Here Are A Few Google Search Hacks To Make Your Life Easier…

Google search may very well be one of the most critically important inventions of all time. We don’t know about you, but we use it daily in our lives to answer all the questions we can’t, like “How spell bureaucracy?” or “How cook crystal meth?”

Over the years, Google has become so much more than just the world’s premiere search engine. It also offers its own suite of services to help you solve all of life’s questions. It’ll help you figure out math equations, learn new languages, and discover cool new places. For all intents and purposes, it’s a complete guide to our world.

But even if you’re the most seasoned Google pro out there, we’d be willing to bet pretty good coin you don’t know all the tricks.

Get a Random Fun Fact by Typing “Fun Facts” Into the Search Bar

Did you know the piano might be a string instrument? Or that the Powder Monkey is actually the name of a naval gun? Neither did we. As you can imagine, there are literally trillions of fun facts on Google. Type “Fun Facts” into the search bar for a completely random fun fact, and then click the “ASK ANOTHER QUESTION” button at the bottom for more facts. Keep it going until you’re the smartest dude at Quizzo for the rest of your life.

Find Your Flight Info Easily

Speaking of traveling, flying itself isn’t always the easiest task. However, if you’re signed in to Gmail and type “Flight Status” into the search bar, Google will display all of your flight information, including your confirmation number, terminal, and even your seat number.

Get Time in a Different Time Zone

From the streets of Tokyo to the hills and valleys of Napa, we want to leave footprints everywhere. As everyone knows, the least fun thing about traveling is adjusting to the time zones in other places. If you’re planning for your trip and want to figure out how far ahead or behind you’ll be, it’s as simple as typing “Time in [City].” Google will automatically return the time in that particular city without having to make you look through pages of information or do awkward math calculations.

Get a Customer Service Phone Number by Searching “Customer Service [Company Name]”

This one is about as basic as it gets, but it’s an invaluable tool if you need to get in contact with a company’s customer service department. Rather than have you Google the name of the company and then spend another half hour skimming through their website for their bust customer service contact, Google will display relevant information if you simply search “Customer Service [Company Name].” If they list it, Google will provide it without the hassle.

Graphing Calculator

When we were growing up, calculus was the bane of our existence. And spending the money on those old TI calculators didn’t help things, either. Well, for all you new-gen calc nerds and engineering students, Google search bar actually doubles as its very own graphing calculator. The coolest thing is there’s no secret to it. Just plug your equation into the search bar and watch Google give you the coordinates and draw the graph. Calc nerds rejoice!

Searching For Things “Near Me” (Or By a Certain Location)

This may or may not be a little creepy, but if you search for anything (restaurants, movie theaters, grocery stores, bars, etc.) with “near me,” Google will give results based on your current location. If you’re going to be traveling, or just want to see what there is to do in a certain city, you can do that, too. For instance, let’s say you’re traveling to Berlin and want to find the best tourist attractions in the city. Typing “Attractions Berlin” will allow Google to curate a special list of the top attractions for you to check out in Berlin.

Type “Flip Coin” to Bring up Google’s Coin Toss Simulator

We won’t say this is the most revolutionary thing Google has ever done, but it’s definitely the most revolutionary thing they’ve done for those Friday nights where you and your buddies can’t settle on one set of plans and also don’t know what loose change is. Need to decide whether to bet it all on black or red? Leave it up to Google fate. Need help picking the next bar? Problem solved. Steak or chicken? Google’s got you, fam. Just open up the search bar, type “Flip Coin,” and watch Google work its magic.

Track a Package Immediately

Keeping track of your packages before they hit your door can be a hassle. You used to have to find out whether they went out via USPS, UPS, or FedEx, and then go to the respective websites and enter in the tracking information. Now, all you have to do is copy the tracking number and paste it directly into a Google search. Google will automatically recognize the format of the number and spit your tracking information directly into the search results screen. How cool is that?

Calculate Your Tip With “Calculate Tip [$$$]”

Search the app store on your phone and you’ll find dozens—seriously dozens—of apps to help you figure out how much to tip your server or bartender. Rather than waste time (and space) on a silly app, just type in “Calculate Tip [Bill Total]” into the search bar. A screen pops up that’ll help you toggle the percentage. The coolest thing about it is that it’ll also split a bill for multiple people with the click of a button.

