But before you set your torch ablaze delete Facebook, let’s take a beat. Is the platform really a toxic monster? Or perhaps more of a misunderstood beneficial beast?
Let’s ask science.
Last month, The Journal of Social Psychologypublished a study exploring the relationship between Facebook and stress. Using 138 active Facebook users as their guinea pigs, researchers from the University of Queensland found that taking a five-day break from the platform lowered levels of the stress hormone cortisol.
“[W]hile participants in our study showed an improvement in physiological stress by giving up Facebook, they also reported lower feelings of well-being,” lead researcher Eric Vanman said in a press release. “People said they felt more unsatisfied with their life and were looking forward to resuming their Facebook activity.”
And those lower cortisol levels? Participants didn’t even notice, reporting that they felt just as stressed as they did before quitting Facebook temporarily.
In some instances, using Facebook can actually help you cope with stress.
That’s according to a study the journal Computers in Human Behavior published in May 2017. Northwestern University researcher Renwen Zhang surveyed 560 Facebook-using university students, focusing on their use of Facebook to disclose information about stressful events in their lives.
Zhang concluded that opening up on Facebook helped the students mentally cope with stressful situations. When the students shared information, they were likely to get support from their Facebook friends in the form of encouragement, advice, or offers of help. This, in turn, made them feel supported, more satisfied with life, and less depressed.
Quitting Facebook means saying goodbye to all those digital hugs that can help you get through your latest breakup or crappy day at work.
When you’ve got leverage, don’t be afraid to use it. That’s been Google’s modus operandi in the news and publishing world over the last year or so as it has pushed its AMP platform, funding various news-related ventures that may put it ahead, and nourished its personalized Chrome tabs on mobile. The latter, as Nieman Labs notes, grew 2,100 percent in 2017.
You may have noticed, since Chrome is a popular mobile browser and this setting is on by default, but the “Articles for You” appear automatically in every new tab, showing you a bunch of articles the company things you’d like. And it’s gone from driving 15 million article views to a staggering 341 million over the last year.
In late 2016, when Google announced the product, I described it as “polluting” the otherwise useful new tab page. I also don’t like the idea of being served news when I’m not actively looking for it — I understand that when I visit Google News (and I do) that my browser history (among other things) is being scoured to determine what categories and stories I’ll see. I also understand that everything I do on the site, as on every Google site, is being entered into its great data engine in order to improve its profile of me.
Like I said, when I visit a Google site, I expect that. But a browser is supposed to be a tool, not a private platform, and the idea that every tab I open is another data point and another opportunity for Google to foist its algorithms on me is rankling.
It has unsavory forebears. Remember Internet Explorer 6, which came with MSN.com as the default homepage? That incredible positioning drove so much traffic that for years after (and indeed, today) it drove disgusting amounts of traffic to anything it featured. But that traffic was tainted: you knew that firehose was in great part clicks from senior citizens who thought MSN was the entire internet.
Of course the generated pages for individual users aren’t the concentrated fire of a link on a major portal, but they are subject to Google approval and, of course, the requisite ranking bonus for AMP content. Can’t forget that!
But wherever you see the news first, that’s your news provider. And you can’t get much earlier than “as soon as you open a new tab.” That’s pretty much the ultimate positioning advantage.
Just how this amazing growth occurred is unclear. If there’s been any word of mouth, I missed it. “Have you tried scrolling down? The news is just right there!” It seems unlikely. My guess would be that the feature has been steadily rolling out in new regions, opting in new users who occasionally scroll down and see these stories.
And unlike many other news distribution platforms, there isn’t much for publishers or sites like this one to learn about it. How are stories qualified for inclusion? Is there overlap with Google News stuff? What’s shown if people aren’t signed in? I’ve asked Google for further info.
Do you, like me, dislike the idea that every time you open a tab — not just when you use its services — Google uses it as an opportunity to monetize you, however indirectly? Fortunately, and I may say consistent with Google’s user-friendliness in this type of thing, you can turn it off quite easily — on iOS, anyway.
Open the menu at the top right of any tab and hit settings. There should be a “Suggested articles” toggle — disable that and you’re done. While you’re at it, you might just head into Privacy and disable search and site suggestions and usage data.
The analysis, which was not limited to studies conducted in the U.S. and Canada, showed that GMO corn varieties have increased crop yields worldwide 5.6 to 24.5 percent when compared to non-GMO varieties. They also found that GM corn crops had significantly fewer (up to 36.5 percent less, depending on the species) mycotoxins — toxic chemical byproducts of crop colonization.
