This Crazy Gadget Helps You “Talk” To Your Computer Without Words

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Hey you! Ever wish your technology was more invasive? You love voice-to-text, but it’s just too public?

Some researchers at MIT Media Lab have come up with the perfect gadget for you. And it looks like a Bane mask crossed with a squid. Or, if you prefer: like a horror movie monster slowly encompassing your jaw before crawling into your mouth.

The researchers presented their work at the International Conference on Intelligent User Interfaces (yes such a thing exists) in March in Tokyo.

Whenever you think of words, they’re silently, imperceptibly, transmitted to your mouth. More specifically, signals arrive at the muscles that control your mouth. And those signals aren’t imperceptible to a highly sensitive computer.

The researchers call this device the AlterEgo. It’s got seven electrodes positioned around the mouth to pick up these signals. The data that the electrodes pick up goes through several rounds of processing before being transmitted wirelessly to a device awaiting instruction nearby. Oh, and it’s got bone-conduction headphones so that devices can respond.

AlterEgo in use. Kapur et al, 2018

The scientists tested their prototype on a few people who trained the software to recognize the data that corresponded to different commands (“call,” “reply,” “add,”), then on a few more to see how accurate it was. The results were promising, though it’s not exactly ready to go into mass production.

The closest comparison to this system is a device you can address in your normal speech, like Siri or Alexa. But, terrifyingly, this is not scientists’ first attempt at creating a more direct way to transmit our thoughts to computers. Most earlier versions have relied directly on brain signals (from devices laid over or implanted in the brain. No thank you).

AlterEgo has the following advantages, according to the researchers:

  • It’s not invasive (seems like kind of a low bar but ok)
  • It’s 92 percent accurate (probably marginally better than your average autocorrect, about the same as Siri or Alexa)
  • It’s portable (and about as sexy as one of those Bluetooth earpieces)
  • Unlike direct brain readings, it can’t read your private thoughts (except for the ones you quietly mouth to yourself)

I admit, in some situations a device like this might be useful. Particular movements could tell your phone to turn on music, or use a calculator, or text your friend. It could control your “smart home,” turning off the oven or starting the coffeepot with a mere twitch. Heck, in 10 years, I could be thinking this article into existence. This goes double for people with disabilities or vision problems that might make controlling a digital device challenging otherwise.

BUT. But. There are a few things that might make AlterEgo less than ideal. The electrodes can’t shift when a person is using them, for example, or the reading will get all messed up. It’s hard to imagine that people would be comfortable hanging out with a device covering half their mouths. And there’s no telling how the system would do in real-world settings — that’s what the researchers have to test out next. And, of course, there’s the issue of crossed signals, like when Alexa thought random sounds were telling it to laugh. And — just thinking big for a second — if it were hacked, could the hacker use the electrodes to physically control your mouth?

Might we have a future in which our faces butt-dial for us? Who’s to say. But you can bet all the people in my nightmares of a dystopian future are equipped with one of these bad boys.

The post This Crazy Gadget Helps You “Talk” To Your Computer Without Words appeared first on Futurism.


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Apple Watch helps solve brutal murder

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An Australian woman claims her mother-in-law was killed in their home by unknown assilants, but data from the victim’s Apple Watch contradicts that testimony. An Apple Watch tracks the wearer’s heartbeat. This means it knows exactly when that heart stops, allowing Adelaide police to know precisely when this murder had taken place. And that was […]

(via Cult of Mac – Tech and culture through an Apple lens)

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Sage: Why gender-neutral AI helps remove social bias

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AI technologist Kriti Sharma (pictured) has the ambition of bringing greater diversity and accountability to the algorithms that guide our decisions and sift through our data.

Since starting at UK software company Sage, she has been working on a gender-neutral virtual assistant, Pegg, which is designed to manage customers’ business finances. She has also published a set of core ethical principles for designing AI systems.

