Remove works by initially taking a burst of shots in succession. By comparing those shots with one another, it is then able to identify which objects are stationary (the scenery, and/or your posing subject) and which ones are moving (those dang people). It then highlights the moving objects on a preview screen, and allows you to select which ones to remove. The end product is a composite photo, with the offending humans taken out.

Although a certain unwanted person may be blocking the background in one shot, that same bit of background will be visible in another shot – this little fact allows the app to fill in the background when it removes the person. Needless to say, Remove can’t help you with bystanders who are standing still … perhaps if it had a feature that used your device’s speaker to yell "Hey buddy, get out my shot!"

The app is presently still in the prototype stage, but a full version should be ready for a demonstration later this month, at the 2012 Mobile World Conference in Barcelona. It is reminiscent of a system being developed at the University of California, San Diego, that is able to remove pedestrians from Google Street View images.

That’s the idea behind one designer’s concept for a Fujitsu Lifebook, which would come with slots for a smartphone, digital camera, and tablet, for them all to all work together as one super device. The unique concept, dubbed "Lifebook 2013," comes from designer Prashant Chandra, who submitted the design to a competition held by Fujitsu. The laptop would feature fitted slots for various smart devices, but those aren’t for your standard connectivity. Attaching a gadget to the Lifebook would bring all it’s functions to the computer, including using its own processor to run some of the laptop’s functions.

Fitting the digital camera to the front would mean pictures could be downloaded to the computer or other devices. Sliding in the smartphone/mp3 player would allow music to be played and other data to be shared across devices. The Lifebook 2013 concept doesn’t have a keyboard itself, since an tablet becomes the keyboard once slotted into place. The tablet can also be used as a second display (like a larger Nintendo DS) or as a digital sketchpad with a stylus. Aside from potentially reducing the overall cost, another advantage to this setup would be that all the devices can be synced and updated simultaneously from the same hub.

"The proposed Lifebook is a laptop computer concept based on the principle of ‘shared hardware,’" explains Chandra. "Currently a lot of hardware is wasted when we use separate devices, as there is often a lot of ‘repeat’ of data stored and features. For example if I have my songs on my music player, why do I have to block the same amount of storage on my laptop? Similarly, if I have a processor sitting in my tablet, why can it not also run/assist my laptop? If I have a fully functional camera with its own memory and image processing power, why do I need to have it repeated in my laptop?"

Put this way it sounds like a logical step forward for the next generation of laptops, though there is the obvious question of being limited to the concept’s constituent devices, which would clearly be a bit limiting for the consumer.

PlateMate is a crowd-sourced dieting system, in which an online community determines the caloric value of users’ meals

Although taking such an approach to nutrition might sound kind of iffy, calorie estimates generated by the crowd-sourced system are apparently just as accurate as those provided by trained nutritionists, and more accurate than self-kept logs.

PlateMate was first developed by Jon Noronha and Eric Hysen, when they were undergrads in Harvard University’s School of Engineering and Applied Sciences.

Users start by taking a photo of their meal, then submitting it to the crowd. That crowd is coordinated using Amazon Mechanical Turk, a collaborative system that was first developed to help improve Amazon product listings. Individual Turkers, as they’re called, look over the submitted photos and try to determine which foods are present in each one, and in what approximate quantities. The total caloric value of the meal is then automatically calculated, the system averages out the totals generated by the various Turkers, and the user is provided with their answer.

Each Turker receives a nominal payment for every task they accomplish.

Presumably, PlateMate users don’t sit around with the food still on their plate, waiting to see the results before tucking in. The crowd feedback for one meal choice, however, could guide them in choosing types and amounts of foods in subsequent meals.

There were some hiccups (no pun intended) in setting up the system. Some Turkers, for instance, misidentified foods submitted by users from other cultures. Other Turkers took the lazy approach – from an on-screen list of types of food, they simply selected the first term that had some relevance to a food they had identified, instead of searching through the list for a more specific term. These problems were addressed by breaking the process down into clearly defined tasks, posting warnings about common errors, being more selective when choosing Turkers, and applying algorithms that chose the most-likely-to-be-accurate food identification from a number that were selected for one item.

