27 Ocak 2016 Çarşamba

Powerful Google tax opponent will urge UK to drop hostility to radical EU change

Multinationals would file single European tax return under plan proposed by EU tax commissioner to stamp out aggressive avoidance
If multinationals filed a single EU tax return, EU commissioner Pierre Moscovici believes, it would remove the temptation for them to divert income from one country to another. Photograph: Gareth Fuller/PA
Simon Bowers
@sbowers00
Wednesday 27 January 2016 17.39 GMT Last modified on Wednesday 27 January 2016 22.01 GMT
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One of the most powerful opponents of Google’s controversial tax structures, European tax commissioner Pierre Moscovici, is expected on Thursday to call on Britain and Ireland to drop their objections to radical tax reform across the EU.

Moscovici, who has previously advocated a Europe-wide “digital tax” on companies such as Google, now wants to tackle aggressive tax avoidance among multinationals by requiring them to file a single European tax return.


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He believes this reform – known as the common consolidated corporate tax base (CCCTB) – would remove the temptation for international firms to artificially divert income from one country to another. Member states, would still be free to set their own corporate tax rates.

Britain, however, is among a small band of countries fiercely opposed to the European commission’s plans, believing they would weaken the UK’s ability to tailor its tax system to attract jobs and investment from international businesses.

“The CCCTB [proposal] has been around a very long time,” Treasury minister David Gauke said last year. “It is a proposal still looking for a justification.”

Moscovici is due to give an update on other corporate tax reforms in Brussels on Thurday morning, but is expected to use the occasion to insist his CCCTB reforms are far from dead in the water – despite British opposition.

The former French finance minister has a long track record of challenging the tax affairs of internet companies – and Google in particular. Two years ago, he led calls for the G20 to create dedicated tax rules for digital companies, though his efforts were ultimately blocked by American pressure. He has also previously advocated a Europe-wide “digital tax” on internet companies that make money from consumers’ personal data.

France has consistently taken a tougher approach to aggressive tax planning by Google and other digital companies. In 2011, tax inspectors raided the search group’s Paris offices, and ever since have been challenging Google’s claims that its French sales can be legitimately booked in Ireland. French tax officials are said to be seeking £380m in back taxes.


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Google is next week expected to reveal that its controversial tax structures have boosted its offshore cash reserves to $43bn – up $4bn in 12 months.

Overnight on Tuesday, fellow US tech group Apple, which also uses controversial tax structures to pay less tax in Europe, revealed its offshore cash pile has now reached $200bn – largely held through companies in Ireland. Chief executive Tim Cook boasted Apple now had “the mother of all balance sheets”.

Earlier this month, Moscovici told MEPs that he wanted to make 2016 “the year of tax reform”, with CCCTB at the centre of his plans. “We have a serious problem with tax avoidance and lack of transparency. Too many people have looked the other way”, Moscovici said.

Since unveiling his reforms last summer, the European tax commissioner has been barraged with lobbying submissions. The majority have come from business trade bodies, law firms and multinationals, many based in the UK, Ireland and the Netherlands.
ut Moscovici insists widespread anger among voters at a string of tax scandals will play a vital role in winning round reluctant governments, often subject to lobbying from big business. He has described CCCTB as part of a [global] trend, drawing support from the pressure of public opinion.

Britain, meanwhile, has attempted to tackle Google’s tax avoidance in its own way. Chancellor George Osborne last year introduced a new tax on diverted profits, having promised to put a stop to technology companies such as Google going to what he called “extraordinary lengths to pay little or no tax” in the UK. Of those who used such structures, he said: “you abuse the trust of the British people”.


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But last week his crackdown pledge was left in tatters after Google confirmed it had struck a deal with HMRC that effectively allowed it to continue to route £4.6bn of UK sales via an Irish company that pays no tax in Britain. Google’s UK arm – which paid £21m in tax according to its latest accounts – will only be required to pay slightly more to HMRC under the settlement.

Critics have branded it a sweetheart deal, pointing out that the £130m in back taxes, which relates to a 10-year period, is tiny in comparison with the sums mounting up in Google’s coffers in Bermuda.

George Osborne has been vocal in supporting some initiatives on international tax reform, but has confused many tax experts by also slashing the UK tax rate – due to fall to 18% by 2020 – and introducing controversial tax breaks to attract multinationals to invest in Britain.