Get a Word’s Definition

This one is invaluable. If you ever want to know the definition of a word without having to go to or Merriam-Webster or, God forbid, a book, just search “Define [Term]” and Google will find and highlight the definition for you.

‘Smart’ Baby Monitors Are Making Parents Needlessly Paranoid

The smart technology found in our phones and other wearables may be great at finding us a nearby Thai restaurant, but not so much at accurately keeping watch over our infant children, say a group of pediatricians in this month’s Journal of the American Medical Association (JAMA).

Their editorial, published online Tuesday, argues that the recent trend of baby monitors that come with newfangled bells and whistles — smartphone integration, sensors built into baby clothing, and an advertised ability to detect complex measurements like a baby’s blood oxygen level — may sound impressive, but they actually provide little practical benefit. In many cases, they cause parents unneeded stress. And at worst, they may be falsely marketing their potential to prevent cases of sudden infant death syndrome (SIDS), the leading cause of death among infants less than a year old.

According to the authors, there are a few major problems with these smart baby monitors.

For one, there’s no scientific evidence that keeping tabs on a healthy baby’s vital signs through these health apps is useful in the first place. They can be notoriously inaccurate at detecting hypertension and other chronic health problems. And even famous wearables like the FitBit have gotten in legal hot water lately, with several class action lawsuits filed against the company last year by users who claim their watches couldn’t accurately track their heart rates or sleep patterns.

Secondly, even with 100 percent accuracy, they could still lead to false alarms. As one example, the authors point out that a perfectly fine baby’s blood oxygen level occasionally drops to levels below 80 percent of normal, without anything being wrong with them. If a smart baby monitor detected that drop though, that could lead to parents unnecessarily rushing their children to the hospital or otherwise drive them even crazier with worry.

You might think products like the Smart Sock monitor by Owlet Baby Care would be regulated by agencies like the Food and Drug Administration, but manufacturers have sidestepped this hurdle by saying their devices aren’t intended to diagnose, treat, or prevent disease. That hasn’t stopped companies from slyly implying they can in their direct advertisements to parents, however. And that side-shuffle has also allowed them to avoid proving their devices even work as intended.

While smart baby monitors shouldn’t be thrown out with the bathwater, particularly for children with chronic breathing problems, they need a lot more vetting and regulation before parents should give them a try, the authors concluded.

And maybe the times are changing sooner than expected — Owlet Baby Care announced earlier this week that they intend to seek FDA approval for a medical version of their Smart Sock.

How Automation is Going to Redefine What it Means to Work

On December 2nd, 1942, a team of scientists led by Enrico Fermi came back from lunch and watched as humanity created the first self-sustaining nuclear reaction inside a pile of bricks and wood underneath a football field at the University of Chicago. Known to history as Chicago Pile-1, it was celebrated in silence with a single bottle of Chianti, for those who were there understood exactly what it meant for humankind, without any need for words.

Now, something new has occurred that, again, quietly changed the world forever. Like a whispered word in a foreign language, it was quiet in that you may have heard it, but its full meaning may not have been comprehended. However, it’s vital we understand this new language, and what it’s increasingly telling us, for the ramifications are set to alter everything we take for granted about the way our globalized economy functions, and the ways in which we as humans exist within it.

The language is a new class of machine learning known as deep learning, and the “whispered word” was a computer’s use of it to seemingly out of nowhere defeat three-time European Go champion Fan Hui, not once but five times in a row without defeat. Many who read this news, considered that as impressive, but in no way comparable to a match against Lee Se-dol instead, who many consider to be one of the world’s best living Go players, if not the best. Imagining such a grand duel of man versus machine, China’s top Go player predicted that Lee would not lose a single game, and Lee himself confidently expected to possibly lose one at the most.

What actually ended up happening when they faced off? Lee went on to lose all but one of their match’s five games. An AI named AlphaGo is now a better Go player than any human and has been granted the “divine” rank of 9 dan. In other words, its level of play borders on godlike. Go has officially fallen to machines, just as Jeopardy did before it to Watson, and chess before that to Deep Blue.

“AlphaGo’s historic victory is a clear signal that we’ve gone from linear to parabolic.”