Down the road, user submissions may also be pared with locational data, so Turkers will know the geographical context of what they’re looking at.

"A lot of prior crowdsourcing research has been about making crowds do things that we wish computers could do, like shorten an 800-word essay to 500 words and have it still make sense," said Noronha. "What makes the nutrition application so interesting as a problem in crowdsourcing is that computers are so very far away from doing it on their own – because food is such a human thing."

Known as Gloria (GLObal Robotic telescopes Intelligent Array for e-Science), the three-year European project will ultimately include 17 telescopes on four continents, run by 13 partner groups from Russia, Chile, Ireland, the United Kingdom, Italy, the Czech Republic, Poland and Spain. Not only will users be able to control the telescopes from their computers, but they will also have access to the astronomical databases of Gloria and other organizations.

The telescope at Spain’s Montegancedo Observatory is serving as the model for Gloria. Located at the Universidad Politécnica de Madrid’s Facultad de Informática, it can already be remotely operated through the internet, using the university’s Ciclope Astro software. This same software will be used by all the Gloria telescopes, to ensure uniformity across the system.

The amount of time that individual users get on the telescopes will be based on their "Karma," determined by how popular their work is with their fellow users. It will reportedly be somewhat like YouTube, where users vote on each other’s video posts.

While the EUR2.5 million (US$3.4 million) project is intended to help armchair astronomers of all types explore the Universe for themselves, it will also be used for crowd-sourced research. The University of Oxford in particular will be using Gloria for its Galaxy Zoo project, in which users are recruited to help classify approximately a million galaxies. Astronomical events will also be broadcast on the system, to help promote Gloria and built its user community.

Graph of media sentiment towards Egypt january 1979 – March 2011

Nipping at the heels of yesterday’s story about the software that automatically writes news articles comes another technological innovation changing the shape of journalism: software that reads news articles.

Kalev Leetaru of the University of Illinois determined that using the Nautilus SGI supercomputer to analyze news stories can help predict major world events. The analysis he used for the experiment was retrospective, feeding the computer millions of articles from which it was able to determine a deteriorating national sentiment towards Libya and Egypt before the revolutions in those countries. The system was also able to narrow down Osama Bin Laden’s location to within 125 miles before he was found and killed last May.

More than 100 million articles were gathered for this study, from various sources including the New York Times archive, Open Source Center and BBC Monitoring (two organizations that monitor local media output worldwide). The system searched for two primary things in the articles: mood and location. Words such as “nice” or “horrible” were used to measure mood, and geocoding converted mentions of places such as “Cairo” or “Pakistan” to plottable coordinates.

For countries that experienced the “Arab Spring,” the supercomputer produced graphs that showed a noticeable decline in media sentiment both within each country and without. Before President Mubarak’s resignation, the tone of media coverage of Egypt fell to one of its lowest points in 30 years, predicting something that U.S. government could not. As Leetaru told BBC news, the president’s continued support of Mubarak showed that high-level analysis suggested Mubarak wasn’t going anywhere. The graph, however, suggests otherwise.

Leetaru’s next step is developing technology to allow this system to forecast major world events, rather than just analyzing them after the fact. He compares it to economic forecasting algorithms, as well as meteorology, in that none of those systems (including his) are perfect, but using them is far better than just guessing.

In April, the University of Southern California made the headlines when it announced that researchers there had created a functioning synthetic synapse circuit using carbon nanotubes. Well, today IBM unveiled a new class of experimental computer chips that are designed to emulate the human brain’s abilities for perception, action and cognition. According to the company, "The technology could yield many orders of magnitude less power consumption and space than used in today’s computers."