Sharma, 29, is now VP of AI at the Sage Group, and is one of a growing number of women with high-profile roles in the artificial intelligence sector.

For example, the UK’s new Office for AI is jointly run by Gila Sacks, director of digital and tech policy at the Department for Digital, Culture, Media, and Sport (DCMS), and Dr Rannia Leontaridi, director of Business Growth at the Department for Business, Energy and Industrial Strategy (BEIS).

Read more: Top priest shares ‘The Ten Commandments of A.I.’ for ethical computing

AI and bias reinforcement

Driving Sharma’s work at Sage is her fear that AI and the fourth industrial revolution will entrench inequality rather than provide solutions to it. Instead of emerging technologies easing problems such as gender, race, and age inequality, the risk is that they could perpetuate them by cementing biases that already exist in human society.

This issue is explored in this external report by Internet of Business editor Chris Middleton.

Speaking to Middleton last year at the Rise of the Machines summit in London, Sharma described herself jokingly as “a token millennial” who had been brought into Sage to shake things up. She explained her belief that the technology industry’s efforts to create human-like software is a strategic error. Instead, AI should “embrace its botness”, she said.

Sharma went on to make the point that many AIs tend to be feminine personalities with female voices, and are designed to respond to routine commands. Meanwhile, some industry-specific systems – in legal services and banking, for example – are often designed to be ‘male’. In this way, she suggested, we risk “projecting workplace stereotypes onto AI” and, by doing so, we reinforce them.

Sharma has expanded on that view in an interview this week. “Despite the common public perception that algorithms aren’t biased like humans, in reality, they are learning racist and sexist behaviour from existing data and the bias of their creators. AI is even reinforcing human stereotypes,” she told PRI.

She shared the example of recent research from Boston University, in which technologists developed an AI program using input from Google News. When the system was asked, “Man is to computer programmer as woman is to X,” the response was “homemaker.”

Unchecked bias such as this both reflects the mass of data stored by human society to date, and highlights the care that programmers need to take when designing software for everyone. (Countless other examples of bias in AI systems – in which racial prejudice appears to be the most commonplace – are included in Middleton’s independent report.)

Read more: AI regulation & ethics: How to build more human-focused AI

Developing a gender-neutral virtual assistant

Sharma’s gender-neutral AI assistant Pegg symbolises her attempt to ensure that technology helps to tackle deeply embedded social and cultural stereotypes. Unlike the domesticated Amazon Alexa or the down-to-business IBM Watson, Pegg is designed to be a sidekick without obvious stereotypes, she said.

“Pegg is proud of being a bot and does not pretend to be human. Initially, there was a lack of awareness within the company and the outside world of stereotypes in AI, but I found it very encouraging that I got a very welcoming response to my efforts.”

Read more: IBM launches new Watson Assistant AI for connected enterprises

Accountability and transparency

According to Sharma, the two key components in developing AIs that reflect social diversity, rather than existing prejudices, are accountability and transparency. Only by understanding the full end-to-end development processes that any artificial system goes through can we check for inherent bias and keep its designers accountable.

“AI needs to reflect the diversity of its users,” she told the Financial Times earlier this month. This means using data sets that are as diverse as possible and making software that’s applicable to everyone.

For example, Google’s image-tagging algorithm was widely condemned in 2015 after it accidentally labelled black people as ‘gorillas’ – an issue that was only rectified by removing the offending word and associated terms from the system completely. The mistake was rooted in the data sets used to train the system.

Related problems have been identified across a whole range of AI systems, from imaging technologies that have long been optimised to identify light skin tones, to the MIT facial recognition system that was unable to identify a black woman, because the training data was compiled by, and among, a closed group of young white males.

The latter example was shared by MIT Media Lab chief Joichi Ito at the 2017 World Economic Forum in Davos, where he called his own students “oddballs”.

Ito suggested that many coders prefer the binary world of computers to the messier and more complex world of human beings. Most coders are young, white males, he added, and this lack of diversity in the technology community is often reflected in the systems that developers design, test, and release.

