipatory reaction (preventing the situation from occurring); and 4,9% "other". The study suggests that this is the result of two effects: 1) drivers effectively learn the limits of the system through usage; and 2) "tricky situations" are common enough so as to prevent excess trust by the driver in the system — creating the counterintuitive result that the better the systems become, the worse the driver may become.

While the study is limited by the age of the vehicles (under a quarter were even running HW2, vs HW3 which is being released now — and due to the length of the study, most of the miles were accumulated on older software versions), it offers positive conclusions — but also a precaution — about the integration of humans and driver assist systems.

In other news, Tesla has announced an April 22 Autonomy Investor Day to showcase the capability of its development versions of the software in city driving, and has started rolling out stoplight detection, no-confirmation automated lane changes and exits, and a limited rollout of advanced summon (navigates through parking lots without a driver).

Long-time Slashdot reader occidental shares a link to the audio of a new interview with the authors of the 2017 article "The Jobs That Artificial Intelligence Will Create" Authors Paul Daugherty and H. James Wilson show that four soft skills are becoming much more valuable as human-machine collaboration advances. These skills include complex reasoning, creativity, social and emotional intelligence, and sensory perception.

An anonymous reader quotes a report from ExtremeTech: MIT researchers have reportedly developed an algorithm that can accelerate [neural networks] by up to 200x. The NAS (Neural Architecture Search, in this context) algorithm they developed "can directly learn specialized convolutional neural networks (CNNs) for target hardware platforms -- when run on a massive image dataset -- in only 200 GPU hours," MIT News reports. This is a massive improvement over the 48,000 hours Google reported taking to develop a state-of-the-art NAS algorithm for image classification. The goal of the researchers is to democratize AI by allowing researchers to experiment with various aspects of CNN design without needing enormous GPU arrays to do the front-end work. If finding state of the art approaches requires 48,000 GPU arrays, precious few people, even at large institutions, will ever have the opportunity to try.

Algorithms produced by the new NAS were, on average, 1.8x faster than the CNNs tested on a mobile device with similar accuracy. The new algorithm leveraged techniques like path level binarization, which stores just one path at a time to reduce memory consumption by an order of magnitude. MIT doesn't actually link out to specific research reports, but from a bit of Google sleuthing, the referenced articles appear to be here and here -- two different research reports from an overlapping group of researchers. The teams focused on pruning entire potential paths for CNNs to use, evaluating each in turn. Lower probability paths are successively pruned away, leaving the final, best-case path. The new model incorporated other improvements as well. Architectures were checked against hardware platforms for latency when evaluated. In some cases, their model predicted superior performance for platforms that had been dismissed as inefficient. For example, 7x7 filters for image classification are typically not used, because they're quite computationally expensive -- but the research team found that these actually worked well for GPUs.

An anonymous reader shares a report: Robotic hands have a tough time getting a grip on pliable objects, but it's not for lack of trying -- most make do with rigid pincers that aren't designed for precision grasping. Fortunately, if a newly published paper is any indication, more versatile systems are on the horizon. In it, researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Harvard describe a novel gripper design that's capable of lifting items in a range of weights, shapes, and sizes.

The team's hollow, cone-shaped gripper comprises three parts -- a 3D-printed, 16-piece silicone rubber skeleton with a gripper-to-mount connector encased by an airtight skin -- that together collapse in on objects as opposed to clutching them. It was inspired by the "magic ball," an origami design that's folded from a rectangular piece of paper pre-creased with a repeating, offset pattern that reversibly changes between a spherical and cylindrical shape. The gripper is powered by a pneumatic vacuum and covered by either a 27-inch latex rubber balloon or a TPU-coated nylon fabric sheet, depending on the configuration. The researchers tested three: one with a self-folded fabric skin skeleton, a second with a rubber-molded skeleton, and a third with a tougher rubber skeleton.

[...] In one experiment where the team mounted the gripper on a robot to test its strength, it managed to lift and grasp objects -- 12 food items, 19 different bottles and cups, and 14 miscellaneous items, some weighing over four pounds -- that were 70 percent of its diameter and up to 120 times its weight without damaging them. It currently works best with cylindrical objects like bottles and cans, according to Shuguang Li, a joint postdoctoral student at MIT CSAIL and Harvard's John A. Paulson School of Engineering and Applied Sciences (SEAS), which makes it a natural fit for factory production lines.

Many organizations may find they're better off hiring pen testers and in-house security researchers directly than running bug bounty programs, according to new MIT research. From a report: The New Solutions for Cybersecurity paper features a surprising analysis of bug bounty programs in the chapter, Fixing a Hole: The Labor Market for Bugs. It studied 61 HackerOne bounty programs over 23 months -- including those run for Twitter, Coinbase, Square and other big names -- and one Facebook program over 45 months. It claimed that, contrary to industry hype, organizations running these programs don't benefit from a large pool of white hats probing their products. Instead, an elite few produce the biggest volume and highest quality of bug reports across multiple products, earning the biggest slice of available rewards. It's also claimed that even these elite "top 1%" ethical hackers can't make a decent wage by Western standards.

An anonymous reader quotes a report from MIT Technology Review: As good as they are at causing mischief, researchers from the MIT-IBM Watson AI Lab realized GANs, or generative adversarial networks, are also a powerful tool: because they paint what they're "thinking," they could give humans insight into how neural networks learn and reason. [T]he researchers began probing a GAN's learning mechanics by feeding it various photos of scenery -- trees, grass, buildings, and sky. They wanted to see whether it would learn to organize the pixels into sensible groups without being explicitly told how. Stunningly, over time, it did. By turning "on" and "off" various "neurons" and asking the GAN to paint what it thought, the researchers found distinct neuron clusters that had learned to represent a tree, for example. Other clusters represented grass, while still others represented walls or doors. In other words, it had managed to group tree pixels with tree pixels and door pixels with door pixels regardless of how these objects changed color from photo to photo in the training set.

Not only that, but the GAN seemed to know what kind of door to paint depending on the type of wall pictured in an image. It would paint a Georgian-style door on a brick building with Georgian architecture, or a stone door on a Gothic building. It also refused to paint any doors on a piece of sky. Without being told, the GAN had somehow grasped certain unspoken truths about the world. Being able to identify which clusters correspond to which concepts makes it possible to control the neural network's output. The team has now released an app called GANpaint that turns this newfound ability into an artistic tool. It allows you to turn on specific neuron clusters to paint scenes of buildings in grassy fields with lots of doors. Beyond its silliness as a playful outlet, it also speaks to the greater potential of this research.

An anonymous reader writes: Three co-creators of the MIT-incubated Julia programming language are the recipients of the 2019 James H. Wilkinson Prize for Numerical Software. With origins in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Department of Mathematics, Julia is a programming language created in 2009 by Jeff Bezanson PhD '15, former MIT Julia Lab researchers Stefan Karpinski, and Viral B. Shah, and professor of mathematics Alan Edelman. The prize will be awarded to Bezanson, Karpinski, and Shah "for the creation of Julia, an innovative environment for the creation of high-performance tools that enable the analysis and solution of computational science problems."