Google last year stalled its plans for a big new London headquarters in King’s Cross, London, insisting, according to reports, that the design proposals for a building – complete with a rooftop pool – to house 5,000 workers were “boring”. A new architect has since been hired, and fresh plans are now expected.

In 2011, Google increased its workforce in France by half and invested heavily in a new Paris head office near the Saint-Lazare train station amid public anger about its tax payments. One French senator accused the group of running its local business as a “charity”.

Google AI computer beats human champion of complex Go boardgame


Fan Hui, three-time champion of the east Asian board game, lost to DeepMind’s program AlphaGo in five straight games
 Fan Hui makes a move against AlphaGo in DeepMind’s HQ in King’s Cross. Photograph: Google DeepMind
Alex Hern
@alexhern
Wednesday 27 January 2016 18.15 GMT Last modified on Wednesday 27 January 2016 22.01 GMT
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When Gary Kasparov lost to chess computer Deep Blue in 1997, IBM marked a milestone in the history of artificial intelligence. On Wednesday, in a research paper released in Nature, Google earned its own position in the history books, with the announcement that its subsidiary DeepMind has built a system capable of beating the best human players in the world at the east Asian board game Go.

Go, a game that involves placing black or white tiles on a 19x19 board and trying to remove your opponents’, is far more difficult for a computer to master than a game such as chess.

DeepMind’s software, AlphaGo, successfully beat the three-time European Go champion Fan Hui 5–0 in a series of games at the company’s headquarters in King’s Cross last October. Dr Tanguy Chouard, a senior editor at Nature who attended the matches as part of the review process, described the victory as “really chilling to watch”.

“It was one of the most exciting moments of my career,” he added. “But with the usual mixed feelings … in the quiet room downstairs, one couldn’t help but root for the poor human being beaten.”

It’s the first such victory for a computer program, and it came a decade before anyone expected it. As recently as 2014, Rémi Coulom, developer of the previous leading Go game AI, Crazy Stone, had predicted that it would take 10 more years for a machine to win against a top-rated human player without a handicap.

AlphaGo beat all expectations by approaching the challenge in a completely different way from previous software. Building on techniques DeepMind had employed in other feats of artificial intelligence, such as its system that could learn to play retro video games, AlphaGo used what the company calls “Deep Learning” to build up its own understanding of the game. It could then pick the moves it thought most likely to win.
When teaching a computer to play a game, the simplest method is to tell it to rank every possible move over the course of the game, from best to worst, and then instruct it to always pick the best move. That sort of strategy works for trivial games such as draughts and noughts and crosses, which have both been “solved” by computers that have fully examined every board state and worked out a way to play to at least a draw, no matter what the other player does.
However, for complex games such as Chess, the simple approach fails. Chess is just too big: in each turn there are approximately 35 legal moves, and a game lasts for around 80 turns. Enumerating every board position becomes computationally impossible very quickly, which is why it took so many years for IBM’s team to work out a way to beat Kasparov.
Go is bigger still. The definition of easy to learn, hard to master, it essentially has just two rules governing the core play, which involves two players alternately placing black and white tiles on a 19x19 board. The stones must be placed with at least one empty space next to it, or part of a group of stones of the same colour with at least one empty space, and if they lose their “liberty”, they are removed from the board.
While a game of chess might have 35 legal moves each turn, a game of Go has around 250 (including 361 legal starting positions alone); where Chess games last around 80 turns, Go games last 150. If Google had tried to solve the game in the same way noughts and crosses was solved, it would have had to examine and rank an obscene amount of possible positions: in the ballpark of 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 of them.
That renders an exhaustive search impossible, and even a selective search, of the style used by Deep Blue to defeat Kasparov, tricky to run efficiently.
Adding to the woes of those trying to master Go is the fact that, unlike chess, it’s very difficult to look at the board and mathematically determine who is winning. In chess, a player with their queen will probably beat a player whose queen has been taken, and so on: it’s possible to assign values to those pieces, and come up with a running score that roughly ranks each player’s prospects. In Go, by contrast, counters are rarely removed from the board, and there’s no simple mathematical way to determine who is in the stronger position until the game is very far progressed.
So AlphaGo focused on a very different strategy. As David Silver, DeepMind’s co-lead researcher on the project, puts it: “AlphaGo looks ahead by playing out the rest of the game in its imagination, many times over.” The program involves two neural networks, software that mimics the structure of the human brain to aggregate very simple decisions into complex choices, running in parallel.
One, the policy network, was trained by observing millions of boards of Go uploaded to an online archive. Using those observations, it built up a predictive model of where it expected the next piece to be played, given knowledge of the board and all previous positions, that could accurately guess the next move of an expert player 57% of the time (compared to a previous record of 44.4% from other groups).
This “supervised learning” was then backed up by a bout of “reinforcement learning”: the network was set to play against itself, learning from its victories and losses as it carried out more than 1m individual games over the course of a day.
The policy network was capable of predicting the probability that any given move would be played as next, but the system also needed a second filter to help it select which of those moves was the best. That network, the “value network”, predicts the winner of the game given each particular board state.
Building AlphaGo isn’t just important as a feather in DeepMind’s cap. The company argues that perfecting deep learning techniques such as this are crucial for its future work. Demis Hassabis, DeepMind’s founder, says that “ultimately we want to apply these techniques in important real-world problems, from medical diagnostics to climate modelling”.
For now, the DeepMind team is focused on one final goal on the Go board: a match against Lee Se-dol, the world champion. Lee says that “regardless of the result, it will be a meaningful event in the baduk (the Korean name for Go) history. I heard Google DeepMind’s AI is surprisingly strong and getting stronger, but I am confident that I can win at least this time.”