So, what is Go? Very simply, think of Go as Super Ultra Mega Chess. This may still sound like a small accomplishment, another feather in the cap of machines as they continue to prove themselves superior in the fun games we play, but it is no small accomplishment, and what’s happening is no game.

AlphaGo’s historic victory is a clear signal that we’ve gone from linear to parabolic. Advances in technology are now so visibly exponential in nature that we can expect to see a lot more milestones being crossed long before we would otherwise expect. These exponential advances, most notably in forms of artificial intelligence limited to specific tasks, we are entirely unprepared for as long as we continue to insist upon employment as our primary source of income.

Let the above chart sink in. Do not be fooled into thinking this conversation about the automation of labor is set in the future. It’s already here. Computer technology is already eating jobs and has been since 1990.


All work can be divided into four types: routine and nonroutine, cognitive and manual. Routine work is the same stuff day in and day out, while nonroutine work varies. Within these two varieties, is the work that requires mostly our brains (cognitive) and the work that requires mostly our bodies (manual). Where once all four types saw growth, the stuff that is routine stagnated back in 1990. This happened because routine labor is easiest for technology to shoulder. Rules can be written for work that doesn’t change, and that work can be better handled by machines.

Distressingly, it’s exactly routine work that once formed the basis of the American middle class. It’s routine manual work that Henry Ford transformed by paying people middle class wages to perform, and it’s routine cognitive work that once filled US office spaces. Such jobs are now increasingly unavailable, leaving only two kinds of jobs with rosy outlooks: jobs that require so little thought, we pay people little to do them, and jobs that require so much thought, we pay people well to do them.

If we can now imagine our economy as a plane with four engines, where it can still fly on only two of them as long as they both keep roaring, we can avoid concerning ourselves with crashing. But what happens when our two remaining engines also fail? That’s what the advancing fields of robotics and AI represent to those final two engines, because for the first time, we are successfully teaching machines to learn.


I’m a writer at heart, but my educational background happens to be in psychology and physics. I’m fascinated by both of them so my undergraduate focus ended up being in the physics of the human brain, otherwise known as cognitive neuroscience. I think once you start to look into how the human brain works, how our mass of interconnected neurons somehow results in what we describe as the mind, everything changes. At least it did for me.

As a quick primer in the way our brains function, they’re a giant network of interconnected cells. Some of these connections are short, and some are long. Some cells are only connected to one other, and some are connected to many. Electrical signals then pass through these connections, at various rates, and subsequent neural firings happen in turn. It’s all kind of like falling dominoes, but far faster, larger, and more complex. The result amazingly is us, and what we’ve been learning about how we work, we’ve now begun applying to the way machines work.

One of these applications is the creation of deep neural networks – kind of like pared-down virtual brains. They provide an avenue to machine learning that’s made incredible leaps that were previously thought to be much further down the road, if even possible at all. How? It’s not just the obvious growing capability of our computers and our expanding knowledge in the neurosciences, but the vastly growing expanse of our collective data, aka big data.


Big data isn’t just some buzzword. It’s information, and when it comes to information, we’re creating more and more of it every day. In fact we’re creating so much that a 2013 report by SINTEF estimated that 90% of all information in the world had been created in the prior two years. This incredible rate of data creation is even doubling every 1.5 years thanks to the Internet, where in 2015 every minute we were liking 4.2 million things on Facebook, uploading 300 hours of video to YouTube, and sending 350,000 tweets. Everything we do is generating data like never before, and lots of data is exactly what machines need in order to learn to learn. Why?

Imagine programming a computer to recognize a chair. You’d need to enter a ton of instructions, and the result would still be a program detecting chairs that aren’t, and not detecting chairs that are. So how did we learn to detect chairs? Our parents pointed at a chair and said, “chair.” Then we thought we had that whole chair thing all figured out, so we pointed at a table and said “chair”, which is when our parents told us that was “table.” This is called reinforcement learning. The label “chair” gets connected to every chair we see, such that certain neural pathways are weighted and others aren’t. For “chair” to fire in our brains, what we perceive has to be close enough to our previous chair encounters. Essentially, our lives are big data filtered through our brains.