Released publicly in 2012, Julia has over 3 million downloads and is used in over 1,500 universities for scientific and numerical computing. "I am proud of the intellectual contributions of the Julia Lab, which applies the latest in computer science to science and engineering problems, while engaging interdisciplinary collaborations all over campus and beyond," said Edelman. "Julia is increasingly the language of instruction for scientific computing at MIT."

Where are you? That's not just a metaphysical question, but increasingly a geopolitical challenge that is putting tech giants like Apple and Alphabet in a tough position. From a report: Countries around the world, including China, Japan, India and the United Kingdom plus the European Union are exploring, testing and deploying satellites to build out their own positioning capabilities. That's a massive change for the United States, which for decades has had a practical monopoly on determining the location of objects through its Global Positioning System (GPS), a military service of the Air Force built during the Cold War that has allowed commercial uses since mid-2000 (for a short history of GPS, check out this article, or for the comprehensive history, here's the book-length treatment).

Owning GPS has a number of advantages, but the first and most important is that global military and commercial users depend on this service of the U.S. government, putting location targeting ultimately at the mercy of the Pentagon. The development of the technology and the deployment of positioning satellites also provides a spillover advantage for the space industry. Today, the only global alternative to that system is Russia's GLONASS, which reached full global coverage a couple of years ago following an aggressive program by Russian president Vladimir Putin to rebuild it after it had degraded following the break-up of the Soviet Union. Now, a number of other countries want to reduce their dependency on the U.S. and get those economic benefits. Perhaps no where is that more obvious than with China, which has made building out a global alternative to GPS a top national priority. Its Beidou navigation system has been slowly building up since 2000, mostly focused on providing service in Asia.

Tim May, co-founder of the influential Cypherpunks mailing list and a significant influence on both bitcoin and WikiLeaks, passed away in mid-December at his home in Corralitos, California. The news was announced last Saturday on a Facebook post written by his friend Lucky Green. Long-time Slashdot reader SonicSpike quotes Reason: In his influential 1988 essay, "The Crypto Anarchist Manifesto," May predicted that advances in computer technology would eventually allow "individuals and groups to communicate and interact with each other" anonymously and without government intrusion. "These developments will alter completely the nature of government regulation [and] the ability to tax and control economic interactions," he wrote... Running 497 words, it was his most influential piece of writing... May became convinced that public-key cryptography combined with networked computing would break apart social power structures...

In September 1992, May and his friends Eric Hughes and Hugh Daniels came up with the idea of setting up an online mailing list to discuss their ideas. Within a few days of its launch, a hundred people had signed up for the Cypherpunks mailing list. (The group's name was coined by Hughes' girlfriend as a play on the "cyberpunk" genre of fiction.) By 1997, it averaged 30 messages daily with about 2,000 subscribers. May was its most prolific contributor. May and Hughes, along with free speech activist John Gilmore, wore masks on the cover of the second issue of Wired magazine accompanying a profile by journalist Steven Levy, who described the Cypherpunks as "more a gathering of those who share a predilection for codes, a passion for privacy, and the gumption to do something about it...."

WikiLeaks founder Julian Assange was an active reader and participant on the list, contributing his first posts in 1995 under the name "Proff."
The article notes that May "recently expressed disgust with the current state of the cryptocurrency community, citing its overpriced conferences and the advent of 'bitcoin exchanges that have draconian rules about KYC, AML, passports, freezes on accounts and laws about reporting 'suspicious activity' to the local secret police.'"

In his last published interview he told CoinDesk "I think Satoshi would barf."

Freshly Exhumed writes: A new approach to controlling magnetism in a microchip could open the doors to memory, computing, and sensing devices that consume drastically less power than existing versions. The approach could also overcome some of the inherent physical limitations that have been slowing progress in this area until now.

Researchers at MIT and at Brookhaven National Laboratory have demonstrated that they can control the magnetic properties of a thin-film material simply by applying a small voltage. Changes in magnetic orientation made in this way remain in their new state without the need for any ongoing power, unlike today's standard memory chips, the team has found. The new finding is being reported today in the journal Nature Materials, in a paper by Geoffrey Beach, a professor of materials science and engineering and co-director of the MIT Materials Research Laboratory; graduate student Aik Jun Tan; and eight others at MIT and Brookhaven.

As silicon microchips draw closer to fundamental physical limits that could cap their ability to continue increasing their capabilities while decreasing their power consumption, researchers have been exploring a variety of new technologies that might get around these limits. One of the promising alternatives is an approach called spintronics, which makes use of a property of electrons called spin, instead of their electrical charge. Because spintronic devices can retain their magnetic properties without the need for constant power, which silicon memory chips require, they need far less power to operate. They also generate far less heat -- another major limiting factor for today's devices.

If extraterrestrial intelligence exists somewhere in our galaxy, a new MIT study proposes that laser technology on Earth could, in principle, be fashioned into something of a planetary porch light -- a beacon strong enough to attract attention from as far as 20,000 light years away. From a report: The research, which author James Clark calls a "feasibility study," appears today in The Astrophysical Journal. The findings suggest that if a high-powered 1- to 2-megawatt laser were focused through a massive 30- to 45-meter telescope and aimed out into space, the combination would produce a beam of infrared radiation strong enough to stand out from the sun's energy. Such a signal could be detectable by alien astronomers performing a cursory survey of our section of the Milky Way -- especially if those astronomers live in nearby systems, such as around Proxima Centauri, the nearest star to Earth, or TRAPPIST-1, a star about 40 light-years away that hosts seven exoplanets, three of which are potentially habitable. If the signal is spotted from either of these nearby systems, the study finds, the same megawatt laser could be used to send a brief message in the form of pulses similar to Morse code.

MIT researchers have devised a way to train semantic parsers by mimicking the way a child learns language. "The system observes captioned videos and associates the words with recorded actions and objects," ZDNet reports, citing the paper presented this week. "It could make it easier to train parsers, and it could potentially improve human interactions with robots." From the report: To train their parser, the researchers combined a semantic parser with a computer vision component trained in object, human and activity recognition in video. Next, they compiled a dataset of about 400 videos depicting people carrying out actions such as picking up an object or walking toward an object. Participants on the crowdsourcing platform Mechanical Turk to wrote 1,200 captions for those videos, 840 of which were set aside for training and tuning. The rest were used for testing. By associating the words with the actions and objects in a video, the parser learns how sentences are structured. With that training, it can accurately predict the meaning of a sentence without a video.