Some AI systems have also been shown to be better at identifying men than women – again, because of biases in the training data.

“AI is a fascinating tool to create equality in the world,” said Sharma. “When I’ve worked with people from diverse backgrounds, that’s where we’ve had the most impact.

“AI needs to be more open, less elite, with people from all kinds of backgrounds: creatives, technologists, and people who understand social policy… getting together to solve real-world problems.”

Plus: The five pillars of AI

In related news, analyst Ray Wang of Constellation Research today published an opinion on AI ethics, in which he suggested that there should be five pillars of development.

Wang said that AI should be: Transparent, so that algorithms, attributes, and correlations should be open to inspection for all participants; explainable, so that humans should be able to understand how AI systems come to their contextual decisions; reversible, so that organisations are able to reverse the learnings and adjust as needed; trainable, so that systems have the ability to learn from humans and other systems; and human led, so that all decisions begin and end with “human decision points”.

But he added, “Prospects of universal AI ethics seem slim. However, the five design pillars will serve organisations well beyond social fads and fears.”

Internet of Business says

We salute Sharma’s work and her commitment to both addressing these problems herself and raising awareness of the issues. It’s notable, too, that this was her personal choice, proving that one person can make a big difference if they set out to do so.

The underlying problem is easy to express: it is not that developers are themselves knowingly biased or prejudiced (necessarily) – it would be a mistake to label the technology community has inherently racist, for example; it is more that most AI systems rely on human beings to train them with data.

Any existing bias in that data – for example, in legal systems that have exhibited a bias against any ethnic or social groups over decades of case law – will then be picked up by the system. Equally, any lack of diversity in the technology community itself – which is known to be overwhelmingly white and male – also risks finding its way into the systems that community designs.

Last year, UK-RAS, the UK’s umbrella organisation for robotics and AI research, quoted figures suggesting that 83 percent of people working in science, technology, engineering, and maths (STEM) careers are male. Among coders, the split is closer to 90 percent male to 10 percent female, with an even stronger bias towards white employees. The systems they produce must not be allowed to reflect these biases.

Read more: Women in tech: the £150bn advantage of increasing diversity

Read more: AI regulation & ethics: How to build more human-focused AI

Read more: Women in AI & IoT: Why it’s vital to Re•Work the gender balance

Additional reporting: Chris Middleton.

The post Sage: Why gender-neutral AI helps remove social bias appeared first on Internet of Business.

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How Washie Helps Keep Your Car Squeaky Clean

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MakeUseOf is expanding its repertoire of apps! Earlier in 2018, we brought you NeedHave, an app to connect donors with those in need, and Obliviate, an app for sending self-destructing messages. Now we’re excited to announce the release of our newest app: Washie. Read on to see what Washie does and how to use it.

Download: Washie for Android | iOS (Free)

What Is Washie?

Washie is a straightforward iOS and Android app that helps you make sure you never wash your car right before a storm again.

There’s nothing worse than spending money on a car wash (or taking the time to do it yourself), only to have rain ruin it the next day. Not only does this waste time, but it’s a waste of money to wash your car when it’s not needed.

Washie provides you with a seven-day forecast and gives you a clear Yes or No on whether you should get a car wash. If there’s rain or snow scheduled in the next week, the app will recommend you avoid getting a wash.

But you don’t even have to check the app manually. Washie will automatically notify you when it’s a good day for a wash. And if you like, you can change the number of days ahead that Washie warns you of rain.

Let’s look at how Washie works.

Using Washie

Washie Car Wash App Main Screen

Download Washie from the App Store and open it on your device. You’ll have to grant the app permission to send notifications and use your location before proceeding, or the app won’t work as intended.

Once you’ve done that, you’ll see Washie’s main screen. Slide the car from the left side of the screen to the right to see if you should wash your car today.

