Digitizing the Environment

I’m getting really excited by all the activity buzzing around alternative energy. This was something I was pushing for as an activist in college, back in the late 80s. Way ahead of my time? You bet. Frustrated? Oh yeah.

We knew it would take more than us do-gooders, even back then. We knew there’s have to be money in it. And, of course, the world has wised up over the last 10 years, especially over the last three. For my part, I’m thrilled to report that we’re going solar at my house! We don’t have the bucks to buy a system, even though our house is very small, but between the government subsidies right now (they’re going fast!), and the ability now to lease a system for a couple decades, the up-front cost is minimal and the whole thing begins to pay for itself within 5 years. We did this with our Takagi tankless hot water heater three years ago. Yes, it cost more to buy and install, but it’s already paying dividends three years down the road. Our heating bills are remarkably lower than our neighbor, who has the same size house but a traditional “on-all-the-time” hot water heater.

I’m going to be live-blogging the install of our solar system in a couple months once it begins, but if anyone who lives in Sungevity’s service range is interested, I can hook you up with a $500 Amex card, in your pocket, just because you read! (not shilling, just using our site’s clout to pay it forward).

What I’d really like to do is start getting involved with wind, because that, by my way of thinking, is the most exciting option coming on the grid. Just today, there’s this great piece in the New York Times reporting that Google, Good Energies and a New York financial firm have each agreed to invest heavily in a proposed $5 billion transmission backbone for future offshore wind farms along the Atlantic Seaboard. The 350-mile underwater spine, which could remove some critical obstacles to wind power development, has stirred excitement among investors, government officials and environmentalists who have been briefed on it,” says the piece.

Not sure how many of you have driven through parts of California, Nevada, Arizona or other states where we’ve got lots of wind turbines spinning already, but it’s a one-of-a-kind experience. This video below does it a bit of justice, but you don’t get the true emotional impact as when you’re driving through for real. For me, it’s combination of awe (at the size and engineering feat) and excitement for the future. The clean future.

It's like when I was 13 and recording music on my Tascam 4-track on a cassette tape. After ping-ponging tracks a couple times, there was so much tape hiss, it was sort of pathetic. But we knew, one day, not so far off, digital 4 tracks would come along and clean it all up. It was just a matter of time. And so I feel today this renewed sense of optimism about the environment. It's just a matter of time... and all that activism back in college will one day pay off—is already starting to pay off.

If you're interested in the Sungevity cash-back deal, shoot me an email: david 'at'

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iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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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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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]