In what is referred to as the "Moral Machine Experiment", a survey of more than two million people from nearly every country on the planet, people preferred to save humans over animals, young over old, and more people over fewer. From a report: Since 2016, scientists have posed this scenario to folks around the world through the "Moral Machine," an online platform hosted by the Massachusetts Institute of Technology that gauges how humans respond to ethical decisions made by artificial intelligence. On Wednesday, the team behind the Moral Machine released responses from more than two million people spanning 233 countries, dependencies and territories. They found a few universal decisions -- for instance, respondents preferred to save a person over an animal, and young people over older people -- but other responses differed by regional cultures and economic status.

The study's findings offer clues on how to ethically program driverless vehicles based on regional preferences, but the study also highlights underlying diversity issues in the tech industry -- namely that it leaves out voices in the developing world. The Moral Machine uses a quiz to give participants randomly generated sets of 13 questions. Each scenario has two choices: You save the car's passengers or you save the pedestrians. However, the characteristics of the passengers and pedestrians varied randomly -- including by gender, age, social status and physical fitness. What they found: The researchers identified three relatively universal preferences. On average, people wanted: to spare human lives over animals, save more lives over fewer, prioritize young people over old ones. When respondents' preferences did differ, they were highly correlated to cultural and economic differences between countries. For instance, people who were more tolerant of illegal jaywalking tended to be from countries with weaker governance, nations who had a large cultural distance from the U.S. and places that do not value individualism as highly. These distinct cultural preferences could dictate whether a jaywalking pedestrian deserves the same protection as pedestrians crossing the road legally in the event they're hit by a self-driving car. Further reading: The study; and MIT Technology Review.

MIT chemical engineers have reportedly designed a material that can react with carbon dioxide from the air, "to grow, strengthen, and even repair itself." According to MIT News, "The polymer, which might someday be used as construction or repair material or for protective coatings, continuously converts the greenhouse gas into a carbon-based material that reinforces itself." From the report: The current version of the new material is a synthetic gel-like substance that performs a chemical process similar to the way plants incorporate carbon dioxide from the air into their growing tissues. The material might, for example, be made into panels of a lightweight matrix that could be shipped to a construction site, where they would harden and solidify just from exposure to air and sunlight, thereby saving on the energy and cost of transportation. The material the team used in these initial proof-of-concept experiments did make use of one biological component -- chloroplasts, the light-harnessing components within plant cells, which the researchers obtained from spinach leaves. The chloroplasts are not alive but catalyze the reaction of carbon dioxide to glucose. Isolated chloroplasts are quite unstable, meaning that they tend to stop functioning after a few hours when removed from the plant. In their paper, [the researchers] demonstrate methods to significantly increase the catalytic lifetime of extracted chloroplasts. In ongoing and future work, the chloroplast is being replaced by catalysts that are nonbiological in origin.

The material the researchers used, a gel matrix composed of a polymer made from aminopropyl methacrylamide (APMA) and glucose, an enzyme called glucose oxidase, and the chloroplasts, becomes stronger as it incorporates the carbon. It is not yet strong enough to be used as a building material, though it might function as a crack filling or coating material, the researchers say. The team has worked out methods to produce materials of this type by the ton, and is now focusing on optimizing the material's properties. Commercial applications such as self-healing coatings and crack filling are realizable in the near term, they say, whereas additional advances in backbone chemistry and materials science are needed before construction materials and composites can be developed.

"Computers can solve your problem. You may not like the answer," writes the Boston Globe. Slashdot reader sandbagger explains: "Boston Public Schools asked MIT graduate students Sebastien Martin and Arthur Delarue to build an algorithm that could do the enormously complicated work of changing start times at dozens of schools -- and re-routing the hundreds of buses that serve them. In theory this would also help with student alertness...." MIT also reported that "Approximately 50 superfluous routes could be eliminated using the new method, saving the school district between $3 million and $5 million annually."

The Globe reports: They took to the new project with gusto, working 14- and 15-hour days to meet a tight deadline -- and occasionally waking up in the middle of the night to feed new information to a sprawling MIT data center. The machine they constructed was a marvel. Sorting through 1 novemtrigintillion options -- that's 1 followed by 120 zeroes -- the algorithm landed on a plan that would trim the district's $100 million-plus transportation budget while shifting the overwhelming majority of high school students into later start times.... But no one anticipated the crush of opposition that followed. Angry parents signed an online petition and filled the school committee chamber, turning the plan into one of the biggest crises of Mayor Marty Walsh's tenure. The city summarily dropped it. The failure would eventually play a role in the superintendent's resignation...

Big districts stagger their start times so a single fleet of buses can serve every school: dropping off high school students early in the morning, then circling back to get the elementary and middle school kids. If you're going to push high school start times back, then you've probably got to move a lot of elementary and middle schools into earlier time slots. The district knew that going in, and officials dutifully quizzed thousands of parents and teachers at every grade level about their preferred start times. But they never directly confronted constituents with the sort of dramatic change the algorithm would eventually propose -- shifting school start times at some elementary schools by as much as two hours. Even more... Hundreds of families were facing a 9:30 to 7:15 a.m. shift. And for many, that was intolerable. They'd have to make major changes to work schedules or even quit their jobs...
Nearly 85% of the district had ended up with a new start time, and "In the end, the school start time quandary was more political than technical... This was a fundamentally human conflict, and all the computing power in the world couldn't solve it."

But will the whole drama play out again? "Last year, even after everything went sideways in Boston, some 80 school districts from around the country reached out to the whiz kids from MIT, eager for the algorithm to solve their problems."

Amateur and professional musicians alike may spend hours poring over YouTube clips to figure out exactly how to play certain parts of their favorite songs. But what if there were a way to play a video and isolate the only instrument you wanted to hear? MIT News: That's the outcome of a new AI project out of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL): a deep-learning system that can look at a video of a musical performance, and isolate the sounds of specific instruments and make them louder or softer. The system, which is "self-supervised," doesn't require any human annotations on what the instruments are or what they sound like. Trained on over 60 hours of videos, the "PixelPlayer" system can view a never-before-seen musical performance, identify specific instruments at pixel level, and extract the sounds that are associated with those instruments. For example, it can take a video of a tuba and a trumpet playing the "Super Mario Brothers" theme song, and separate out the soundwaves associated with each instrument. The researchers say that the ability to change the volume of individual instruments means that in the future, systems like this could potentially help engineers improve the audio quality of old concert footage. You could even imagine producers taking specific instrument parts and previewing what they would sound like with other instruments (i.e. an electric guitar swapped in for an acoustic one).

Researchers at the Massachusetts Institute of Technology have developed a new piece of software that uses wifi signals to monitor the movements, breathing, and heartbeats of humans on the other side of walls. While the researchers say this new tech could be used in areas like remote healthcare, it could in theory be used in more dystopian applications. Inverse reports: "We actually are tracking 14 different joints on the body [...] the head, the neck, the shoulders, the elbows, the wrists, the hips, the knees, and the feet," Dina Katabi, an electrical engineering and computer science teacher at MIT, said. "So you can get the full stick-figure that is dynamically moving with the individuals that are obstructed from you -- and that's something new that was not possible before." The technology works a little bit like radar, but to teach their neural network how to interpret these granular bits of human activity, the team at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) had to create two separate A.I.s: a student and a teacher.