This reveals Washie’s home screen, with a big Yes or No answering whether you should wash your car. You’ll see the seven-day forecast below, with each day’s temperature and conditions. If any of the next seven days calls for rain or snow, you shouldn’t wash your car.

Washie Settings

Washie Car Wash App Settings

Tap the three-bar Menu button at the top-right of Washie’s main screen to open its settings. Here, you can toggle a few options:

  • Weather criteria: Decide how many consecutive rain-free days Washie will check when recommending a wash.
  • Wash reminders: Turn this off if you don’t want to see a notification when it’s a good day for a wash.
  • Units: Choose between Fahrenheit and Celsius for temperature readings.

You’ll also see links to share the app with friends, check out MakeUseOf’s other apps, get in contact with the developers, or rate the app.

To return to the main screen from Settings, just swipe in from the left side of the screen.

Washie Saves You Time and Money

Washie is a simple app designed to make car washes simple. The automated reminders mean you don’t have to manually check if it’s going to rain in the next week, saving you time. And by avoiding washing your car right before a storm, you save money by getting the most out of your wash.

So if you’re tired of rain ruining your shiny clean car and don’t want to plan a schedule for getting your car washed, let Washie do the work. Your car will thank you!

Download: Washie for Android | iOS (Free)

Image Credit: baranq/Depositphotos

iPhone and iPad – MakeUseOf

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Grovermade’s new HomePod stand helps you avoid white ring woes

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Afraid of your new HomePod leaving unsightly rings on your wooden furniture? Grovermade’s new accessory may be the solution you seek.

Today, Oregon-based tech accessory manufacturer Grovermade launched the latest addition to its line of beautifully designed desktop solutions. Called the HomePod Stand, it’s essentially a base that sits underneath your shiny new HomePod, keeping the silicone away from your finished wood while also displaying it securely and attractively.

The stand sits underneath your HomePod like a coaster would, but don’t be mistaken — it isn’t a coaster, at least according to Grovermade:

The problem was straightforward: Apple has admitted the HomePod leaves a white ring on naturally finished wood, the same type of finish on our wood products. There are some easy fixes. You could use a wool felt pad, basically a glorified coaster, to solve the problem. But it didn’t sit right with our team. It was too easy. It felt more like a bandage than a real solution. And, it looked ugly. We didn’t want to just protect the table, we wanted to make the HomePod better!

And better it is. Aesthetically, each stand is minimal and tidy, and made of precision-machined and hand-finished aluminum, hardwood, or cork. That way, you can select whichever finish would fit best in your home and add to the beauty of your speaker, not detract from it. You can even choose between two different woods (walnut and maple), two different cork colors (dark and light), and two different metal finishes (black and silver). In addition, to further protect your pristine tabletop, every stand come with a layer of microsuede on its underside.

If you’d like an alternative to using decorative scissors to cut out a piece of felt to stick underneath your HomePod (not that there’s anything wrong with that), you can get Grovemade’s HomePod Stand for yourself starting at $ 20. If I were you, I’d order one ASAP, because there’s currently a 2-4 week wait for delivery.

See at Grovermade


Are you considering the HomePod stand for your HomePod? Let me know in the comments!

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AI Helps Scientists Discover New Viruses — Here’s Why That Matters

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Viruses are all around us, and we currently haven’t classified even a fraction of that huge and diverse population. The tiny organisms that can only survive inside a living host can wreak havoc on our bodies, but that’s not the only reason researchers are so compelled by them. We now know that viruses could be playing a part in “non viral diseases” such as liver cirrhosis, or even chronic fatigue syndrome and inflammatory bowel disease — but we still don’t understand how.

To get there, we need machine learning.

Because viruses can’t be grown in the lab, scientists have traditionally looked for new species by sampling various diverse environments (including metro carriages and sewage systems). But picking single microbes out of the dirt is a slow process that makes it difficult for researchers to understand the behavior of fast-evolving viruses.

