Shown off by Microsoft’s chief research officer Rick Rashid at TechFest 2012, the technology preserves the speakers timbre, accent, and intonation while translating between 26 languages supported by Microsoft speech. While it leaves a trace of digitized robot voice on some syllables (you can hear some samples via the Extremetech link below), it does a remarkably good job of maintaining the speaker’s own nuances of speech while swapping in the proper words and conjugations.

The process isn’t exactly instantaneous, at least not from a full stop. The software needs to spend about an hour with each party learning the particulars of that person’s individual speech characteristics. But once the software is acclimated, it can translate more or less in real time. The idea is that one day in the not too distant future, we will be able to train our phones just once in the styles of our speech and then use the software to speak over the phone with anyone, regardless of whether we share a language, in real time.

In other translation-on-my-smartphone news, researchers at the University of Aberdeen are developing an application that uses the camera on a laptop or mobile device to translate sign language directly into text. The idea is to extend an understanding of sign language to the vast majority of people who aren’t fluent, and in the process increase the opportunities for conversation between those with hearing disabilities and the world around them. The team hopes to have the technology available as a product by 2013.

The goal is to democratize sequencing and eliminate the still-heady costs associated with genetic analysis, making DNA and protein sequencing as commonplace as an exam with a tongue depressor.

Oxford Nanopore Technologies Ltd. uses a proprietary nanopore detection system to seek out and study molecules. Nanopores are organic molecules with a hole in them, embedded in a polymer membrane. The membrane’s electrical field allows individual strands of DNA to pass through the nanopores, and the disruption in current through the nanopore can be analyzed and matched to base pairs.

The company uses this setup in two configurations: the GridION system, which consists of nodes filled with disposable test cartridges containing multiple nanopores, and the MinION, designed for portable analysis of single molecules.

Each GridION node and cartridge is initially designed to deliver tens of gigabytes of data every 24 hours. Initially, the company intends to make 2,000-nanopore cartridges, but has plans for a 20-node installation using an 8,000-nanopore configuration. The latter would be expected to deliver a complete human genome in 15 minutes, the company says.

MinION is much smaller and can sequence up to 150 million base pairs in six hours. It uses blood, plasma and serum for sample analysis, like other lab tests, and it doesn’t need polymerase chain reaction amplification techniques to work. It will be on sale for $900 later this year, according to the company.

With technology like this, fast, sub-$1,000 genome sequencing could become commonplace.

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.

Imagine you’re a developer and you have some code you’d like to run on a quantum computer. And imagine there’s a quantum computer maker who says you can run your code. But you can’t trust each other — you, the developer, don’t want the computer maker to rip off your great code, and the computer builder doesn’t want you to peep its breakthrough machine. This new system can satisfy both of you.

Stefanie Barz and colleagues at the University of Vienna’s Center for Quantum Science and Technology prepared an experimental demonstration of a blind computing technique, and tested it with two well-known quantum computing algorithms.

Here’s how it would work: You, the developer, prepare some quantum bits, in this case photons that have a polarity (vertical or horizontal) known only to you. Then you would send these to the remote quantum server. The computer would entangle the qubits with even more qubits, using a quantum entangling gate — but the computer wouldn’t know the nature of the entangled states, just that they are in fact entangled. The server is “blind” to the entanglement state, and anyone tapping into the server would be blind, too.

Imagine the computer tries to snoop on the qubits and see their entanglement, which could then be used to extract the information they carry. You’d be able to tell, because of the laws of quantum mechanics. The cat is both dead and alive until you check whether it’s dead or alive, and then it’s one or the other. If your photon has a specific state, you’d be able to tell that it was spied upon.

Back to the entangled bits. The actual information processing takes place via a sequence of measurements on your qubits. These measurements would be directed by you, based on the particular states of each qubit (which, again, only you know). The quantum server would run the measurements and report the results to you. This is called measurement-based quantum computation. Then you’d be able to interpret the results, based on your knowledge of the qubits’ initial states. To the computer — or any interceptor — the whole thing would look utterly random.

Since you know the entangled state on which the measurements were made, you can be certain whether the server really was a quantum computer. And you wouldn’t have to disclose your algorithm, the input or even the output — it’s perfectly secure, the researchers write in their paper, published online today in Science.

Blind quantum computation is more secure than classical blind computation, which relies on tactics like the backward factoring of prime numbers, said Vlatko Vedral, a researcher at the University of Oxford who wrote a Perspective piece explaining this finding.

“The double blindness is guaranteed by the laws of quantum physics, instead of the assumed difficulty of of computational tasks as in classical physics,” Vedral writes.

The Vienna team argues their simulation is a potentially useful technique for future cloud-based quantum computing networks.

“Our experiment is a step toward unconditionally secure quantum computing in a client-server environment where the client’s entire computation remains hidden, a functionality not known to be achievable in the classical world,” they write.

The teaser video (below) doesn’t offer a ton of information about the computer, but does show off a widget hub in the corner of the desk you can use to launch applications on the screen, and the ability to pull down a timeline populated with news information, tweets, or other alerts from the top corner of the table. Both the widgets and the timeline can be casually swiped away when you’re done with them, and the screen and location of the widgets can be customized to meet your own personal needs. The ExoPC also supports full-screen applications, showing off in the video an app that instantly turns the computer into an electronic piano.

Multi-touch desk computers aren’t really anything new. Samsung for instance recently announced the Samsung SUR40, a 40-inch, 1080p multitouch table running Microsoft’s Surface software. Where the ExoPC stands out, however, is in its price tag. While the SUR40 and other table computers are designed for businesses (and priced that way, the SUR40 is US$8,400!), the ExoPC is instead priced at a modest $1,299 making it affordable for average consumers.

The Samsung SUR40 is expected to be a computer replacement, however, the ExoPC also appears to be something you would use as a replacement for a traditional desk, and a supplement for your actual computer.

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.

A consumer version of a system already in use at some U.S. animal shelters, iPet Companion Home Version lets computer users remotely control dog or cat toys located in their home, watching their pets reacting to those toys’ movements in real time. For some people, it could be the biggest workplace distraction since Facebook.

The in-home iPet hardware consists of a webcam, a control box, and two mechanisms that are capable of swinging and bobbing one pet toy each (which aren’t included). Remotely accessing a password-protected online portal, users utilize onscreen controls to operate the two mechanisms, making the toys move. The live webcam feed shows them the moving toys, along with their critters’ reactions – hopefully, the animals will respond by playing with the toys, as opposed to being freaked out by two inanimate objects that appear to be moving on their own.

If users don’t want to spend too much company time goofing off with Fido or Felix, they can spread the playtime around by giving their password to family and friends. In the commercial version of iPet Companion, anyone can access the portals, with users often having to wait several minutes in an online queue before they can interact with the shelter animals.

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.