[T]he team developed one A.I. program that monitored human movements with a camera, on one side of a wall, and fed that information to their wifi X-ray A.I., called RF-Pose, as it struggled to make sense of the radio waves passing through that wall on the other side. The research builds off of a longstanding project at CSAIL lead by Katabi, which hopes to use this wifi tracking to help passively monitor the elderly and automate any emergency alerts to EMTs and medical professionals if they were to fall or suffer some other injury. For more information, a press release and video about the software are available.

An anonymous reader quotes a report from Motherboard: A student at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) is developing new technology, called MapLite, that eliminates the need for maps in self-driving car technology altogether. This could more easily enable a fleet-sharing model that connects carless rural residents and would facilitate intercity trips that run through rural areas. In a paper posted online on May 7 by CSAIL and project partner Toyota, 30-year-old PhD candidate Teddy Ort -- along with co-authors Liam Paull and Daniela Rus -- detail how using LIDAR (a radar-like sensor that uses lasers instead of radio waves to measure distances) and GPS together can enable self-driving cars to navigate on rural roads without having a detailed map to guide them. The team was able to drive down a number of unpaved roads in rural Massachusetts and reliably scan the road for curves and obstacles up to 100 feet ahead, according to the paper.

An anonymous reader quotes a report from MIT News: MIT neuroscientists have developed a new magnetic resonance imaging (MRI) sensor that allows them to monitor neural activity deep within the brain by tracking calcium ions. Because calcium ions are directly linked to neuronal firing -- unlike the changes in blood flow detected by other types of MRI, which provide an indirect signal -- this new type of sensing could allow researchers to link specific brain functions to their pattern of neuron activity, and to determine how distant brain regions communicate with each other during particular tasks. In tests in rats, the researchers showed that their calcium sensor can accurately detect changes in neural activity induced by chemical or electrical stimulation, deep within a part of the brain called the striatum.

The new sensor consists of two types of particles that cluster together in the presence of calcium. One is a naturally occurring calcium-binding protein called synaptotagmin, and the other is a magnetic iron oxide nanoparticle coated in a lipid that can also bind to synaptotagmin, but only when calcium is present. Calcium binding induces these particles to clump together, making them appear darker in an MRI image. High levels of calcium outside the neurons correlate with low neuron activity; when calcium concentrations drop, it means neurons in that area are firing electrical impulses. The current version of the sensor responds within a few seconds of the initial brain stimulation, but the researchers are working on speeding that up. They are also trying to modify the sensor so that it can spread throughout a larger region of the brain and pass through the blood-brain barrier, which would make it possible to deliver the particles without injecting them directly to the test site.

NCSA Mosaic 1.0, the first web browser to achieve popularity among the general public, was released on April 22, 1993. It was developed by a team of students at the University of Illinois' National Center for Supercomputing Applications (NCSA), and had the ability to display text and images inline, meaning you could put pictures and text on the same page together, in the same window. Wired reports: It was a radical step forward for the web, which was at that point, a rather dull experience. It took the boring "document" layout of your standard web page and transformed it into something much more visually exciting, like a magazine. And, wow, it was easy. If you wanted to go somewhere, you just clicked. Links were blue and underlined, easy to pick out. You could follow your own virtual trail of breadcrumbs backwards by clicking the big button up there in the corner. At the time of its release, NCSA Mosaic was free software, but it was available only on Unix. That made it common at universities and institutions, but not on Windows desktops in people's homes.

The NCSA team put out Windows and Mac versions in late 1993. They were also released under a noncommercial software license, meaning people at home could download it for free. The installer was very simple, making it easy for just about anyone to get up and running on the web. It was then that the excitement really began to spread. Mosaic made the web come to life with color and images, something that, for many people, finally provided the online experience they were missing. It made the web a pleasure to use.

New submitter Paige.Bennett writes: Up till now, graphene has been produced in small batches in labs. But MIT just found a way to mass-produce graphene in large sheets using a process that rolls out five centimeters of graphene each minute. The longest span so far was nearly four hours, which produced about 10 meters of graphene. According to MIT, here's how their conveyor belt system works: "The first spool unfurls a long strip of copper foil, less than one centimeter wide. When it enters the furnace, the foil is fed through first one tube and then another, in a 'split-zone' design. While the foil rolls through the first tube, it heats up to a certain ideal temperature, at which point it is ready to roll through the second tube, where the scientists pump in a specified ratio of methane and hydrogen gas, which are deposited onto the heated foil to produce graphene." The work has been published in the journal Materials and Interfaces.

As part of an effort to identify distant planets hospitable to life, NASA has established a crowdsourcing project in which volunteers search telescopic images for evidence of debris disks around stars, which are good indicators of exoplanets. From a report: Using the results of that project, researchers at MIT have now trained a machine-learning system to search for debris disks itself. The scale of the search demands automation: There are nearly 750 million possible light sources in the data accumulated through NASA's Wide-Field Infrared Survey Explorer (WISE) mission alone. In tests, the machine-learning system agreed with human identifications of debris disks 97 percent of the time. The researchers also trained their system to rate debris disks according to their likelihood of containing detectable exoplanets. In a paper describing the new work in the journal Astronomy and Computing, the MIT researchers report that their system identified 367 previously unexamined celestial objects as particularly promising candidates for further study.

An anonymous reader quotes a report from MIT Technology Review: The MIT Media Lab will sever ties with a brain-embalming company that promoted euthanasia to people hoping for digital immortality through "brain uploads." The startup, called Nectome, had raised more than $200,000 in deposits from people hoping to have their brains stored in an end-of-life procedure similar to physician-assisted suicide. MIT's connection to the company came into question after MIT Technology Review detailed Nectome's promotion of its "100 percent fatal" technology. Under a subcontract, MIT was receiving approximately $300,000 from a federal grant won by Nectome to develop methods of brain preservation and analysis. According to an April 2 statement, MIT will terminate the research contract with Media Lab professor and neuroscientist Edward Boyden. Boyden said he didn't have a financial stake or other personal involvement with Nectome. MIT's connection to the company drew sharp criticism from some neuroscientists, who say brain uploading isn't possible.

dryriver writes: Before I ask my question, there already is free and open-source software (FOSS) for wind turbine design and simulation called QBlade. It lets you calculate turbine blade performance using nothing more than a computer and appears compatible with Xfoil as well. But consider this: the ultimate, most efficient and most real-world usable and widely deployable wind turbine rotor may not have traditional "blades" or "foils" at all, but may be a non-propeller-like, complex and possibly rather strange looking three-dimensional rotor of the sort that only a 3D printer could prototype easily. It may be on a vertical or horizontal axis. It may have air flowing through canals in its non-traditional structure, rather than just around it. Nobody really knows what this "ultimate wind turbine rotor" may look like.