That’s where AI comes in. Machine learning is a form of artificial intelligence used to identify complex patterns — the algorithm gets trained through a pool of data before becoming autonomous, and can be used to scan massive genomic datasets in search of new viruses.

For example, Nature reports, bioinformatician Deyvid Amgarten, who works at the University of São Paulo in Brazil, used machine learning to identify virus genomes hidden in compost piles at the city’s zoo. He told Nature he will use his findings to learn how viruses can help break down organic matter and make composting more efficient.

His work was inspired by a tool built by Jie Ren. Ren, a computational biologist at the University of Southern California in Los Angeles, used his algorithm to examine and compare faeces samples from people with liver cirrhosis, and healthy people. His team found some viruses more common in healthy people than in those with cirrhosis, a clue that viruses could be playing a part in the disease.

According to Nature, findings such as Ren’s leave scientists wondering if viruses could also influence elusive diseases such as chronic fatigue syndrome and inflammatory bowel disease, which is estimated to affect around three million adults in the U.S. alone. Immunologist Derya Unutmaz, who works at the Jackson Laboratory for Genomic Medicine in Farmington, Connecticut, echoes these speculations, observing that viruses may be the source of inflammatory reactions that could impair our metabolism and immune system.

From identifying the role of viruses in non-viral diseases, to matching viruses with specific families of bacteria to fight drug resistance, artificial intelligence may revolutionize how we navigate the largely uncharted landscape of these tiny microbes that play such a huge part in our lives.

The post AI Helps Scientists Discover New Viruses — Here’s Why That Matters appeared first on Futurism.


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Facebook’s latest Android app helps you find and pay for public Wi-Fi

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Facebook has quietly launched an Android app for its Express Wi-Fi initiative, which lets users log on to public Wi-Fi networks hosted by local partners, for a nominal fee. The company began testing the service in India back in 2015, and rolled it out across 700 hotspots there last May, and it also became available in four other countries thereafter. The new app works in Indonesia and Kenya, notes TechCrunch. Oddly enough, it’s not available to me in India, even though the app supports Indian languages and its screenshots mention locations in the country. While Express Wi-Fi’s service has been…

This story continues at The Next Web

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Samsung Galaxy S9 teardown helps explain its camera tricks

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Samsung's Galaxy S9 and S9+ revolve around their camera features, but some of the hardware functionality behind them has been a little mysterious. The picture is a little clearer, however, as iFixit has torn down the S9+ and provided a better look a…
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Health IoT: App helps sports stars predict and manage injuries

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Researchers at the University of Tennessee Chattanooga have developed a platform that measures an athlete’s risk of injury using the Internet of Things (IoT).

The new system could allow athletes at every level, from superstar to hopeful, to create a personal injury risk profile, and manage it from their own smartphones.

Professional athletes live with the knowledge that a serious injury could occur at any moment. Beyond the physical repercussions, these apparent twists of fate can damage successful careers, affect team members or clubs, and have a lasting impact economically and psychologically.

Part of the solution to the ever-present threat of injuries lies in no longer treating them as bad luck, claim researchers. Instead, athletes and their trainers or managers can use new technology to help predict when they might occur.

Using the IoT, researchers at the University of Tennessee Chattanooga have developed a framework to predict and help reduce the risk of injury.

Their research is set out in Mitigating sports injury risks using Internet of Things and analytic approaches, a paper published in the journal Risk Analysis. It explains how screening procedures can help predict the likelihood of an injury using wireless devices and cloud analytics.

Read more: Pyeongchang Winter Olympics to be defended by drone-catching drones

Creating a dashboard for injury risk

Sports injury management, even at a professional level, will always rely on some form of subjective assessment. That might come from the athlete in question, who’s determined to run or play in the next game, despite the pain. Or it might come from a doctor who has to interpret that information and make a split-second decision, while facing commercial or personal pressures.

However, the University of Tennessee Chattanooga researchers have done their best to remove this element from the screening process – or at least to provide as much objective data as possible to minimise the risk.