The power of deep learning is that it’s a way of using massive amounts of data to get machines to operate more like we do without giving them explicit instructions. Instead of describing “chairness” to a computer, we instead just plug it into the Internet and feed it millions of pictures of chairs. It can then have a general idea of “chairness.” Next we test it with even more images. Where it’s wrong, we correct it, which further improves its “chairness” detection. Repetition of this process results in a computer that knows what a chair is when it sees it, for the most part as well as we can. The important difference though is that unlike us, it can then sort through millions of images within a matter of seconds.

This combination of deep learning and big data has resulted in astounding accomplishments just in the past year. Aside from the incredible accomplishment of AlphaGo, Google’s DeepMind AI learned how to read and comprehend what it read through hundreds of thousands of annotated news articles. DeepMind also taught itself to play dozens of Atari 2600 video games better than humans, just by looking at the screen and its score, and playing games repeatedly. An AI named Giraffe taught itself how to play chess in a similar manner using a dataset of 175 million chess positions, attaining International Master level status in just 72 hours by repeatedly playing itself. In 2015, an AI even passed a visual Turing test by learning to learn in a way that enabled it to be shown an unknown character in a fictional alphabet, then instantly reproduce that letter in a way that was entirely indistinguishable from a human given the same task. These are all major milestones in AI.

However, despite all these milestones, when asked to estimate when a computer would defeat a prominent Go player, the answer even just months prior to the announcement by Google of AlphaGo’s victory, was by experts essentially, “Maybe in another ten years.” A decade was considered a fair guess because Go is a game so complex I’ll just let Ken Jennings of Jeopardy fame, another former champion human defeated by AI, describe it:

Go is famously a more complex game than chess, with its larger board, longer games, and many more pieces. Google’s DeepMind artificial intelligence team likes to say that there are more possible Go boards than atoms in the known universe, but that vastly understates the computational problem. There are about 10¹⁷⁰ board positions in Go, and only 10⁸⁰ atoms in the universe. That means that if there were as many parallel universes as there are atoms in our universe (!), then the total number of atoms in all those universes combined would be close to the possibilities on a single Go board.

Such confounding complexity makes impossible any brute-force approach to scan every possible move to determine the next best move. But deep neural networks get around that barrier in the same way our own minds do, by learning to estimate what feels like the best move. We do this through observation and practice, and so did AlphaGo, by analyzing millions of professional games and playing itself millions of times. So the answer to when the game of Go would fall to machines wasn’t even close to ten years. The correct answer ended up being, “Any time now.”


Any time now. That’s the new go-to response in the 21st century for any question involving something new machines can do better than humans, and we need to try to wrap our heads around it.

We need to recognize what it means for exponential technological change to be entering the labor market space for nonroutine jobs for the first time ever. Machines that can learn mean nothing humans do as a job is uniquely safe anymore. From hamburgers to healthcare, machines can be created to successfully perform such tasks with no need or less need for humans, and at lower costs than humans.

Amelia is just one AI out there currently being beta-tested in companies right now. Created by IPsoft over the past 16 years, she’s learned how to perform the work of call center employees. She can learn in seconds what takes us months, and she can do it in 20 languages. Because she’s able to learn, she’s able to do more over time. In one company putting her through the paces, she successfully handled one of every ten calls in the first week, and by the end of the second month, she could resolve six of ten calls. Because of this, it’s been estimated that she can put 250 million people out of a job, worldwide.

Viv is an AI coming soon from the creators of Siri who’ll be our own personal assistant. She’ll perform tasks online for us, and even function as a Facebook News Feed on steroids by suggesting we consume the media she’ll know we’ll like best. In doing all of this for us, we’ll see far fewer ads, and that means the entire advertising industry — that industry the entire Internet is built upon — stands to be hugely disrupted.

A world with Amelia and Viv — and the countless other AI counterparts coming online soon — in combination with robots like Boston Dynamics’ next generation Atlas portends, is a world where machines can do all four types of jobs and that means serious societal reconsiderations. If a machine can do a job instead of a human, should any human be forced at the threat of destitution to perform that job? Should income itself remain coupled to employment, such that having a job is the only way to obtain income, when jobs for many are entirely unobtainable? If machines are performing an increasing percentage of our jobs for us, and not getting paid to do them, where does that money go instead? And what does it no longer buy? Is it even possible that many of the jobs we’re creating don’t need to exist at all, and only do because of the incomes they provide? These are questions we need to start asking, and fast.


