Creators of the popular game revealed this week that Minecraft has now been sold more than 100 million times – and a few copies have even made it to Antarctica. The figures combine sales from PC, console, and mobile versions of the game to create a user-base that'includes folks from every country and territory on the planet.' Creators of the popular game revealed this week that Minecraft has now been sold more than 100 million times – and a few copies have even made it to Antarctica. The figures combine sales from PC, console, and mobile versions of the game to create a user-base that'includes folks from every country and territory on the planet' Minecraft was created in 2009. At the start of the game, a player is put into a'virtually infinite game world.'

If you still think Minecraft is a PC game--well, you're flat wrong. According to new numbers released by Mojang and Microsoft, the original version for the PC is the least popular platform, in almost every region worldwide. Microsoft said Thursday that Minecraft has sold more than 106,859,714 copies to date across all platforms--which would represent the twelfth most populous nation in the world, right behind Japan. Four copies have even been sold into Antarctica. But if you dig into Microsoft's numbers, they reveal that far, far more users are buying Minecraft on platforms other than the PC.

Okay, so Minecraft was already kinda-sorta the second-bestselling game of all time if you don't count Wii Sports, which was a pack-in, and I'm loathe to count stuff you can't buy standalone. But yes, on the basis of conventional video game sales leaderboards, with over 100 million copies (106,859,714 to be precise) across PC, mobile and console in the pocket, Minecraft is now officially second only to that all-time, all-platforms, indefatigable puzzling juggernaut, Tetris. Tetris has something like half a billion on the books if the entrepreneurial math here is right. So there's probably no way Minecraft is going to beat that, probably ever. But consider the next-bestselling game (excluding Wii Sports) is Grand Theft Auto V, with an impressive but presumably now creeping 65 million copies.

SAN FRANCISCO -- Amazon's Jeff Bezos is a Star Trek-loving space geek, but unlike Elon Musk, he's got no plans on for heading to Mars. People haven't really thought this through," he said. Bezos spent 45 minutes in a convivial public conversation at the Washington Post's Transformers Conference in Washington D.C., which was also webcast live. He was interviewed by Martin Baron, executive editor of the Post, which he bought in 2013. After a few jokes about whether or not he'd have a job when the conversation was done, Baron asked Bezos about Amazon's Echo device and its cloud-based voice recognition agent Alexa. The Echo got more competition Wednesday in Mountain View, Calif. Amazon's CEO said the original inspiration for the Echo was the talking computers of Star Trek. While the Echo team is still quite a ways away from reaching that goal, he didn't feel too badly because after all, Star Trek was set more than 250 years in the future. "We still have a couple of centuries, but I don't think we'll need that much time," Bezos said. Bezos said he grew up playing pretend Star Trek every day with his friends when he was in fourth grade in Houston. "We would fight over who got to be Captain Kirk or Mr. Spock, and somebody played the computer too.

Two years ago, a lawyer in Indiana sent me a check for seventy-eight thousand dollars. The money was from my uncle Walt, who had died six months earlier. I hadn't been expecting any money from Walt, still less counting on it. So I thought I should earmark my inheritance for something special, to honor Walt's memory. It happened that my longtime girlfriend, a native Californian, had promised to join me on a big vacation. She'd been feeling grateful to me for understanding why she had to return full time to Santa Cruz and look after her mother, who was ninety-four and losing her short-term memory. She'd said to me, impulsively, "I will take a trip with you anywhere in the world you've always wanted to go." To this I'd replied, for reasons I'm at a loss to reconstruct, "Antarctica?" Her eyes widened in a way that I should have paid closer attention to. But a promise was a promise. Hoping to make Antarctica more palatable to my temperate Californian, I decided to spend Walt's money on the most deluxe of bookings--a three-week Lindblad National Geographic expedition to Antarctica, South Georgia island, and the Falklands. I paid a deposit, and the Californian and I proceeded to joke, uneasily, when the topic arose, about the nasty cold weather and the heaving South Polar seas to which she'd consented to subject herself. I kept reassuring her that as soon as she saw a penguin she'd be happy she'd made the trip. But when it came time to pay the balance, she asked if we might postpone by a year. Her mother's situation was unstable, and she was loath to put herself so irretrievably far from home. By this point, I, too, had developed a vague aversion to the trip, an inability to recall why I'd proposed Antarctica in the first place. The idea of "seeing it before it melts" was dismal and self-cancelling: why not just wait for it to melt and cross itself off the list of travel destinations? I was also put off by the seventh continent's status as a trophy, too remote and expensive for the common tourist to set foot on. It was true that there were extraordinary birds to be seen, not just penguins but oddities like the snowy sheathbill and the world's southernmost-breeding songbird, the South Georgia pipit. But the number of Antarctic species is fairly small, and I'd already reconciled myself to never seeing every bird species in the world. The best reason I could think of for going to Antarctica was that it was absolutely not the kind of thing the Californian and I did; we'd learned that our ideal getaway lasts three days.