The easiest way to find such a rotor might be through machine-learning. You get an algorithm to create complex non-traditional 3D rotor shapes, simulate their behavior in wind, and then mutate the design, simulate again, and get a machine learning algorithm to learn what sort of mutations lead to a better performing 3D rotor. In theory, enough iterations -- perhaps millions or more -- should eventually lead to the "ultimate rotor" or something closer to it than what is used in wind turbines today. Is this something FOSS developers could tackle, or is this task too complex for non-commercial software? The real world impact of such a FOSS project could be that far better wind turbines can be designed, manufactured and deployed than currently exist, and the fight against climate change becomes more effective; the better your wind turbines perform, and the more usable they are, the more of a fighting chance humanity has to do something against climate change. Could FOSS achieve this?

Mallory Locklear reports via Engadget: MIT announced yesterday that it and Commonwealth Fusion Systems -- an MIT spinoff -- are working on a project that aims to make harvesting energy from nuclear fusion a reality within the next 15 years. The ultimate goal is to develop a 200-megawatt power plant. MIT also announced that Italian energy firm ENI has invested $50 million towards the project, $30 million of which will be applied to research and development at MIT over the next three years. MIT and CFS plan to use newly available superconducting materials to develop large electromagnets that can produce fields four-times stronger than any being used now. The stronger magnetic fields will allow for more power to be generated resulting in, importantly, positive net energy. The method will hopefully allow for cheaper and smaller reactors. The research team aims to develop a prototype reactor within the next 10 years, followed by a 200-megawatt pilot power plant.

From a blog post on MIT News Office: Veil would provide added protections to people using shared computers in offices, hotel business centers, or university computing centers, and it can be used in conjunction with existing private-browsing systems and with anonymity networks such as Tor, which was designed to protect the identity of web users living under repressive regimes. "Veil was motivated by all this research that was done previously in the security community that said, 'Private-browsing modes are leaky -- Here are 10 different ways that they leak,'" says Frank Wang, an MIT graduate student in electrical engineering and computer science and first author on the paper. "We asked, 'What is the fundamental problem?' And the fundamental problem is that [the browser] collects this information, and then the browser does its best effort to fix it. But at the end of the day, no matter what the browser's best effort is, it still collects it. We might as well not collect that information in the first place."

MIT researchers have developed a special-purpose chip that increases the speed of neural-network computations by three to seven times over its predecessors, while reducing power consumption 94 to 95 percent. From a report: That could make it practical to run neural networks locally on smartphones or even to embed them in household appliances. "The general processor model is that there is a memory in some part of the chip, and there is a processor in another part of the chip, and you move the data back and forth between them when you do these computations," says Avishek Biswas, an MIT graduate student in electrical engineering and computer science, who led the new chip's development. "Since these machine-learning algorithms need so many computations, this transferring back and forth of data is the dominant portion of the energy consumption. But the computation these algorithms do can be simplified to one specific operation, called the dot product. Our approach was, can we implement this dot-product functionality inside the memory so that you don't need to transfer this data back and forth?"

Researchers in the emerging field of "neuromorphic computing" have attempted to design computer chips that work like the human brain. From a report: Instead of carrying out computations based on binary, on/off signaling, like digital chips do today, the elements of a "brain on a chip" would work in an analog fashion, exchanging a gradient of signals, or "weights," much like neurons that activate in various ways depending on the type and number of ions that flow across a synapse. In this way, small neuromorphic chips could, like the brain, efficiently process millions of streams of parallel computations that are currently only possible with large banks of supercomputers. But one significant hangup on the way to such portable artificial intelligence has been the neural synapse, which has been particularly tricky to reproduce in hardware.

Now engineers at MIT have designed an artificial synapse in such a way that they can precisely control the strength of an electric current flowing across it, similar to the way ions flow between neurons. The team has built a small chip with artificial synapses, made from silicon germanium. In simulations, the researchers found that the chip and its synapses could be used to recognize samples of handwriting, with 95 percent accuracy. The design, published today in the journal Nature Materials, is a major step toward building portable, low-power neuromorphic chips for use in pattern recognition and other learning tasks.

Camel Pilot writes: The new GOP tax plan -- which just passed the House -- will tax tuition waivers as income. Graduate students working as research assistants on meager stipends would have to declare tuition waivers as income on the order of $80,000 income. This will force many graduate students of modest means to quit their career paths and walk away from their research. These are the next generation of scientists, engineers, inventors, educators, medical miracle workers and market makers. As Prof Claus Wilke points out: "This would be a disaster for U.S. STEM Ph.D. education." Slashdot reader Camel Pilot references a report via The New York Times, where Erin Rousseau explains how the House of Representatives' recently passed tax bill affects graduate research in the United States. Rousseau is a graduate student at M.I.T. who studies the neurological basis of mental health disorders. "My peers and I work between 40 and 80 hours a week as classroom teachers and laboratory researchers, and in return, our universities provide us with a tuition waiver for school. For M.I.T. students, this waiver keeps us from having to pay a tuition bill of about $50,000 every year -- a staggering amount, but one that is similar to the fees at many other colleges and universities," he writes. "No money from the tuition waivers actually ends up in our pockets, so under Section 117(d)(5), it isn't counted as taxable income." Rousseau continues by saying his tuition waivers will be taxed under the House's tax bill. "This means that M.I.T. graduate students would be responsible for paying taxes on an $80,000 annual salary, when we actually earn $33,000 a year. That's an increase of our tax burden by at least $10,000 annually."

Camel Pilot writes: The new GOP tax plan -- which just passed the House -- will tax tuition waivers as income. Graduate students working as research assistants on meager stipends would have to declare tuition waivers as income on the order of $80,000 income. This will force many graduate students of modest means to quit their career paths and walk away from their research. These are the next generation of scientists, engineers, inventors, educators, medical miracle workers and market makers. As Prof Claus Wilke points out: "This would be a disaster for U.S. STEM Ph.D. education." Slashdot reader Camel Pilot references a report via The New York Times, where Erin Rousseau explains how the House of Representatives' recently passed tax bill affects graduate research in the United States. Rousseau is a graduate student at M.I.T. who studies the neurological basis of mental health disorders. "My peers and I work between 40 and 80 hours a week as classroom teachers and laboratory researchers, and in return, our universities provide us with a tuition waiver for school. For M.I.T. students, this waiver keeps us from having to pay a tuition bill of about $50,000 every year -- a staggering amount, but one that is similar to the fees at many other colleges and universities," he writes. "No money from the tuition waivers actually ends up in our pockets, so under Section 117(d)(5), it isn't counted as taxable income." Rousseau continues by saying his tuition waivers will be taxed under the House's tax bill. "This means that M.I.T. graduate students would be responsible for paying taxes on an $80,000 annual salary, when we actually earn $33,000 a year. That's an increase of our tax burden by at least $10,000 annually."

theodp writes: Well, this year's Hour of Code is almost upon us, and if Google has its way, K-12 schoolchildren across the nation will be learning computer science by creating Google Doodles with Scratch (lesson plan). Curiously, the introductory video for the Create Your Own Google Logo Hour of Code activity from the Google Computer Science Education Department sternly warns kids, "While it is okay to use the Google logo for your personal Doodle, it is not okay [emphasis Google's] to use it anyplace else or outside this activity." In addition to respecting its intellectual property, Google instructs kids that they are to follow the Scratch Community Guidelines when they create Google logos: "Please stay positive, friendly, and supportive towards others in the Scratch Community. Help us keep Scratch a place where people of different backgrounds and interests feel welcome to hang out and create together."