Fortunately, people are beginning to ask these questions, and there’s an answer that’s building up momentum. The idea is to put machines to work for us, but empower ourselves to seek out the forms of remaining work we as humans find most valuable, by simply providing everyone a monthly paycheck independent of work. This paycheck would be granted to all citizens unconditionally, and its name is universal basic income. By adopting UBI, aside from immunizing against the negative effects of automation, we’d also be decreasing the risks inherent in entrepreneurship, and the sizes of bureaucracies necessary to boost incomes. It’s for these reasons, it has cross-partisan support, and is even now in the beginning stages of possible implementation in countries like Switzerland, Finland, the Netherlands, and Canada.

The future is a place of accelerating changes. It seems unwise to continue looking at the future as if it were the past, where just because new jobs have historically appeared, they always will. The WEF started 2016 off by estimating the creation by 2020 of 2 million new jobs alongside the elimination of 7 million. That’s a net loss, not a net gain of 5 million jobs. In a frequently cited paper, an Oxford study estimated the automation of about half of all existing jobs by 2033. Meanwhile self-driving vehicles, again thanks to machine learning, have the capability of drastically impacting all economies — especially the US economy as I wrote last year about automating truck driving — by eliminating millions of jobs within a short span of time.

And now even the White House, in a stunning report to Congress, has put the probability at 83 percent that a worker making less than $20 an hour in 2010 will eventually lose their job to a machine. Even workers making as much as $40 an hour face odds of 31 percent. To ignore odds like these is tantamount to our now laughable “duck and cover” strategies for avoiding nuclear blasts during the Cold War.

All of this is why it’s those most knowledgeable in the AI field who are now actively sounding the alarm for basic income. During a panel discussion at the end of 2015 at Singularity University, prominent data scientist Jeremy Howard asked “Do you want half of people to starve because they literally can’t add economic value, or not?” before going on to suggest, ”If the answer is not, then the smartest way to distribute the wealth is by implementing a universal basic income.”

Moshe Vardi expressed the same sentiment after speaking at the 2016 annual meeting of the American Association for the Advancement of Science about the emergence of intelligent machines, “we need to rethink the very basic structure of our economic system… we may have to consider instituting a basic income guarantee.”

Even Baidu’s chief scientist and founder of Google’s “Google Brain” deep learning project, Andrew Ng, during an onstage interview at this year’s Deep Learning Summit, expressed the shared notion that basic income must be “seriously considered” by governments, citing “a high chance that AI will create massive labor displacement.”

When those building the tools begin warning about the implications of their use, shouldn’t those wishing to use those tools listen with the utmost attention, especially when it’s the very livelihoods of millions of people at stake? If not then, what about when Nobel prize winning economists begin agreeing with them in increasing numbers?

No nation is yet ready for the changes ahead. High labor force non-participation leads to social instability, and a lack of consumers within consumer economies leads to economic instability. So let’s ask ourselves, what’s the purpose of the technologies we’re creating? What’s the purpose of a car that can drive for us, or artificial intelligence that can shoulder 60% of our workload? Is it to allow us to work more hours for even less pay? Or is it to enable us to choose how we work, and to decline any pay/hours we deem insufficient because we’re already earning the incomes that machines aren’t?

What’s the big lesson to learn, in a century when machines can learn?

I offer it’s that jobs are for machines, and life is for people.

Is Tech The Cause Of Insomnia, Or Can It Cure It?

For Shakespeare, it was the chief nourisher in life’s feast. For the Dalai Lama, the best meditation. And for the technology industry, it is the next frontier of innovation, with the global market for sleep tech products set to reach over $76 billion in 2019.

In light of this, CES organizers the Consumer Technology Association launched its debut Sleep Tech Marketplace at the show this January, in partnership with the National Sleep Foundation. “From sleep trackers and silent alarms, to bedroom lighting, white noise and even smart beds, sleep technologies are helping us take control of our nighttime routines and rejuvenate efficiently,” says Gary Shapiro, president and CEO of the CTA.

