Samsung Galaxy A10 rumoured to be company’s first with in-display fingerprint sensor

first_imgYou may be aware by now that Samsung is going with a new strategy wherein it introduces new technologies to its mid-range Galaxy A line instead of its flagship Galaxy S line. The Galaxy A7 (2018) was the company’s first to come with a triple rear camera system, following which we had the Galaxy A9 (2018), which was the world’s first quad-camera smartphone. It now seems that the Galaxy A10 (2019) will be the company’s first smartphone to sport an in-display fingerprint sensor.This latest rumour comes via a Chinese tipster, but we urge our readers to take this leak with a fistful of salt. The tipster tweeted very simply, “Galaxy A10, UDFS” where UDFS stands for Under Display Fingerprint Sensor. Now, it is widely expected that the upcoming Galaxy S10 flagship will sport an ulltrasonic in-display fingerprint sensor, but its launch will only happen sometime in February. That leaves the whole of January clear for Samsung to bring out the Galaxy A10 (2019).It won’t be surprising considering Samsung just launched the Galaxy A8s a few days ago, which was the company’s first smartphone with an Infinity-O punch-hole display. The Galaxy A10 (2019) will likely be Samsung’s most premium mid-range phone yet, which is why it may just get a 2018 flagship Snapdragon 845 chipset. The Galaxy A8s runs on a Snapdragon 710 chipset, so it makes sense for Samsung to give the A10 a more powerful processor.These are among the first set of rumours about the Galaxy A10, so it is best to be a little skeptical for now. We still have no information about the design or other specifications of the Galaxy A10. Chances are that Samsung go with an Infinity-O display much like it did with the Galaxy A8s. We should know more about the Galaxy A10 in the days to come so do follow this space for more information.advertisementALSO READ | Samsung Galaxy A8s launched: Key specs, features, price and everything else you should knowALSO READ | Samsung Galaxy M20 may get the biggest battery in a Samsung phone yetlast_img read more

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Investment banks thought they were smart enough to predict the World Cup. They weren’t

first_imgUBS put a similar amount of wasted effort into trying to predict a winner. The Swiss multinational used results from the previous five tournaments, controlling for factors such as home nation advantage and Elo ratings (an objective measure of team strength that looks at how well a team has performed in the past) to perform a type of statistical modeling known as Monte Carlo simulation. This gave them the results of 10,000 virtual tournaments which they then analyzed to see how many times each team won. UBS ended up with Germany, Brazil, and Spain as the most likely teams to win, with Germany as the favourite. Share on LinkedIn Pinterest While these are dark days for Marcus, the pig might take some solace in the fact that he’s far from alone in being completely wrong about the World Cup. Before the tournament kicked off a number of investment banks built sophisticated computer models to try and predict the future world champions via the power of data analytics. It might seem bizarre that financial institutions are competing to be soccer soothsayers, but they do it as a kind statistical-model dick swinging; the theory being that if they are good at predicting the World Cup they should also be good at predicting the direction of the markets. Unsurprisingly, however, pretty much all of the big banks’ predictions have been embarrassingly wrong. analysis Ivan Rakitic: Croatia will have 4.5m players on pitch in World Cup final Read more Share on Messenger World Cup 2018 Poor Mystic Marcus. The supposedly-prophetic pig who predicted that England would beat Croatia on Wednesday has been vilified on social media following England’s loss, with fans calling for him to be turned into bacon. Reuse this content ING’s approach looked at market value of each team, which was calculated from individual play transfer value estimates and previous performance. The idea being that the higher the value, the higher the chance of success. They picked Spain as the winner so clearly their strategy, while novel, was not entirely bullet-proof. The bank with the most successful prediction was Nomura. The Japanese firm used portfolio theory, with analysts explaining that they looked at “the value of players in each team, the momentum of team performance and historical performance to arrive at three portfolios of teams to watch.” They picked France as the final winner of the 21st Fifa World Cup; although they predicted France would be playing Spain in the finals. Share on Facebook Share on Pinterest Pinterest Seeing how wrong big banks were about the World Cup is a sobering remindercenter_img To be fair to all the data experts who didn’t get it right, it’s extremely difficult to try and predict the World Cup. Debs Balme, the director of analytics for Merkle, a performance marketing agency (“and a super proud England fan”) told the Guardian that the accuracy of statistical modelling depends on how much data you can feed into them. “For sports like baseball or basketball where there are lots of games against the same opposition it’s an easier solution to predict, as there is more data available. Baseball players play 162 games a season, for example. And the Mets and Yankees have played each other 115 times. So there is more history of performance [than in the World Cup], and a greater wealth of data to be able to make more accurate predictions.” Some of the anomalous results of this World Cup, such as Germany being eliminated at the initial group level for the first time in 80 years, obviously make predictions more difficult.In recent years technology evangelists have been touting the power of data to predict the future and make important decisions about everything from the economy to employee performance. However, time and time again – from polls being wrong about Donald Trump to Brexit forecasting errors – we are reminded that data analytics has its limits. Seeing how wrong big banks were about the World Cup is a sobering reminder of how fallible even the most sophisticated statistical models are. Topics Share via Email Facebook Banking Share on WhatsApp Let’s start with Goldman Sachs. This year the banking behemoth continued its unsuccessful tradition of picking Brazil as the winner (it has done so for the last three World Cups). Unlike Marcus the pig, Goldman Sachs didn’t arrive at this conclusion through instinct, but through “hours of number crunching, 200,000 probability trees, and 1 million simulations”. Goldman Sachs’ artificial intelligence-powered algorithms led them to conclude that “England meets Germany in the quarters, where Germany wins; and Germany meets Brazil in the final, and Brazil prevails.” What’s more, the banks stated: “For the doubters out there, this final result was cross-checked in excruciating detail by our (German) Chief Economist Jan Hatzius!”After Belgium defeated Brazil in the quarter finals, they gave it another go, “with Brazil now out of the World Cup, Belgium is at the top of our probability table”, Goldman’s analysts wrote last week, shortly before Belgium lost to France. The bank also forecast that Belgium would be facing England in the final. (It’s actually France versus Croatia, as I’m sure you are aware.) Facebook Twitter Twitter Share on Twitter World Cup Goldman Sachs revised its prediction on 9 July to predict a Belgian win. Photograph: Goldman Sachs Unpredictable: Domagoj Vida of Croatia during a training session ahead of the World Cup finals. Photograph: Mikhail Japaridze/TASSlast_img read more

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