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Mac Tips: Backup (Part 2)

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Last week I covered backing up your Mac with Mozy -- a way to get your most important files backed up online for free. But because the free Mozy solution only stores up to 2 GB of data, you'll need to look elsewhere for a complete backup that covers your music, photos, and so on. You could pay a subscription for the Mozy full service, but this can get expensive over time -- and it can be very slow to upload tons of data over your home internet connection.

For Mac users, the obvious choice for full-drive backup is Time Machine, a new feature in Mac OS X Leopard. The ultimate "set it and forget it" backup, Time Machine uses an external drive (USB or Firewire) to back up your Mac's hard drive. It works in the background, waking up every hour or so to back up any newly changed files. It requires zero user intervention beyond attaching the backup drive. Setup is extremely simple: just plug in a new USB or Firewire drive to your Mac running Leopard, and you'll be asked whether you want to use that drive for Time Machine. Easy! Note: the initial backup will take some may want to make sure your Mac is set not to fall asleep during this backup, so you can be sure to have a complete backup the first time. Later backups only copy what has changed, and usually only take a few minutes. All of the backups happen in the background, so you can continue to use your Mac while the backup is in progress.

To retrieve files from Time Machine, you can enter the crazy 3D Time Machine view (pictured above), where you zoom back in time to find specific files. A timeline on the right shows backups over time, so you can easily zip to a specific date and see what was in a given folder. Personally, I've never used this feature -- it's rare that I actually lose a single file or want to go back to an old version like this. (Though Apple seems to think this is a really zippy demo, so you'll see it in lots of online reviews.) But what I do use is the whole-disk restore feature: you can boot from any Leopard install DVD, plug in a Time Machine backup drive, and use it to restore your Mac's main hard drive. This is extremely useful in case your main drive dies and is replaced with a new one, or you want to clone your drive onto a new Mac.

Apple just released Time Capsule, which is an Airport Extreme wireless router with a built-in Time Machine backup disk (either 500 GB or 1 Terabyte [!]). This further simplifies backup, since you don't even have to plug in a drive -- it's available wirelessly. Also, Time Capsule is handy if you have a lot of Macs in the house and want to back them up to a single, central place without carrying a disk around. So if you need a wireless router AND you want to do Time Machine, check out Time Capsule. But if you just want to get started with Time Machine, an external disk (USB/Firewire) will be cheaper. Generally you want your backup disk to have at least 1.5x-2x more capacity than you're using on your Mac's main drive. Thus, if you're using 60 GB on your laptop's drive, you'll want your Time Machine backup drive to be in the 90-120 GB range, at minimum.

One thing to keep in mind: if your Time Machine backup disk is in the same location as your Mac, you could lose both of them in a disaster. So if your house burns down (let's hope it doesn't), you'd likely lose both your Mac and the backup. If it's possible for you to store the backup disk in some other location (for example, at work, if you bring a laptop back and forth), you'll have a bit more security. This is also why you'll also want to use a solution like Mozy to back up your most critical files online, thus hopefully protected from any disaster that might befall your Mac. By using this two-prong backup strategy, you'll be protected against a wide variety of possible problems.

Thanks for reading about backup! Windows users, please chime in using the comments if you have suggestions for Windows backup solutions. Also if anyone has a request for a future Mac Tip, please leave a note!

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iStock // Ekaterina Minaeva
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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Scientists Think They Know How Whales Got So Big
May 24, 2017
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It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]