It’s interesting that Shapiro mentions “rejuvenate”, because there are several schools of thought about what rejuvenation actually goes on while we’re dozing. The latest research unveiled at the University of Freiburg seems to support the synaptic homeostasis hypothesis, which states that sleep is necessary for the brain to consolidate memories and prepare for the next day. For the first time, scientists were able to show that sleep resets the build-up of connections that takes place during waking hours in the human brain.

Our greater understanding of sleep as a biological mechanism is enabling a new generation of inventors to rethink the place of technology in our night cycles. In many ways, however, the surge of interest in sleep tech isn’t down to scientific progress, but our culture’s unhealthy approach to one of life’s pervading necessities.

Can technology prevent burnout?

Arianna Huffington, the co-founder and former editor-in-chief of The Huffington Post, left her eponymous news website last year to focus on her corporate wellness service, Thrive Global. Upon her departure, Huffington told staff that she had “become more and more passionate – okay, obsessed – with burnout and stress and how we can reduce their impact on our lives”.

In her latest book, The Sleep Revolution: Transforming Your Life, One Night at a Time, Huffington writes: “Death from overwork has its own word in Japanese (karoshi), in Chinese (guolaosi), and in Korean (gwarosa). No such word exists in English, but the casualties are all around us. […] Sleep deprivation has become an epidemic.”

When Huffington gave her now-viral TED Talk on sleep, she discussed how sleep deprivation one-upmanship has flourished in our modern business world. “For men, sleep deprivation has become a virility symbol,” she noted. Not only is this damaging to personal health, but it’s an unsustainable situation for the world’s leading companies and institutions to be in. So how to tackle this global sleep crisis?

Perhaps it should come as little surprise, but there’s an app for that. More specifically, Rythm, a neurotechnology company based in Paris and San Francisco, has created the world’s first active wearable to improve sleep quality. Designed to be worn while sleeping, Dreem is a headband that uses sound synchronized to your sleep cycles to improve the quality of your shuteye. To understand how this works, it’s important to realize that sleep is an active state. A single night’s sleep consists of multiple sleep cycles, with each cycle following a well-orchestrated sequence. Light sleep, then deep sleep, leading to REM (rapid eye movement), which is when most dreams occur.

But humans have been sleeping without the aid of technology for millennia – do we really need wearables to help? “You’re right in that we’ve been sleeping the same way for a very long time,” says Hugo Mercier, Rythm CEO and co-founder. “However, with technology rapidly changing every aspect of our lives, we believe that we can use its positive influence to [improve] quality of sleep too. We at Rythm believe that we need to get past traditional and inaccurate tech (activity trackers, sleep apps, etc) and push towards technology that is validated by hard science.”

Using bone-conduction technology that transmits sound without earplugs, the audio stimulation supplied by Dreem is designed to help the brain stay in deep sleep. Characterised by slow oscillations, deep sleep is crucial for brain energy restoration, memory consolidation, hormone balance, and delaying degeneration.

If you’re wondering how noise – not usually associated with a good night’s sleep – can aid in prolonging deep sleep, it might help to picture a swing. In the context of brain-activity patterns, the slow oscillations observed during deep sleep are like a swing on a windy day. The audio stimulation is supposed to be akin to the repeated pushes that help the swing oscillate regularly. Users can view their sleep brainwaves via the accompanying iOS app, and more importantly, track sleep history over time.

Counting sheep

Speaking of tracking sleep history, Hugh Langley, US editor of Wareable, recently took part in a self-conducted sleep study. “I wanted to see how much tech out there is actually helpful in going beyond just tracking to help us make improvements to our sleep,” explains Langley. “I don’t suffer from any severe sleep problems, but in the past I’ve been bad at sticking to bed times and making sure I’m getting consistently good night’s sleep. I also wanted to see if there were things I hadn’t picked up on that were negatively impacting my sleep.

“One thing I found – and one thing the doctor warned me of, actually – was that thinking too much about [sleep] actually started having the opposite effect I wanted it to. In one week in particular, I was fretting over data and devices so much, worrying about getting enough sleep, that I got a bit of sleep anxiety and struggled to fall asleep. Caring about sleep quality is important, but there’s such a thing as caring too much.”

