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Google Maps ditched data to figure out pandemic driving – but the best is yet to come

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Google Maps may have had 13 years practice at getting traffic patterns right, but 2020 threw a wrench in the works with pandemic driving apparently a very different matter. Google has revealed that it was forced to shake-up its precious algorithms in order to deal with COVID-19 related traffic uncertainty, including ditching the older data that would traditionally be essential for better predicting how the roads might be flowing.

Usually, Google Maps relies on masses of historical information to figure out how traffic on diferent roads will behave. “For example,” product manager Johann Lau explains, “one pattern may show that the 280 freeway in Northern California typically has vehicles traveling at a speed of 65mph between 6-7am, but only at 15-20mph in the late afternoon. We then combine this database of historical traffic patterns with live traffic conditions, using machine learning to generate predictions based on both sets of data.”

The granularity of that information is important, because what’s happening on the road now might not be the same as what you can expect later when you actually plan on driving. Google uses that localized data and combines it with AI-powered predictions of upcoming traffic from historical trends. The result, Lau says, has been higher than 97-percent trip length prediction accuracy.

That is, until the pandemic started. It’s not just a signifiant cut in road trips that affects things – though Google says it observed up to a halving in worldwide traffic back in early 2020 – but variations in when places have opened up. With some areas restricted, and others not, the old models weren’t holding.

“To account for this sudden change, we’ve recently updated our models to become more agile – automatically prioritizing historical traffic patterns from the last two to four weeks, and deprioritizing patterns from any time before that,” Lau explains.

It’s all been combined with what’s called “authoritative data” that’s sourced from local governments – and covers things like road closures, where maintenance and construction might be taking place, and where COVID-related slowdowns could be likely – and incident reports from drivers. Recent updates to Google Maps, borrowing techniques honed by Waze, made that reporting process easier while on the move.

What may prove most interesting is how all this continue to evolve over time, as platforms like Android Automotive OS become more commonplace. Launching initially in the Polestar 2 EV, Google’s software for connected cars is expected to roll out across vehicles from GM, Volvo, Audi, and others. Running Google Maps as the native navigation system, and with privileged access to metrics from the car’s underlying hardware, it’ll be a far richer pipe of traffic and road condition data that Google will be able to anonymously aggregate.

Indeed, while the aesthetic of the digital dashboard design will vary according to automaker, the underlying data fed back to Google will potentially benefit every car company using Android Automotive OS. Rather than having to rely on active user reports of icy road conditions, for example, Google might be able to identify those conditions based on feedback from the traction control and stability systems in each vehicle. That data could then be shared across all vehicles running the Android-based platform, with drivers given a preemptive warning about – or simply routed around – possibly dangerous conditions ahead.

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Realme’s Next Premium Tablet Looks To Have An Unusual Design

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Even though we still have six days before the Realme Pad X launches in China, some of the specs of the Realme Pad X have already been confirmed by Realme’s CMO Xu Qi Chase, GSMArena claims. We know that this mid-range tablet will get the Qualcomm Snapdragon 870 chipset. This also means that the Realme Pad X will become the first Realme tablet to feature 5G connectivity. While the CMO did not reveal the rest of the specs, there’s been rumors about the likelihood of the Realme Pad fetting a QHD+ display that could also support a 120 Hz refresh rate.

From the images, it is also evident that the Realme Pad X gets a single rear-facing camera that is situated on an unusually large camera bump. There is a smaller circle below the rear camera with a prominent “AI” logo. The tablet also skips an LED flash for low-light situations.

Designwise, the Realme Pad looks like a contemporary tablet with small bezels and flat sides. One of the invites also showcases the Realme Pad X being used with a stylus. It remains to be seen if this accessory will be part of the retail package or an optional extra. With the launch date for this product a week away, there is a good chance that we could have additional details about the Realme Pad X before the official launch.

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Snapdragon 8+ Gen 1 Revealed As The Heart Of Your Next Android Flagship Phone

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Qualcomm’s latest flagship processor continues to be based on a 4nm manufacturing process — albeit this time from TSMC. This change has allowed Qualcomm to increase the GPU and CPU clock speeds by up to 7%. The result is that the Prime Cortex X2 is now clocked at 3.2 GHz (as opposed to 3 GHz on the Snapdragon 8 Gen 1). Similarly, the 3x Cortex A710 core now clocks at 2.8 GHz (compared to 2.5 GHz earlier).

Then we have the 4x Cortex A-510 efficiency cores that also see a jump from 1.8 GHz to 2 GHz. While Qualcomm is yet to reveal the clock speeds for the Adreno GPU on the Snapdragon 8+ Gen1, they already claim a 10% higher clock speed in the promotional materials.

The rest of the hardware on the Snapdragon 8+ Gen 1 is similar to that of its predecessor — and this includes the X65 integrated modem as well. The new chip continues to support 3200 MHz LPDDR5 RAM, and the ISP used is the same, with support for 200 MP resolution, 8K video capture, and 64 MP burst capture. In terms of encoding, the chip retains support for Dolby Vision, HDR10+, HDR10, and HLG. A glaring omission, this time around too, is the lack of support for the AV1 codec.

In simpler terms, apart from the faster performance on account of the supposedly better manufacturing process, the Snapdragon 8+ Gen 1 does not add anything over its predecessor in terms of additional features.

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Why Black Holes Slow Down Time As You Get Closer To One

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To understand why time slows down as an object gets closer to a black hole, it is necessary to understand what time dilation is. Live Science explains that Einstein — obsessed with space and time — was the first to realize that time was relative. After more than a decade of work, Einstein published his general theory of relativity in 1915, shocking the Newtonian establishment and revolutionizing science. Einstein argued that while the laws of physics are constant throughout the universe (via The Conversation), speed or motion, space, and time are not constant but relative. Relative to what? To the point of observation or observer.

Einstein often spoke about trains and how people on and off moving trains would perceive time and speed differently. He cited, for example, that a speeding train would move much faster for a person standing on the side of the track than for a person chasing the train on another train running parallel to it. This has fueled a range of wild experiments with clocks and atomic clocks, and the answers proved Einstein was right: time is not constant and it can dilate.

But to be scientifically accurate, time does not change because of where an observer may be; it changes due to changes in gravity. Scientists have proven these changes in time by measuring atomic clocks on top of buildings and on ground levels, or on orbiting satellites and on Earth. So, if gravity can change time, what would happen to time in the presence of the massive gravitational forces of a black hole?

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