Utilizing advanced algorithms and silicon circuitry, the two prototype "neurosynaptic computing chips" are said to recreate the phenomena that takes place between spiking neurons and synapses in biological systems. The idea is that such chips would be used in "cognitive computers," which would learn through experiences – like the human brain – rather than simply being programmed.

To that end, IBM has joined forces with a number of academic partners, to develop such computers through the Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) project. According to the company, "The goal of SyNAPSE is to create a system that not only analyzes complex information from multiple sensory modalities at once, but also dynamically rewires itself as it interacts with its environment – all while rivaling the brain’s compact size and low power usage." Phases 0 through 1 have already been completed, while the Defense Advanced Research Projects Agency (DARPA) has reportedly awarded the project US$21 million in funding for Phase 2.

The two chips themselves contain no biological components. According to the press release, however, both chips do feature 256 artificial neurons, with one core containing 262,144 programmable synapses, and the other containing 65,536 learning synapses. In lab tests, the chips have so far been used to execute simple applications such as navigation, machine vision, pattern recognition, associative memory and classification.

Ultimately, IBM hopes to produce a chip system featuring ten billion neurons and hundred trillion synapses, that would consume one kilowatt of power and have a volume of less than two liters (0.5 U.S. gallons).

"Future applications of computing will increasingly demand functionality that is not efficiently delivered by the traditional architecture," said Dharmendra Modha, project leader for IBM Research. "Imagine traffic lights that can integrate sights, sounds and smells and flag unsafe intersections before disaster happens or imagine cognitive co-processors that turn servers, laptops, tablets, and phones into machines that can interact better with their environments."

Partners in Phase 2 of SyNAPSE include Columbia University, Cornell University, the University of California at Merced, and the University of Wisconsin, Madison.

The BCMI lets you create music using nothing more than eye movement and brainwaves

Imagine a Wii that lets you play a musical instrument with your brain without touching strings or a keyboard. That’s exactly what this "proof of concept" brain-computer-music-interface (BCMI) is designed to do – it uses brain waves and eye movement to sound musical notes, so even a person with "locked-in-syndrome" could participate in creative activity analogous to learning to play a musical instrument. Developed by a team headed by Eduardo Miranda, a composer and computer music specialist from the UK’s University of Plymouth, the BCMI can be set up on a laptop computer for under $3,500 (including the computer). For people who are disabled, assistive technology usually aims at day-to-day functioning and largely ignores the unique aspect of being a human – creativity. This is different.

The Brain Computer Interface as an assistive technology

"Creativity – like human life itself – begins in darkness." – Julia Cameron

No-one wants to even think about it but imagine a car crash or a stroke left you totally paralyzed and your only active movements were eye movements, facial gestures and minimal head movements. If you still retain full cognitive capacity, you would have what is called locked-in syndrome, a fate some might regard worse than death. For any person with a disability, one of the biggest obstacles is that people simply assume that if your body doesn’t work, then your brain is probably not capable of much either. How much worse is this for the person isolated by locked-in syndrome?

Historically, assistive technologies have relied on the person being able to maneuver at least one part of their body. For example, an Augmented Communication Device may require them to press buttons on a keyboard that has pre-designated questions, statements or responses. These devices can be adapted in order for the buttons to be pressed with a finger, a toe, or a metal-pointer attached to their head. Pretty impressive. But what about people with locked-in syndrome who aren’t capable of such motor function other than eye movements? Most of the technology has been simply passing them by.

Technology in the form of the brain computer interface (BCI) provides hope for these and many other people because we no longer have to imagine being able to use our thoughts to control a wheelchair or a communication device. In the past decade this technology has moved increasingly from fantasy into a reality.

In 2007, Mike Hanlon wrote about "The first commercially available Brain Computer Interface" and pointed out how work in the area was focused on enabling paralyzed humans to communicate far more freely, but noted the potential to enhance everyone was not that far away. He was right. Within the last five years we have moved from the ability to point with the mind to a thought controlled cursor. And we have moved from driving wheelchairs with brainwaves to driving a car controlled by mind power.