One could argue that the web is already decentralized. But with major websites like Google and Facebook, it's increasingly harder to stay decentralized. Paul Ford writes: There's a good research report that was just published. It's called "Defending Internet Freedom through Decentralization: Back to the Future?" (That's a PDF so watch yourself.) What is decentralization? Take the web: Anyone can set up a web page and link to any other web page. That's decentralized. Anyone can make a search engine to find those web pages. That's centralized. The search engine can add blogging. That's Google + Blogger. Now it's both a publisher and a search engine. It has more power. Decentralized things are harder to manage and use. Centralized things end up easy to use and make money for relatively few people. The web is inherently decentralized, which has made it much easier for large companies to create large, centralized platforms. It's a paradox and very thorny. God bless the authors of this paper, they don't make you wade through. They pop up with recommendations by page 5: "We advise investors -- whether motivated by civic or fiscal concerns -- both to watch this space closely and to advocate for the pre-conditions that we believe will enable a healthier marketplace for online publishing. A precondition for the success of these distributed platforms is a shift towards user-controlled data, the ownership of a user's social graph and her intellectual property created online. It will be difficult for new platforms to develop without widespread support for efforts towards data portability and rights over data ownership. Data portability also enables new models for aggregation. Small, thoughtfully curated news sources will be made more powerful by having access to the user data currently locked inside mega-platforms, but right now, federated clients that interoperate between different platforms are borderline illegal -- fixing this may require adjusting overly broad regulations, like the Digital Millennium Copyright Act."
"We believe that these user-controlled data rights are essential to develop a more robust market and allow new efforts to emerge from existing communities. Though individual users might not directly care about or understand these rights, their adoption will free developers to create applications that leverage users' existing data, so that they can provide compelling, interesting new experiences, even with a small user base."

A better treatment for Alzheimer's patients may be on the horizon thanks to new research from MIT. Researchers at MIT's Picower Institute for Learning and Memory have discovered that they can reverse memory loss in mice by blocking an enzyme called HDAC2. From the study: For several years, scientists and pharmaceutical companies have been trying to develop drugs that block this enzyme, but most of these drugs also block other members of the HDAC family, which can lead to toxic side effects. The MIT team has now found a way to precisely target HDAC2, by blocking its interaction with a binding partner called Sp3. "This is exciting because for the first time we have found a specific mechanism by which HDAC2 regulates synaptic gene expression," says Li-Huei Tsai, director of MIT's Picower Institute for Learning and Memory and the study's senior author. Blocking that mechanism could offer a new way to treat memory loss in Alzheimer's patients. In this study, the researchers used a large protein fragment to interfere with HDAC-2, but they plan to seek smaller molecules that would be easier to deploy as drugs. Picower Institute postdocs Hidekuni Yamakawa, Jemmie Cheng, and Jay Penney are the lead authors of the study, which appears in the Aug. 8 edition of Cell Reports.

MIT officials said U.S. President Donald Trump badly misunderstood their research when he cited it on Thursday to justify withdrawing the United States from the Paris Climate Agreement. From a report: Trump announced during a speech at the White House Rose Garden that he had decided to pull out of the landmark climate deal, in part because it would not reduce global temperatures fast enough to have a significant impact. "Even if the Paris Agreement were implemented in full, with total compliance from all nations, it is estimated it would only produce a two-tenths of one degree Celsius reduction in global temperature by the year 2100," Trump said. "Tiny, tiny amount." That claim was attributed to research conducted by MIT, according to White House documents seen by Reuters. The Cambridge, Massaschusetts-based research university published a study in April 2016 titled "How much of a difference will the Paris Agreement make?" showing that if countries abided by their pledges in the deal, global warming would slow by between 0.6 degree and 1.1 degrees Celsius by 2100. "We certainly do not support the withdrawal of the U.S. from the Paris agreement," said Erwan Monier, a lead researcher at the MIT Joint Program on the Science and Policy of Global Change, and one of the study's authors. "If we don't do anything, we might shoot over 5 degrees or more and that would be catastrophic," said John Reilly, the co-director of the program, adding that MIT's scientists had had no contact with the White House and were not offered a chance to explain their work.

Kristine Lofgren writes: Home building hasn't changed much over the years, but leave it to MIT to take things to the next level. A new technology built at MIT can construct a simple dome structure in 14 hours and it's powered by solar panels, so you can take it to remote areas. MIT's 3D-printing robot can construct the entire basic structure of a building and can be customized to fit the local terrain in ways that traditional methods can't do. It even has a built-in scoop so it can prepare the building site and gather its own construction materials. You can watch a video of the 3D-printing robot in action here.

Sunday was the 28th anniversary of the day that 33-year-old Tim Berners-Lee submitted his proposal for the World Wide Web -- and the father of the web published a new letter today about "how the web has evolved, and what we must do to ensure it fulfills his vision of an equalizing platform that benefits all of humanity."

It's been an ongoing battle to maintain the web's openness, but in addition, Berners-Lee lists the following issues: 1) We've lost control of our personal data. 2) It's too easy for misinformation to spread on the web. 3) Political advertising online needs transparency and understanding. Tim Berners-Lee writes:
We must work together with web companies to strike a balance that puts a fair level of data control back in the hands of people, including the development of new technology like personal "data pods" if needed and exploring alternative revenue models like subscriptions and micropayments. We must fight against government over-reach in surveillance laws, including through the courts if necessary. We must push back against misinformation by encouraging gatekeepers such as Google and Facebook to continue their efforts to combat the problem, while avoiding the creation of any central bodies to decide what is "true" or not. We need more algorithmic transparency to understand how important decisions that affect our lives are being made, and perhaps a set of common principles to be followed. We urgently need to close the "internet blind spot" in the regulation of political campaigning.
Berners-Lee says his team at the Web Foundation "will be working on many of these issues as part of our new five year strategy," researching policy solutions and building progress-driving coalitions, as well as maintaining their massive list of digital rights organizations. "I may have invented the web, but all of you have helped to create what it is today... and now it is up to all of us to build the web we want -- for everyone." Inspired by the letter, very-long-time Slashdot reader Martin S. asks, does the web need improvements? And if so, "I'm wondering what Slashdotters would consider to be a solution?"