Rajiv Pant, CTO of Thrive Global, also points out tech’s drawbacks in the bedroom: “Recent technology products, especially those with LED displays, have decreased both the duration and quality of sleep for most people. Scientific studies show that exposure to blue light emanating from screens decreases the production of melatonin, the hormone that helps control our sleep and wake cycles. At night, such light from devices disrupts the body’s biological clock, causing impairment of sleep.

“In addition to blue light, devices such as smartphones in the bedroom also disrupt sleep in many other ways, as they are the portal to our to-do lists and daily stresses. People stay up late web surfing or check their phones in the middle of the night, so sleep quality is impaired.”

However, Langley is keen to stress that for people who have trouble sleeping, some technology can be very helpful. “Some [products] I used monitored outside stimuli such as light and noise, and sometimes these things can mess with our sleep without us realizing,” reasons Langley. “For people who sleep fine, maybe they don’t need the tech – but who knows, [by using tech] they may still find ways to get a better night’s rest.”

Pant is more cautious, advising instead that “while new sleep technology can certainly help improve your sleep, they’re not a substitute for healthy sleep practices. It’s still essential to not keep screens in the bedroom, to exercise, and to reduce anxiety and stress.”

If burnout is modern epidemic then it is inevitably tangled – one way or another – with the screens and sensors that make up 21st-century life. There’s no clear-cut answer on whether rejuvenating wearables cancel out distraction machines, but one thing is for sure: with a third of us suffering from some form of insomnia during our lives, now is the time to wake up to the extent of the crisis – whether the solution lies in technology or not.

Style Girlfriend Sends Style Advice to Your Phone

For the last four years, Style Girlfriend has been a destination for guys looking for style advice from a woman’s POV. Hell, we’ve turned to them numerous times. Now, with the launch of their on-demand messaging service, they’re delivering personalized, real-time style advice right to your phone. Simply sign up here to receive a number you can text with your style-related queries. Need help finding quality jeans that won’t break the bank? Want some assistance pairing pieces? Want the thumbs up on the outfit you’re wearing? All of the help you need will be a text message away.

Felix Gray Computer Glasses Reduce the Pain of Staring at Screens

One look at a pair of Felix Gray glasses and we think you’ll agree that they’re gorgeous. But the frames made of premium Italian acetate also house lenses designed to make staring at a computer all day a lot less painful for you in the long run. Felix Gray Computer Glasses help combat sleep loss/disturbance, blurry vision, retina degeneration, eye fatigue, nearsightedness and dry eyes by filtering part of the blue light spectrum. Factor in the cool frame options and it’s easy to see why you’ll find Felix Gray Computer Glasses on faces all over the offices of companies like Spotify, Uber, LinkedIn and Barclays. It’s hard to limit time on the computer when it’s all but required for most jobs these days, but that doesn’t mean you shouldn’t be protected.


Remember Myspace? A New Hack of the Site May Still Affect You and Millions

Myspace announced a hacker has stolen username and password information from more 360 million accounts. The social network announced in a blog post that it found out about the hack before this past weekend. The hack reportedly stole Myspaceusers’ login data including email addresses, Myspace usernames, passwords, and secondary passwords. The information was reportedly made available on an “online hacker forum.”

According to LeakedSource, information was stolen from 360,213,024 accounts. However, those more likely to be affected by the hack are users with accounts created before June 2013. So, basically everyone.

“Email addresses, Myspace usernames, and Myspace passwords for the affected Myspace accounts created prior to June 11, 2013 on the old Myspace platform are at risk,” wrote Myspace in the blog post.

Myspace explained it doubled down on its security measures after June 2013: “The compromised data is related to the period before those measures were implemented. We are currently utilizing advanced protocols including double salted hashes (random data that is used as an additional input to a one-way function that “hashes” a password or passphrase) to store passwords. Myspace has taken additional security steps in light of the recent report.”

Myspace thinks a hacker known as “Peace” is responsible for the hack, as well as being responsible for recent hacks against Tumblr and LinkedIn.

The main concern is that users may be affected in places beyond their likely inactive Myspace accounts. That’s why Myspace is advising users who may have used the same username and or password information from their Myspace accounts elsewhere to change their account information.

Myspace is working with law enforcement to investigate the hack.