The brain-computer-music-interface

This latest development has thrust the BCI into the world of music and creativity where, in this, its first use, the brain computer musical interface promises to enhance life immensely for those with a most severe disability, locked-in syndrome.

This is the brainchild of a team headed up by Eduardo Miranda, and the Plymouth BCMI Project [PDF]. The system is not yet wireless, but uses a laptop computer, related software, 3 electrodes and an EEG amplifier and can be built for under US$3,500.

Using brainwaves a person can almost immediately produce a full range of musical notes from this device by simply looking intently at one of four icons. These four icons are responsible for sounding pitch, rhythm, and controlling the strength and speed of the notes. Like learning to play a musical instrument, playing music with this device requires skill and learning. As the scientists note, however, this can be an attractive attribute.

With minimal practice in this proof of concept test, the person with locked-in syndrome rapidly demonstrated skill at playing and found it an enjoyable experience.

Check out what such a device can do when output from it is hooked into a piano keyboard. A practiced person has the potential to play masterful music using nothing but his or her brainwaves.

A whole new medium for creativity

Assistive technologies have made life easier for millions of people with disabilities around the globe. We have technology that can help people at home and at work; help them to communicate; help them with mobility. In fact you could say we’ve got technology for almost everything important to a person’s life, right? But until now, these technologies largely ignored the most unique aspect of being a human – creativity.

In the grand scheme of life, you probably wouldn’t say that cooking dinner for yourself or getting yourself out of bed in the morning were the things you were most proud of achieving. People want to be unique, innovative, and admired for their talents. Why else would we write books, design cars, or start our own companies? It’s in our nature to create. The BCMI promises to give a whole new medium for creativity because it can be used by anyone almost regardless of any physical disability. Inside each one of us is the untapped potential to be the next Beethoven without the agony of studying music theory or learning the piano. All you need is a brain.

Millimeter-Scale Computer

Tiny-fingered researchers at the University of Michigan have created this computer, the world’s first complete millimeter-scale computing system. It is a prototype designed to be implanted in a human eye, to monitor internal pressure there for signs of glaucoma.

The machine includes a teeny battery, a consolidated radio and antenna, a pressure sensor, memory, and a rather diminutive processor designed to consume extremely little power.

IBM has announced its fifth annual Next Five in Five – a list of five technologies that the company believes “have the potential to change the way people work, live and play over the next five years.” While there are no flying cars or robot servants on the list, there are holographic friends, air-powered batteries, personal environmental sensors, customized commutes and building-heating computers.

3D telepresence

It may not be a flying car, but it’s definitely one we’ve seen in sci-fi movies before – the ability to converse with a life-size holographic image of another person in real time. The futurists at IBM point to recent advances in 3D cameras and movies, predicting that holography chat (aka 3D telepresence) can’t be all that far behind. Already, the University of Arizona has unveiled a system that can transmit holographic images in near-real-time.

It is also predicted that 3D visualization could be applied to data, allowing researchers to “step inside” software programs (wasn’t that just in a movie?), computer models, or pretty much anything else that is limited by a simple 2D screen. IBM compares it to the way in which the Earth appears undistorted when we experience it first-hand in three dimensions, yet it appears pinched at the top and bottom when we see it on a two-dimensional world map.

Air-powered or non-existent batteries

Lithium-air batteries are already in the works, and IBM predicts that batteries “that use the air we breath to react with energy-dense metal” will result in smaller, lighter rechargeable batteries that last ten times longer than today’s lithium-ion variety. While such batteries could be used in everything from cars to home appliances, it is also suggested that small items such as mobile phones might not need batteries at all. IBM is trying to reduce the amount power required for such devices to less than 0.5 volts per transistor. At those rates, it is claimed, they could be powered via “energy scavenging” – like already-existing kinetic wrist watches that get their power from the user’s arm movements, or experimental piezoelectric devices.