A team of MIT researchers have created the world's strongest and lightest material known to man using graphene. Futurism reports: Graphene, which was heretofore, the strongest material known to man, is made from an extremely thin sheet of carbon atoms arranged in two dimensions. But there's one drawback: while notable for its thinness and unique electrical properties, it's very difficult to create useful, three-dimensional materials out of graphene. Now, a team of MIT researchers discovered that taking small flakes of graphene and fusing them following a mesh-like structure not only retains the material's strength, but the graphene also remains porous. Based on experiments conducted on 3D printed models, researchers have determined that this new material, with its distinct geometry, is actually stronger than graphene -- making it 10 times stronger than steel, with only five percent of its density. The discovery of a material that is extremely strong but exceptionally lightweight will have numerous applications. As MIT reports: "The new findings show that the crucial aspect of the new 3-D forms has more to do with their unusual geometrical configuration than with the material itself, which suggests that similar strong, lightweight materials could be made from a variety of materials by creating similar geometric features."

An anonymous reader quotes a report from CNNMoney: Researchers at the MIT Computer Science and Artificial Intelligence Laboratory have developed a device that uses radio waves to detect whether someone is happy, sad, angry or excited. The breakthrough makes it easier to accomplish what scientists have tried to do for years with machines: sense human emotions. The researchers believe tracking a person's feelings is a step toward improving their overall emotional well-being. The technology isn't invasive; it works in the background without a person having to do anything, like wearing a device. The device called EQ-Radio, which was detailed in a paper published online Tuesday, resembles a shoebox, as of now. It works by bouncing wireless signals off a person. These signals are impacted by motion, such as breathing and heartbeats. When the heart pumps blood, a force is exerted onto our bodies, and the skin vibrates ever so slightly. After the radio waves are impacted by these vibrations, they return to the device. A computer then analyzes the signals to identify changes in heartbeat and breathing. The researchers demonstrated their system detects emotions on par with an electrocardiogram (EKG), a common wearable device medical professionals use to monitor the human heart. The machine's analysis of the radio waves relies on artificial intelligence, which learns how various heartbeats indicate certain emotions. As a part of the testing, the machine bounced radio waves off actors who recreated a range of emotions. The more emotions the machine experienced, the better it identified what signals, such as a fast heartbeat, gave away their true feelings. By monitoring radio waves reflected off people who are happy, the machine is exposed to certain signs -- such as heart rate or a type of breathing -- associated with being in good spirits.

An anonymous reader quotes a report from Gizmodo: In a breakthrough that will appeal to both spies and those who work with priceless but frail historical documents, researchers at MIT have developed a camera that uses terahertz radiation to peer at the text on pages of a book, without it having to be open. Terahertz radiation falls somewhere between the microwave and infrared spectrums, and the research team, including Barmak Heshmat, Ramesh Raskar, and Albert Redo Sanchez from MIT, and Justin Romberg and Alireza Aghasi from Georgia Tech, chose that particular flavor of radiation because of how it reacts with different chemicals. Different chemicals produce a distinct frequency as they react with different terahertz frequencies, which can be measured and distinguished. In this instance, it allows the researchers to tell the different between ink and blank paper. Complex algorithms and software is required to translate the frequencies being bounced back to the camera, allowing it to distinguish letters on a page. But it also relies on how far the short bursts of terahertz radiation are traveling, by precisely timing how long it takes to reach the 20-micrometer-thick air gaps between pages of a book, it's able to calculate when it moves from page to page. The report adds, "the researchers feel their system could be a fantastic tool for museums or other facilities who want to explore and catalog historical documents, without actually having to touch or open them, and risk damage."

An anonymous reader quotes a report from MSN: Scientists at MIT claim to have created a new wireless technology that can triple Wi-Fi data speeds while also doubling the range of the signal. Dubbed MegaMIMO 2.0, the system will shortly enter commercialization and could ease the strain on our increasingly crowded wireless networks. Multiple-input-multiple-output technology, or MIMO, helps networked devices perform better by combining multiple transmitters and receivers that work simultaneously, allowing then to send and receive more than one data signal at the same time. MIT's MegaMIMO 2.0 works by allowing several routers to work in harmony, transmitting data over the same piece of spectrum. MIT claimed that during tests, MegaMIMO 2.0 was able to increase data transfer speed of four laptops connected to the same Wi-Fi network by 330 percent. Paper co-author Rahul said the technology could also be applied to mobile phone networks to solve similar congestion issues. "In today's wireless world, you can't solve spectrum crunch by throwing more transmitters at the problem, because they will all still be interfering with one another," Ezzeldin Hamed, lead author on a paper on the topic, told MIT News. "The answer is to have all those access points work with each other simultaneously to efficiently use the available spectrum."

New submitter gwolf writes: The great educator, creator of the Logo programming language, and the enabler for computer education in the 1980s has passed away. Listing his contributions is impossible in an article summary, but the ACM has published a short in-memoriam note for him. Papert is, without exaggeration, one of the people I owe my career and life choices to.

An anonymous reader writes from a report via TechCrunch: MIT has developed a glasses-less 3D display for movie theaters. The Nintendo 3DS is one of a handful of devices to feature glasses-less 3D, but it is designed for a single users where the user is looking at the display head-on at a relatively specific angle. It's not something made for a movie theater with hundreds of seats, each of which would have a different viewing angle. What's neat about MIT's 3D display is that it doesn't require glasses and it lets anyone see the 3D effect in a movie theater, no matter where they are sitting. The MIT Computers Science and Artificial Intelligence Lab (CSAIL) created the prototype display called 'Cinema 3D' that uses a complex arrangement of lenses and mirrors to create a set number of parallax barriers that can address every viewing angle in the theater based on seat locations. It works in a movie theater because the seats are in fixed locations, and people don't tend to move around, change seats or alter their viewing angle too much. What's also neat about the Cinema 3D is that is preserves resolution, whereas other glasses-less 3D displays carry cots in terms of image resolution. The prototype is about the size of a letter-sized notepad, and it needs 50 sets of mirrors and lenses. It should be ready for market once researchers scale it up to a commercially viable product.