Some have argued that GMOs in the U.S. and Canada haven’t increased crop yields and could threaten human health; this sweeping analysis proved just the opposite.
For this study, published in the journal Scientific Reports, a group of Italian researchers took over 6,000 peer-reviewed studies from the past 21 years and performed what is known as a “meta-analysis,” a cumulative analysis that draws from hundreds or thousands of credible studies. This type of study allows researchers to draw conclusions that are more expansive and more robust than what could be taken from a single study.
There have been, for a variety of largely unscientific reasons, serious concern surrounding the effects of GMOs on human health. This analysis confirms that not only do GMOs pose no risk to human health, but also that they actually could have a substantive positive impact on it.
Mycotoxins, chemicals produced by fungi, are both toxic and carcinogenic to humans and animals. A significant percentage of non-GM and organic corn contain small amounts of mycotoxins. These chemicals are often removed by cleaning in developing countries, but the risk still exists.
GM corn has substantially fewer mycotoxins because the plants are modified to experience less crop damage from insects. Insects weaken a plant’s immune system and make it more susceptible to developing the fungi that produce mycotoxins.
In their analysis, the researchers stated that this study allows us “to draw unequivocal conclusions, helping to increase public confidence in food produced with genetically modified plants.”
While there will likely still be questions raised as GMOs are incorporated into agriculture, this analysis puts some severe concerns to rest. Additionally, this information might convince farmers and companies to consider the potential health and financial benefits of using genetically modified corn. Some are already calling this meta-analysis the “final chapter” in the GMO debate.
I know January is supposed to be the month where everyone is understandably broke because of Christmas and the New Year, but we’re now deep within February and my bank account does not look any friendlier. To be fair, a lot of it is self-afflicted, as there have just been so many fantastic gaming releases on every platform in the few weeks of 2018 we’ve had so far. If you’re similarly spent, but also are keen to fill up that backlog with even more essential iOS titles, you’re in luck – some seminal App Store classics have been heavily reduced in price over the past few days. If you’re missing any of these games from your collection, you truly have no excuse now.
You Must Build A Boat, $ 0.99 Kicking off our sales round-up is the phenomenal puzzler You Must Build A Boat from Luca Redwood of EightyEight Games fame. There’s very little I need to say about this excellent title, as it has received numerous accolades at TouchArcade since its release in 2015, including an emphatic five star review and our coveted Game of the Week award. In my opinion, this is one of the best match-3/puzzle games on the platform, and in many ways You Must Build A Boat feels like the sequel to Dungeon Raid that we never got – which is even more pertinent considering the latter game’s demise at the hands of iOS 11. This puzzle RPG title is full of content and irreverent charm, and at a bargain price of $ 0.99 (down from $ 2.99 for only the second time in three years), it really is essential for any iOS gaming fan.
10000000, $ 0.99 Read the above paragraph and replace You Must Build A Boat with 10000000, and you know my thoughts on this landmark iOS release. Seriously though, while the former title may be a spiritual sequel to this game, 10000000 is an incredible game in its own right, and is truly iconic in the illustrious history of the App Store. Dropping quite literally out of nowhere in 2012, 10000000 was our Game of the Year runner-up at the time, and its hopelessly compulsive gameplay loop of hitting the dungeons, solving puzzles, upgrading your skills and repeating it all for hours was perfection. 10000000 hasn’t been on sale since 2014, so even though it’s more than worth its normal $ 2.99 cost of entry, this is another must-have for anyone with a passing interest in puzzle games.
MONSTER HUNTER FREEDOM UNITE for iOS, $ 3.99 While finding the iTunes link for Monster Hunter Freedom Unite, I stumbled upon an App Store review that stated “At only $ 15?! Such a freaking great deal”. This sums up why Capcom’s latest promotion for its flagship beast-slaying series on iOS is an absolute bargain, as Monster Hunter Freedom Unite is on sale for only $ 3.99. It may be a bit old in the tooth now, despite its notoriety for not actually working on iOS for the longest time, but Monster Hunter Freedom Unite is still one of the best console-size experiences on the App Store to date. With the console version of Monster Hunter World dominating gaming headlines over the past few months, Freedom Unite is an excellent place to dive into the series in its classic portable guise.