Penguins living in the Antarctic Ocean are under threat from a variety of factors including climate change, fisheries and human disturbance. In spite of studying the region for over a hundred years, scientists have still not developed a way to measure changes in penguin populations. Now researchers have developed a new way to keep an eye on penguins, using 50 cameras and the help of the general public. Penguins living in the Antarctic Ocean are under threat from a variety of factors including climate change, fisheries and human disturbance. The Penguins Lifeline project at the University of Oxford has been running since 2009.

The Lost World: Jurassic Park 1997 AMC Sun. Tomorrow Never Dies 1997 EPIX Wed. 10 p.m., Thur. The X-Files: Fight the Future 1998 IFC Thur. Hard to Kill 1990 Sundance Mon. 8 p.m., Tue. A scientist gives his bodyguard superhuman powers in order to fight racists. A lawyer unwittingly becomes friends with an unstable woman who has a criminal history. A successful businesswoman puts her family, career and life on the line to satisfy her addiction to sex. With his father trapped in the wreckage of their spacecraft, a youth treks across Earth's now-hostile terrain to recover their rescue beacon and signal for help. In the future a cutting-edge android in the form of a boy embarks on a journey to discover his true nature. An 11-year-old boy experiences the worst day of his young life but soon learns that he's not alone when other members of his family encounter their own calamities. A struggling writer falls in love with a stenographer while trying to finish his new novel in 30 days.

Generalised Degrees of Freedom (GDF), as defined by Ye (1998 JASA 93:120-131), represent the sensitivity of model fits to perturbations of the data. As such they can be computed for any statistical model, making it possible, in principle, to derive the number of parameters in machine-learning approaches. Defined originally for normally distributed data only, we here investigate the potential of this approach for Bernoulli-data. GDF-values for models of simulated and real data are compared to model complexity-estimates from cross-validation. Similarly, we computed GDF-based AICc for randomForest, neural networks and boosted regression trees and demonstrated its similarity to cross-validation. GDF-estimates for binary data were unstable and inconsistently sensitive to the number of data points perturbed simultaneously, while at the same time being extremely computer-intensive in their calculation. Repeated 10-fold cross-validation was more robust, based on fewer assumptions and faster to compute. Our findings suggest that the GDF-approach does not readily transfer to Bernoulli data and a wider range of regression approaches.

We present a Hidden Markov Model-based algorithm for constructing timescales for paleoclimate records by annual layer counting. This objective, statistics-based approach has a number of major advantages over the current manual approach, beginning with speed. Manual layer counting of a single core (up to 3km in length) can require multiple person-years of time; the StratiCounter algorithm can count up to 100 layers/min, corresponding to a full-length timescale constructed in a few days. Moreover, the algorithm gives rigorous uncertainty estimates for the resulting timescale, which are far smaller than those produced manually. We demonstrate the utility of StratiCounter by applying it to ice-core data from two cores from Greenland and Antarctica. Performance of the algorithm is comparable to a manual approach. When using all available data, false-discovery rates and miss rates are 1-1.2% and 1.2-1.6%, respectively, for the two cores. For one core, even better agreement is found when using only the chemistry series primarily employed by human experts in the manual approach.

Ensembles of climate models are commonly used to improve climate predictions and assess the uncertainties associated with them. Weighting the models according to their performances holds the promise of further improving their predictions. Here, we use an ensemble of decadal climate predictions to demonstrate the ability of sequential learning algorithms (SLAs) to reduce the forecast errors and reduce the uncertainties. Three different SLAs are considered, and their performances are compared with those of an equally weighted ensemble, a linear regression and the climatology. Predictions of four different variables--the surface temperature, the zonal and meridional wind, and pressure--are considered. The spatial distributions of the performances are presented, and the statistical significance of the improvements achieved by the SLAs is tested. Based on the performances of the SLAs, we propose one to be highly suitable for the improvement of decadal climate predictions.