Smartphones become indispensable tools for journalists, human right workers, and activists in war-torn regions. But at the same time, as Intercept points out, they become especially potent tracking devices that can put users in mortal danger by leaking their location. To address the problem, NSA whistleblower Edward Snowden and hardware hacker Andrew "Bunnie" Huang have been developing a way for potentially imperiled smartphone users to monitor whether their devices are making any potentially compromising radio transmissions. "We have to ensure that journalists can investigate and find the truth, even in areas where governments prefer they don't," Snowden told Intercept. "It's basically to make the phone work for you, how you want it, when you want it, but only when." Snowden and Huang presented their findings in a talk at MIT Media Lab's Forbidden Research event Thursday, and published a detailed paper. From the Intercept article: Snowden and Huang have been researching if it's possible to use a smartphone in such an offline manner without leaking its location, starting with the assumption that "a phone can and will be compromised." [...] The research is necessary in part because most common way to try and silence a phone's radio -- turning on airplane mode -- can't be relied on to squelch your phone's radio traffic. Fortunately, a smartphone can be made to lie about the state of its radios. The article adds: According to their post, the goal is to "provide field-ready tools that enable a reporter to observe and investigate the status of the phone's radios directly and independently of the phone's native hardware." In other words, they want to build an entirely separate tiny computer that users can attach to a smartphone to alert them if it's being dishonest about its radio emissions. Snowden and Haung are calling this device an "introspection engine" because it will inspect the inner-workings of the phone. The device will be contained inside a battery case, looking similar to a smartphone with an extra bulky battery, except with its own screen to update the user on the status of the radios. Plans are for the device to also be able to sound an audible alarm and possibly to also come equipped with a "kill switch" that can shut off power to the phone if any radio signals are detected.Wired has a detailed report on this, too.

An anonymous reader writes: MIT's Media Lab has produced Ori, a range of robotic, modular furniture designed to make small places feel more roomy. The Architect's Newspaper reports: "With its name coming from the Japanese word 'origami,' the furniture system combines robotics, architecture, and design to let interiors double-up as bedrooms, living rooms, dining rooms, and offices. Teaming up with Swiss product designer Yves Behar, founder and CEO of Ori and research scientist at MIT Hasier Larrea has his eyes set on fundamentally altering the 'experience and economics of the urban built environment.' Speaking in a press release, Larrea added that 'Ori's systems make possible the effortless and magical transformation of interior spaces, providing the totally new experience of having our interior space intelligently conform to our activities, rather than our activities being forced to conform to our interior space.' A movable mainframe, containing a variety of concealable furniture and storage, is the core concept in Ori's modular and mechatronic furniture. Using the wall mounted control panel, the module can move across the floor and deploy different pieces of furniture. This can all be done remotely through the Ori app as well." Ori is not on the market yet, but inquiries can be made via Ori's website.

An anonymous reader writes from a report via PC Magazine: Following the recent vulnerabilities in Tor, researchers at MIT's Computer Science and Artificial Intelligence Laboratory and the Ecole Polytechnique Federale de Lausanne have been working on a new anonymity network that they say is more secure than Tor. While the researchers are planning to present their new system, dubbed Riffle, at the Privacy Enhancing Technologies Symposium later this month, they did say the system uses existing cryptographic techniques, but in new ways. A series of servers are what make up Riffle, each of which "permutes the order in which it receives messages before passing them on to the next," according to a news release. "For instance, messages from senders Alice, Bob, and Carol reach the first server in the order A, B, C, that server would send them to the second server in a different order -- say C, B, A. The second server would permute them before sending them to the third, and so on." Nobody would know which was which by the time they exited the last server. Both Tor and MIT's anonymity network use onion encryption. Riffle uses a technique called verifiable shuffle in addition to onion encryption to thwart tampering and prevent adversaries from infiltrating servers with their own code. Last but not least, it uses authentication encryption to verify the authenticity of an encrypted message. The researchers say their system provides strong security while using bandwidth much more efficiently than similar solutions.

An anonymous reader writes from a report via Gizmag: MIT's new Swarm chip could help unleash the power of parallel processing for up to 75-fold speedups, while requiring programmers to write a fraction of the code that is usually necessary for programs to take full advantage of their hardware. Swarm is a 64-core chip developed by Prof. Daniel Sanchez and his team that includes specialized circuitry for both executing and prioritizing tasks in a simple and efficient manner. Neowin reports: "For example, when using multiple cores to process a task, one core might need to access a piece of data that's being used by another core. Developers usually need to write code to avoid these types of conflict, and direct how each part of the task should be processed and split up between the processor's cores. This almost never gets done with normal consumer software, hence the reason why Crysis isn't running better on your new 10-core Intel. Meanwhile, when such optimization does get done, mainly for industrial, scientific and research computers, it takes a lot of effort on the developer's side and efficiency gains may sometimes still be minimal." Swarm is able to take care of all of this, mostly through its hardware architecture and customizable profiles that can be written by developers in a fraction of the time needed for regular multi-core silicon. The 64-core version of Swarm came out on top after MIT researchers tested it out against some highly-optimized parallel processing algorithms, offering three to 18 times faster processing. The most impressive result was when Swarm achieved results 75 times better than the regular chips, because that particular algorithm had failed to be parallelized on classic multi-core processors. There's no indication as to when this technology will be available for consumer devices.

HughPickens.com writes: What should a driverless car with one rider do if it is faced with the choice of swerving off the road into a tree or hitting a crowd of 10 pedestrians? The answer depends on whether you are the rider in the car or someone else is, writes Peter Dizikes at MIT News. According to recent research most people prefer autonomous vehicles to minimize casualties in situations of extreme danger -- except for the vehicles they would be riding in. "Most people want to live in in a world where cars will minimize casualties," says Iyad Rahwan. "But everybody wants their own car to protect them at all costs." The result is what the researchers call a "social dilemma," in which people could end up making conditions less safe for everyone by acting in their own self-interest. "If everybody does that, then we would end up in a tragedy whereby the cars will not minimize casualties," says Rahwan. Researchers conducted six surveys, using the online Mechanical Turk public-opinion tool, between June 2015 and November 2015. The results consistently showed that people will take a utilitarian approach to the ethics of autonomous vehicles, one emphasizing the sheer number of lives that could be saved. For instance, 76 percent of respondents believe it is more moral for an autonomous vehicle, should such a circumstance arise, to sacrifice one passenger rather than 10 pedestrians. But the surveys also revealed a lack of enthusiasm for buying or using a driverless car programmed to avoid pedestrians at the expense of its own passengers. "This is a challenge that should be on the mind of carmakers and regulators alike," the researchers write. "For the time being, there seems to be no easy way to design algorithms that would reconcile moral values and personal self-interest."

"A new study shows that most people prefer that self-driving cars be programmed to save the most people in the event of an accident, even if it kills the driver," reports Information Week. "Unless they are the drivers." Slashdot reader MojoKid quotes an article from Hot Hardware about the new study, which was published by Science magazine. So if there is just one passenger aboard a car, and the lives of 10 pedestrians are at stake, the survey participants were perfectly fine with a self-driving car "killing" its passenger to save many more lives in return. But on the flip side, these same participants said that if they were shopping for a car to purchase or were a passenger, they would prefer to be within a vehicle that would protect their lives by any means necessary. Participants also balked at the notion of the government stepping in to regulate the "morality brain" of self-driving cars.
The article warns about a future where "a harsh AI reality may whittle the worth of our very existence down to simple, unemotional percentages in a computer's brain." MIT's Media Lab is now letting users judge for themselves, in a free online game called "Moral Machine" simulating the difficult decisions that might someday have to be made by an autonomous self-driving car.