Life Is Strange, $ 0.99Life is Strange has been somewhat of a revelation amongst console gamers since its 2015 debut, as the story of Max and her devastating attempts to change the future through a gift of being able to rewind time. While we noted minor performance and control niggles in our review, this is the game episodic console classic in arguably its most intuitive form yet, and $ 0.99 for the first episode is a great price to try the series out for anyone on the fence. Life is Strange does require relatively recent iOS devices to run – and I really would only recommend it for those with powerhouses such as the iPad Pro – but this is really a title that needs to be experienced at least once by every gamer.
While these four titles are the highlights of the past week’s App Store promotions, I’ve undoubtedly missed a few classics from the list, and many essential releases are being discounted every day. Let us know which games you’ve picked up recently, or any sales you’ve managed to sniff out, on our Price Drops forum and Discord server.
“I have read and understood…” has got to be one of the biggest lies people commit on a regular basis. It’s the typical ending for the long-winded customer agreements or privacy policies attached to every online service, which few ever read. Or at least, not in their entirety.
When humankind finds something difficult, we typically build a gizmo to do it for us — and this case is no different. It turns out, reading lengthy fine-print is the expertise of a machine-learning artificial intelligence (AI) designed by researchers from the Federal Institute of Technology at Lausanne, Switzerland (EPFL), the University of Wisconsin, and the University of Michigan. Their research began with a question, said lead researcher Hamza Harkous from EPFL.
“What if we visualize what’s in the policy for the user?” Harkous said in an interview with WIRED. “Not to give every piece of the policy, but just the interesting stuff.”
A bit of a fine print here, though. Even with a powerful tool like Polisis, the barest minimum effort is still required from the human user. In other words, a policy summary is not helpful if you don’t actually bother to read it. The AI can help, but human users have to help themselves first.
You can decided for yourself whether the music your friends play on your HomePod through AirPlay will affect Apple Music’s “For You” section in the Music app on iPhone and iPad…. Read the rest of this post here
YouTube today announced plans to combat state-sponsored content and conspiracy theories. The platform plans to label all state-funded broadcasters and conspiracy theorists, a move to add much-needed context to the types of channels often responsible for the spread of misinformation. Often overlooked, YouTube offers yet another platform for the spread of misinformation. While Facebook and Twitter grab headlines, state-sponsored actors (like RT) and internet wack jobs like Alex Jones continue facilitating the spread of news stories ranging from misleading to patently false. YouTube Chief Product Officer Neal Mohan confirmed the problem in an interview with The Wall Street Journal, although…
The science and tech world has been abuzz about quantum computers for years, but the devices are not yet affecting our daily lives. Quantum systems could seamlessly encrypt data, help us make sense of the huge amount of data we’ve already collected, and solve complex problems that even the most powerful supercomputers cannot – such as medical diagnostics and weather prediction.
That nebulous quantum future became one step closer this November, when top-tier journal Naturepublishedtwo papers that showed some of the most advanced quantum systems yet.
If you still don’t understand what a quantum computer is, what it does, or what it could do for you, never fear. Futurism recently spoke with Mikhail Lukin, a physics professor at Harvard University and the senior author of one of those papers, about the current state of quantum computing, when we might have quantum technology on our phones or our desks, and what it will take for that to happen.
This interview has been slightly edited for clarity and brevity.
Futurism:First, can you give me a simple explanation for how quantum computing works?
Mikhail Lukin: Let’s start with how classical computers work. In classical computers, you formulate any problem you want to solve in the form of some input, which is basically a stream of 0s and 1s. When you want to do some calculation, you basically create a certain set of rules depending on how this stream should actually move. That’s the process of calculation — addition, multiplication, whatever.
But we’ve known for more than 100 years that our microscopic world is fundamentally quantum mechanical. And in quantum mechanics, you can have systems. Your computer, for instance, or your chair can be placed in two different states at once — that’s the idea of quantum superpositions. In other words, your computer can be simultaneously both in Boston and in New York. So this quantum superposition, even though it sounds very weird, is allowed by the laws of quantum mechanics. On a large scale, like the example that I gave, it is clearly very strange. But in the microscopic world, like with a single atom, creating this kind of superposition state is actually quite common. So by doing these scientific experiments, scientists proved that a single atom is in two different states at once.
