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New Chrome Update Will Improve Your Laptop’s Battery Life

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Google Chrome is a great browser, but it’s not great to your laptop’s battery. The more tabs you have open, the quicker your computer will run out of juice (although at a certain point, one more tab won’t make a difference for your already tanked battery, as a WIRED writer found out during a 2013 test). Now, Google is trying to fix the problem. The new version of Chrome dramatically reduces the percentage of CPU (central processing unit) your computer uses while running a large number of tabs in the browser. The result? Greater battery life and faster performance, according to Ars Technica UK.

Previously, you could download an extension like One Tab, which collapses all your open tabs into a list of links to reduce memory usage, but sometimes, you just need to be able to toggle between tabs while the pages are still loaded—especially if you’re working on a research project.

Chrome 57 increases how much the browser throttles background tabs, meaning it limits the amount of CPU that the tab can use. After 10 seconds of being in the background (so not the tab you’re actively looking at), Chrome limits how much processing power a tab can use to about 1 percent of each processing core, improving battery life. However, this doesn’t apply to some types of web pages, like those playing music.

As Sebastian Anthony writes for Ars Technica:

The Chromium team says it's seeing ’25 percent fewer busy background tabs’ with the new throttling mechanism in place. Anecdotally, after updating to Chrome 57 and with about 20 tabs open, my laptop feels a lot more responsive. Switching between tabs feels a little quicker, and there seems to be less input lag when typing or otherwise interacting with the browser. I haven't tested battery life yet, but it wouldn't surprise me if there's a significant improvement.

By 2020, Google plans to completely suspend background tabs from updating, rather than letting them continue running and using up CPU, a move that will likely increase battery life significantly. For now, however, Google estimates that Chrome 57 has led to 25 percent fewer busy background tabs.

You can update your browser by going to “About Google Chrome” in your taskbar.

[h/t Ars Technica UK]

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Nick Briggs/Comic Relief
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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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