This greater objectivity is added by combining the athlete’s previous injury history with the results of a number of standardised screening tests. The result is a real-time dashboard providing details of each individual athlete’s status.

Read more: British Athletics deploys digital pace-makers for Rio Olympics

Data, screening, and predictive analytics

The research project was developed in real-world conditions with a team of American footballers.

A month before the players got together for preseason training, information on their previous injuries was collected using a Sport Fitness Index (SFI) survey. Each player then took a Unilateral Forefoot Squat (UFS) test, which assessed their ability to synchronise muscle responses in their legs while holding an upright position.

The researchers used accelerometers built into their smartphones to measure the results. The collected data was then integrated with the athletes’ self-reports of previous injuries and with longitudinal tracking of exposure to game conditions.

In their analysis of the data, the researchers found the ‘red zone’: athletes who played at least eight games were over three times more likely to suffer an injury than those who played fewer than eight games. Of those athletes who exhibited at least one risk factor, 42 percent then sustained an injury.

“Assigning all athletes to a single type of training program, without consideration of an individual’s unique risk profile, may fail to produce a substantial decrease in injury likelihood,” wrote Gary Wilkerson, lead author of the study.

“The results also provide a useful estimation of the odds of injury occurrence for each athlete during the subsequent season.”

Internet of Business says

Moving forward, Wilkerson and his team predict that the prevalence of smartphones and other IoT devices will help to make these and similar screening tests more accessible to athletes at all levels.

Anybody participating in sport could then put all of their data together to identify their own personalised injury risk. A truly smart solution to a painful – and often costly – problem.

Read more: Philips expands healthtech portfolio with IoT, AI, cloud solutions

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Ericsson helps expand LTE and IoT in Saudi Arabia

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NEWSBYTE: Saudi telco looks to Ericsson to assist LTE network expansion in the kingdom.

Saudi Telecom has inked a deal with Ericsson to help in a major nationwide expansion of its 4G network in Saudi Arabia, including the deployment of LTE Advanced and NB-IoT.

The deal is part of the telco’s drive to overhaul mobile broadband for its customers and open up business opportunities in the IoT, as well as laying the groundwork for 5G.

The LTE Advanced expansion will include the deployment of Ericsson’s 5G-ready baseband hardware. LTE Advanced will be deployed in a new 700MHz band spectrum acquired by STC. It will increase STC network throughput in 4G/LTE by up to 50 percent for smartphones, said a statement from the two companies.

In addition to the ramped-up access speeds delivered by LTE Advanced, subscribers will benefit from extended coverage, much longer battery life, and the low-cost devices enabled by NB-IoT, it added.

Expanding IoT network

STC will also deploy NB-IoT across its expanded network to “drive and support enterprise IoT ecosystem innovation and business opportunities”, said the announcement. This includes smart city applications, such as metering, parking sensors, and connected cars.

Read more: TomTom brings connected car services to Kia and Hyundai

STC recently renewed and upgraded its managed services contract with Ericsson. In addition to existing network planning/optimisation, network operations, and telecom field services, the contract now includes field services efficiency, as well as first- and second-line support.

“By making digital transformation real and effective for STC through 4G expansion, we will enable their customers to enjoy enriched experiences, whether that means lightning-speed video and media access for subscribers, or IoT business innovation and opportunities for enterprises,”said Rafiah Ibrahim, head of market area Middle East and Africa, Ericsson.

“Our partnership with STC shows that 4G network evolution is already happening and paving the way for 5G.”

Internet of Business says

In the light of a raft of recent announcements from Western companies working in partnership with China, India, and elsewhere, it is good to see international partnerships extending to the MENA region too: yet more evidence that the IoT is a global movement.

Read more: Vodafone teams up with China Mobile to drive global IoT expansion

Read more: AI: $ 16 trillion GDP boost will mainly benefit China – PwC

Read more: South Korea most automated nation on earth, says report. The UK? Going nowhere

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