The idea of quantum computers is to basically make use of these rules of quantum mechanics to process information. It’s pretty easy to understand how this can be so powerful. In classical computers, you give me a certain input, I put it in my computer, I give you an output. But if our hardware was quantum mechanical, rather than just sequentially providing some input and reading out the answers, I could prepare the computer register in the quantum superpositions of many different kind of inputs.
This means that if I then take this superposition state and process it using the laws of quantum mechanics, I can process many, many inputs at once. It could be potentially an exponential speedup, compared to the classical programs.
F:What does a quantum computer look like?
ML: If you were to walk into a room with our quantum machine in it you would see a vacuum cell or tube and a bunch of lasers which shine into it. Inside we have a very low density of a certain atom. We use lasers to slow down the atomic motion very close to absolute zero, which is called laser cooling.
F:So how do you program the thing?
ML:. To program a quantum computer, we shine a hundred tightly-focused laser beams into this vacuum chamber. Each of these laser beams acts as a optical tweezer, grabbing one atom or not. We have these atom traps, each of which is either loaded or empty. We then take a picture of these atoms in these traps, and we figure out which traps are full and which are empty. Then we rearrange the trap containing single atoms in any pattern that we wish. This desired arrangement of single atoms, each individually held in and easily controlled, are positioned basically at will.
Positioning these atoms is one way that we can program it. To actually control the qubit, we gently, carefully, push the atoms from their lowest energy state into a higher energy state. We do this with carefully chosen laser beams that shoot to one specific transition. Their frequency is very tightly controlled. In this excited state the atom actually becomes very big and, because of this atom size, the atoms start interacting or – in other words – talking to each other. By choosing the state to which we excite the atoms and choosing their arrangements and positions, we can then program the interaction in a highly controllable way.
F:What kinds of applications would a quantum computer be most useful for?
ML: To be honest, we really don’t know the answer. It’s generally believed that quantum computers will not necessarily help for all computational tasks. But there are problems that are mathematically hard for even the best classical computers. They usually involve some complex problems, such as problems involving complex optimizations in which you try to satisfy a number of contradictory constraints.
Suppose you want to give some kind of collective present to a group of people, each of which has its own niche. Some of the niches might be contradictory. So what happens is, if you solve this problem classically, you have to check each pair or triplet of people to make sure that at least their niche is satisfied. The complexity of this problem grows in size very, very rapidly because the number of classical combinations you need to check is exponential. There is some belief that for some of these problems, quantum computers can offer some advantage.
Another very well-known example is factoring. If you have a small number, like 15, it’s clear that the factors are 3 and 5, but this is the kind of problem that very quickly becomes complicated as the number grows. If you have a large number that is a product of two large factors, classically there is pretty much no better way to find what these factors are than just trying numbers from one, two, three, and so on. But it turns out that a quantum algorithm exists, called Shor’s algorithm, that can find the factors exponentially faster than the best known classical algorithms. If you can do something exponentially faster than using the alternative approach, then it’s a big gain.
F:It sounds like your mission, and that of others in your field, is to help us advance and understand this technology, but the applications are sort of secondary and will come when you have the tools. Does that seem about right?
ML: I will answer your question with an analogy. When classical computers were first developed, they were mostly used to do scientific calculations, numerical experiments to understand how complex physical systems behave. Right now, quantum machines are at this stage of development. They already allow us to study complex quantum physical phenomena. They are useful for scientific purposes, and scientists are already doing it now.
In fact, one significance of our papers [published in Nature] is that we have already built machines, which are large enough, and complex enough, and quantum enough to do scientific experiments that are very difficult to impossible to do on even the best possible classical computers — essentially supercomputers. In our work, we already used our machine to make a scientific discovery, which had not been made up until now in part because it’s very difficult for classical computers to model these systems. In some ways, we are now crossing the threshold where quantum machines are becoming useful, at least for scientific purposes.
When classical computers were being developed, people had some ideas of which algorithms to run on them. But actually it turned out that when the first computers were built, people were able to start experimenting with them and discovered many more practically efficient, useful algorithms. In other words, that’s really when they discovered what these computers can actually be good for.
That’s why I’m saying that we really don’t know now the tasks for which quantum computers will be particularly useful. The only way to find these tasks is to build large, functional, quantum machines to try these things out. That’s an important goal, and I should say that we are entering this phase now. We’re very, very close to a stage when we can start experimenting with quantum algorithms on large scale machines
F:Tell me a little bit about your Nature paper. What actually is the advance here? And how close are we to being able to start discovering the algorithms that could work on quantum computers?