Personal sensors creating “citizen scientists”

As it currently stands, most scientific data must be gathered by scientists, who have to go out in the field and set up sensors or other data recording devices. Within five years, however, a lot of that data could be gathered and transmitted by sensors in our phones, cars, wallets, computers, or just about anything else that is subjected to the real world. Such sensors could be used to create massive data sets used for everything from fighting global warming to tracking invasive species. IBM also sees custom scientific smartphone apps playing a part in “citizen science,” and has already launched an app called Creek Watch, that allows us regular folks to update the local water authority on creek conditions.

Customized commutes

Invaluable as Mapquest and other online mapping services have become to many of us, apparently it’s just the tip of the iceberg. In the not-so-distant future, says IBM, sensors and other data sources (such as the aforementioned citizen scientists, perhaps?) will provide a continuous stream of information on traffic conditions, road construction, public transit schedules, and other factors that could affect your commute. When you inquire about the quickest way of getting from A to B, computer systems will do more than simply consulting a map – they will also take into account all the variables unique to that day and time, combine them with mathematical models and predictive analytics technologies, and advise a route accordingly. It is also possible that, utilizing such data, traffic management systems could learn traffic patterns, and self-adjust themselves to minimize congestion.

Harvesting computer heat

It is estimated that half of the energy consumed by data centers goes toward cooling computer processors, with most of the removed hot air simply being blown into the atmosphere. Instead, IBM sees that heat being captured to warm the air in other areas of the building, to heat water, or to be converted into electricity. The company has already developed an on-chip water-cooling system for computer clusters, which is being demonstrated on the Swiss Aquasar supercomputer. It utilizes a network of microfluidic capillaries inside a heat sink, attached to the surface of each chip. Water flows within a few microns of the semiconductor material, picks up heat from it, then pipes the warm water to a heat exchanger – from there, the cooled water returns to the computers, within a closed loop system.

As with last year’s list, given that all of these technologies are already in experimental use, it’s a pretty good bet that they will indeed one day find their way our lives. Whether that day is within the next five years, however, is another question.

The Adult Visual Cortex Neurons in the brain’s visual pathway can transmit images to the brain faster than the conscious mind can assess them. But hook a computer to that brain and its visual pathway becomes a supercharged analysis tool.

Brain-machine interfaces hold potential for a variety of ends, from helping the neurologically or physically disabled communicate and interact with their environments, to creating thought-controlled computers that augment the brain with computing power. A group of researchers at Columbia are turning that model on its ear, using brain power to augment computing tasks. Their device couples the human brain and computers to perform tasks neither could do as efficiently on their own.

The device, known as C3Vision (cortically coupled computer vision) taps into the fast processing power of the brain to help computer programs manage complex problem, particularly those posed by image recognition. An electroencephalogram (EEG) cap on the head of a human user is used to detect neurological signals in the brain. The computer then flashes images up on the screen at a rate of about ten per second. The conscious brain doesn’t even have time to adequately consider each image, but the subconscious is hard at work.

The system is great at working our problems that computer language has a problem tackling. For instance, it’s easy enough to search for a picture of a bicycle on the Web, but it’s far more difficult for a search engine like Google or Bing to search for something that looks “odd” or perhaps “silly.” The brain, however, can take these less-defined, more abstract qualifiers and very quickly assess whether or not an image fits the term.

The conscious brain doesn’t even have to get involved. The images flash too quickly for a person to rate his or her interest in each one, but the visual pathways in the brain move much more quickly. Machine-learning algorithms can quickly detect the neurological signals that represent the brain’s interest in a given image, and helps the computer to rank the images for interest. If the person sees something interesting or different, the computer knows it even if the person does not.

As such, the system has been used in tests to accurately scan satellite images for the presence of surface-to-air missiles faster than either a human or a machine could alone. Which accounts for DARPA’s interest in the technology; the DoD research arm has sunk $4.6 million into the development of the tech via a spinoff from the university. But the tech could also be used for a variety of other tasks that require the analysis of large volumes of visual data.