The social network, beside being a shrine to your teen days and your Myspaceangle selfies, once housed accounts from “Princess” Kim Kardashian and “tighty-whitey” wearing Tom Hardy.

Tired of Living in Pinellas? Teleport App Helps You Choose Which City You’d Be Happy Living In

Teleport, Inc is a free web app working to completely change the process of moving abroad. With their software, they allow you to browse basic details of over 100 cities around the world, virtually exploring the most optimal locations and helping to streamline the task of preparing (and executing) the actual move. Aiming to make “physically rearranging the human population” that much easier, Teleport is working towards a future of global free movement.

Asking a series of questions about budget, income, housing requirements and the like, Teleport operates similarly to an online dating site, but at the end of the questionnaire instead of potential mates, you get potential homes. Their data helps make the research for an upcoming relocation much more basic, refining choices down to the perfectly personalized preferences. Focusing on helping people and businesses connect around the world, the company seeks to create a diverse worldwide workforce.

Designed by some of the entrepreneurs behind the explosively successful Skype, the team is now working to encourage diversification of job opportunities and potential applicants, no matter what the geographic separation between the two is. As their company site explains, they “strive for a culture as fluid, diverse and borderless as the world [they’re] serving.”


Tech Companies Dominate Forbes’ ‘Most Valuable Brands’ List

Forbes released its Most Valuable Brands list Thursday, and once again tech companies are dominating. Out of the top 10 brands, tech companies held five slots with Apple, Google, and Microsoft comprising the top three in that order.

2016 marks only the sixth year Forbes has tallied the richest brands, but in that time Apple has never lost its number one position. This year, Forbes valued the company at $154.1 billion, nearly double second-place Google, which was valued at $82.5 billion. The leap from second to third isn’t quite as stark; Microsoft came in at $75.2 billion.

Here are the top ten:

  1. Apple
  2. Google
  3. Microsoft
  4. Coca-Cola
  5. Facebook
  6. Toyota
  7. IBM
  8. Disney
  9. McDonald’s
  10. GE

Even though tech companies like Apple and Microsoft might offer similar products, what Forbes‘ list reveals is the way brands affect sales. iPhones make up almost half of the smartphones sold in the U.S. “Brands get their value from how customers perceive them,” said David Reibstein, a professor of marketing at the University of Pennsylvania’s Wharton School. “What makes it valuable from a company perspective is that customers are willing to pay a higher price or are more likely to buy.”

Facebook and IBM also appeared in the top 10, with the former continuing to grow. Facebook rose 44 percent and is the fastest-growing brand for the second year in a row. As of 2016, the social media platform boasts 1.65 billion users. Explaining that growth, Reibstein said, “Facebook keeps innovating and adding more and more functionally and features.” It also helps that other companies use Facebook to build their own brands.

Samsung, Amazon, Cisco, Oracle, and Intel also appeared within the top 20 brands.

In order to settle upon their list of 100 brands, Forbes analyzes 200 global brands, all of which need to have a presence outside the U.S. They then tally each brand’s earnings over the past three years and look at their role by industry.

For now, tech seems unstoppable.

Social Media is Really Messing With Your Sleep

Instagram models and Snapchat gurus might want to proceed with caution. According to researchers from the University of Pittsburgh School of Medicine, frequent social media users probably aren’t sleeping too well.

The study, which was published digitally and will appear in the April issue of the academic journal Preventative Medicine, featured a subject pool of 1,788 American adults ranging from 19 to 32 years old who were asked about their social media activity. Researchers inquired about popular social media platforms including Facebook, YouTube, Twitter, Google Plus, Instagram, Snapchat, Reddit, Tumblr, Pinterest, Vine and LinkedIn, EurekAlert reports.

What they found was that individuals who checked their social media more frequently were three times as likely to suffer from sleep disturbance, and users who checked more often during the day were twice as likely to have troubled sleep compared to those who didn’t use it as much.

“This may indicate that frequency of social media visits is a better predictor of sleep difficulty than overall time spent on social media,” said Dr. Jessica C. Levenson, lead author and a postdoctoral researcher in Pitt’s Department of Psychiatry. “If this is the case, then interventions that counter obsessive ‘checking’ behavior may be most effective.”

In others words, it might be time to put down the phone and get some shut eye.