Apple iPhone 8 – iOS 8 Introduction

Apple iPhone 8 : Every year new iOS arrives like this time the iOS 8 and new features comes up. Isn’t it too early to talk about it? iPhone 8, Apple has always comes with new and latest features which make the Apple iPhone Series very much attractive and among the Dream series of People. Apple has been an eye candy for any individual. Whenever Apple has a new invention then there is also a buzz from public for the same. Not too longer time passed when iPhone 6 and iPhone next version is hitting the market. Apple always surprise people with its scandals and keep the interest alive everywhere. Then be ready to embrace next iPhone that is iPhone 7. iOS is the foundation of iPhone, iPad and iPod touch.
    Apple iPhone 7
It comes with a collection of apps that let you do the everyday things, and the not-so-everyday things, in ways that are intuitive, simple and fun. So apps take full advantage of hardware features such as the dual-core processor, accelerated graphics, wireless antennas and more. Multitasking is a perfect example. iOS learns when you like to use your apps and updates the content in them at power-efficient times, like when your device is already in use and connected to Wi‑Fi. So the content in your favourite apps stays up to date without a major drain on your battery.
Because Apple makes both the hardware and the operating system for iPad, iPhone and iPod touch, everything is designed to work together. So apps take full advantage of hardware features such as the dual-core processor, accelerated graphics, wireless antennas and more. Multitasking is a perfect example. iOS learns when you like to use your apps and updates the content in them at power-efficient times, like when your device is already in use and connected to Wi‑Fi. So the content in your favourite apps stays up to date without a major drain on your battery.


iPhone 8 Features

The user interface is built around the device’s multi-touch screen, including a virtual keyboard. The iPhone has Wi-Fi and can connect to many cellular networks, including 1xRTT (represented by a 1x on the status bar) and GPRS (shown as GPRS on the status bar), EDGE (shown as a capital E on the status bar), UMTS and EV-DO (shown as 3G), a faster version of UMTS and 4G (shown as a 4G symbol on the status bar), and LTE (shown as LTE on the status bar). An iPhone can shoot video (though this was not a standard feature until the iPhone 3GS), take photos, play music, send and receive email, browse the web, send texts, GPS navigation, record notes, do mathematical calculations, and receive visual voicemail.
Technology has made quite some advancement in the past two decades and even wireless chargers have been discovered. So we cannot think of carrying those cables along with us always. However, we still do not get to see this feature in the latest iPhone. However, we are expecting this feature to be integrated in iPhone 8 in the course of the next two years.

Trapping solar energy to run various gadgets is in use for quite some time. Therefore, in the next generation iPhone 8 we might get to see solar batteries whereby charging the gadget will be far more easier and at the same time environment friendly. Retina tracking sensors is a latest technology that is already available in some of the flagship Android phones. However, we didn’t get to see this technology even in the latest version of the iPhone i.e. iPhone 6. iPhone lovers would definitely like to experience this hands free way of unlocking the phone and expect it to be integrated in iPhone 8. Since Apple products have been always known for their security features, we are pretty sure that this feature will be present in the next generation iPhones.