ML: So first let’s talk about how one could quantify quantum machines. It can be done along three different axes. On one axis is the scale — how many qubits [a “quantum bit,” the unit that makes up the basis of quantum computer the way “bits” do in classical computing] it is. More is better. Another axis is the degree of quantum-ness, that is, how coherent these systems are. So eventually, the way to quantify it is that if you have a certain number of qubits, and you perform some calculations with that, what’s the probability that this calculation is error-free?
If you have a single qubit, you have a small chance to make an error. Once you have a lot of them, this probability is exponentially higher. So the systems described in our paper, and also in the complementary paper, have large enough qubits and are coherent enough so that we can basically do the entire series of computations with fairly low error probability. In other words, in a finite number of tries, we can have a result that has no errors.
But this is still not the complete story. The third axis is how well you can program this machine. Basically if you can make each qubit talk with any other qubit in an arbitrary fashion, you can also encode any quantum problem into this machine. Such machines are sometimes called universal quantum computers. Our machine is not fully universal, but we demonstrate a very high degree of programmability. We can actually change the connectivity very quickly. This in the end, is what allows us to probe and to make new discoveries about these complex quantum phenomena.
F:Could a quantum computer be scaled down to the size of a phone, or something vaguely portable at some point?
ML: That is not out of the question. There are ways to package it so that it can actually become portable and potentially can be miniaturized enough maybe not to the point of a mobile phone, but perhaps a desktop computer. But that cannot be done right now.
F:Do you think, like classical computers, quantum computers will make the shift from just scientific discoveries to the average user in about 30 years?
ML: The answer is yes, but why 30 years? It could happen much sooner.
F:What has to happen between now and then? What kind of advances need to be made to get us there?
ML: I think we need to have big enough computers to start really figuring out what they can be used for. We don’t know yet what quantum computers are capable of doing, so we don’t know their full potential. I think the next challenge is to do that.
The next stage will be for engineering and creating machines that could be used maybe to target some specialized applications. People, including [my team], are already working on developing some smallscale quantum devices, which are designed to, for example, aide in medical diagnostics. In some of these applications, quantum systems just measure tiny electric or magnetic fields, which could allow you to do diagnostics more efficiently. I think these things are already coming, and some of these ideas are already being commercialized.
Then maybe, some more general applications could be commercialized. In practice quantum computers and classical computers will likely work hand-in-hand. In fact, most likely what would happen is that the majority of the work is done by classical computers, but some elements, the most difficult problems, can be solved by quantum machines.
There is also another field called quantum communication where you can basically transfer quantum states between distant stations. If you use quantum states to send information, you can build communication lines that are completely secure. Moreover, through these so-called quantum networks, sometimes called quantum internet, we should be able to access quantum servers remotely. That way, I can certainly imagine many directions in which quantum computers can enter everyday life, even though you don’t carry it in your own pocket.
F:What’s something that you wish more people knew about quantum computers?
ML: Quantum computing and quantum technology have been in the news for some time. We scientists know that it’s an exciting area. It’s really the frontier of the scientific research across many subfields. Over the last five to 10 years, most people assumed that the developments have been very futuristic. They assumed that it will take a long time before we create any useful quantum machines.
I think that this is just not the case. I think we are already entering the new era with tremendous potential for scientific discoveries, which might have wideranging applications for material science, chemistry — really anything that involves complex physical systems. But I also feel that very soon we will start discovering what quantum computers can be useful for in a much broader scope, ranging from optimization to artificial intelligence and machine learning. I think these things are around the corner.
We don’t yet know what and how quantum computers will do it, but we will find out very soon.
A new “Recommended for You” is now rolling out to Instagram users. The section will suggest posts for you based on posts that’ve been liked by other accounts you follow. The section will be clearly labeled and will include three to five suggested posts.
You can temporarily hide the “Recommended for You” section by tapping the three-dot menu above the post and then selecting “Hide”.
Instagram did explain to TechCrunch that the “Recommended for You” section will only appear after you’ve viewed all the posts in your feed.
Many Instagram users were frustrated the last time that the service made a big change to their feeds, when it switched from a chronological view to an algorithmic one, and this “Recommended for You” section is likely to annoy some users, too. Since the feature can only be temporarily hidden, though, many users will just have to get used to seeing it in their feeds.