    Apple iPhone 6  
All together, the iPhone seems rather well positioned to do again in its second eight years what it did in its first: set the benchmark for mobile user experience and give Apple another head start on competition that seems increasingly incapable of independent innovation.


Apple iPhone 8 Specifications

iPhone 8 Concept Design – Designers have been emulating depth for years in an effort to afford users more navigational context. This is why iOS apps have zoomed in and out since the first generation; it’s why iOS 7 brought translucency to Notification Center. Depth gives users a sense of order and helps prevent them from getting lost. Apple usually launches one flagship phone every year. If Apple keeps on following this tradition, then we can expect iPhone 8 to be released in the year 2016. However, just in case Apple makes in change in plan, then we might get to see this phone next year as well.

iPhone 8 Price
And as far as the price of the product is concerned, we can expect it to be around “Apple iPhone 8 Price in USA is $1150″ Apple iPhone 8 Price in India is Rs.70000″. But it is too early to make any concrete statement right now. The display size is increasing per iPhone series. So what to expect ? iPhone 6 is already here with the display of 5.5 inches and 4.7 inches. So iPhone 7 is expected to come with a 6 Inches display at max and the same would be with the Apple iPhone 8 we think so. Because if the size gets increased even from 6 Inches it would be falling into the tablet category and not in the phone category.If we talk about the RAM of the device “Apple iPhone 8” it would be 8 GB and the device would be very powerful after being powered with 8 GB RAM. Apple iPhone 8 is expected to come in different variants as per the previous launches and it will be 64 GB Variant, 128 GB Variant but the glam will be 256 GB Variant.iPhone 8 will be giving the same of 18 Hrs of usage on 4G.



24 Ocak 2016 Pazar

A future of self-driving cars? We're ready now

Growing up in the 1980s, I got my driver's license at age 17 -- and I was just about the last one of my friends to do so. It was stressful, but after I passed the test I got an exultant feeling of liberation.

But for many young people today, that's a rite of passage they'll never go through. Or even care about.

A study that the University of Michigan's Transportation Research Institute published this week shows that young people are less likely to have a driver's license. "There was a continuous decrease in the percentage of persons with a driver's license" for people in the US age 16 to 44 from 1983 to 2014, study authors Michael Sivak and Brandon Schoettle said. Among 18-year-olds, the percentage with a driver's license dropped from 80 percent to 60 percent, and for 20- to 24-year-olds, from 92 to 77 percent.
The numbers suggest that although self-driving cars represent the transportation of tomorrow, people are ready for the technology today. And that they're more open to car-hailing startups like Uber, Lyft and BlaBlaCar, part of a broader shift in how we consider getting around.

"What we're seeing is a group of millennials who don't want to be behind the wheel," said Richard Wallace, director of transportation systems analysis at the Center for Automotive Research.

After all, who wants to worry about insurance, oil changes or parking?

But it's not just young people who are changing. From 1983 to 2014, people at the older end of the spectrum got driver's licenses more often -- a rise from 55 percent to 79 percent for people 70 or older. That shows a desire to get around. But as people get older and their reflexes and vision worsen, self-driving cars could fulfill that demand.

Anybody can appreciate how self-driving cars have the potential to take the hassle out of traffic, letting people rest or get work done or watch videos on phones. But improved safety is a prime selling point for self-driving cars, too. One University of Michigan expert predicts crash rates will drop by 90 percent.

In rural areas of Kansas or Iowa, knowing how to drive a car will remain an essential skill. But younger people these days are happier with an urban life. According to the US Census Bureau, the country's urban population increased 14 percent -- 24 million people -- between 2000 and 2013.

There are also cultural reasons younger people aren't so enamored with cars, Wallace said. Gadgets carry cachet that cars have lost, with people plopping phones on the table at meetings instead of showing off Detroit's latest in their suburban driveways.

"The car was the cutting-edge technology of its day. For the postwar generation, going through the 1970s, there was nothing else out there you could own that had the technological sophistication," Wallace said. "Now it's smartphones and maybe Oculus virtual reality. The Internet superhighway is much more the Route 66 of the current generation."