The True Purpose of Solitaire, Minesweeper, and FreeCell

If you haven't ever played Solitaire, Minesweeper, Hearts or FreeCell, it's safe to say you're in the minority. These simple Windows games have probably caused more lost worker hours than anything short of a worldwide coffee shortage. Whichever one was your favorite, the temptation to take just one more go at beating them—to get a faster time or a better score—was hard to ignore.

But as fun as these games were, they weren't actually designed for entertainment. At least not in their Windows incarnations.

The oldest of the four, Microsoft Solitaire, was first added to Windows 3.0 in 1990. Although the game (sometimes called "Patience") has existed since the late 1700s, this digital version seemed to be demonstrating that in the future we would no longer require a physical deck to play simple card games. But that's not what it was doing at all. Its real aim was far more modest: it was teaching mouse-fluency by stealth.

The intention was that Solitaire would get a generation of computer users still most familiar with a command-line input to teach themselves how to drag and drop, without realizing that's what they were doing. The fact that we're still dragging and dropping today suggests that it worked rather well.

Minesweeper, too, has a similar place in technological culture. The numbers-based logic puzzle has roots in the mainframe gaming scene of the 1960s and 1970s, where a version called "Cube" by Jerimac Ratliff became incredibly popular. Decades later, in 1992, the Microsoft version Minesweeper was introduced to Windows 3.1—not to demonstrate that Windows was an adept gaming operating system, but to make the idea of left and right clicking second nature for Windows users, and to foster speed and precision in mouse movement.

If you needed any proof that this isn't a coincidence, look at another Microsoft card game: Hearts. It was introduced with 1992's Windows for Workgroups 3.1—the first network-ready version of Windows—and used Microsoft's new NetDDE technology to communicate with other Hearts clients on a local network. Again, this wasn't just a card game. It was a way to get people interested in (and hopefully impressed by) the networking capabilities of their new system.

And finally, there's FreeCell. Released for Windows 3.1 as part of the Microsoft Entertainment Pack Volume 2, FreeCell was bundled with the Win32s package that allowed 32-bit applications to run on the 16-bit Windows 3.1. Its purpose was actually to test the 32-bit thunking layer (a data processing subsystem), which had been introduced as part of Win32s. If the thunking layer was improperly installed, FreeCell wouldn't run. So what you thought was a game was actually a stealth test of software systems.

Of course, none of this explains why those games persisted once their remit was fulfilled. The answer is simple: people had too much fun with them. Any time Microsoft tried to remove the games from a release of Windows, testers went crazy. Eventually, in 2012, Microsoft released a version, Windows 8, without any of the games. Users could download the Solitaire Collection and Minesweeper separately, but you had to pay extra to play without ads.

However, with this year's release of Windows 10, Microsoft has at least brought back Solitaire. If you go looking for the others in your search bar, you'll instead be shown search results from the Windows Store where you can download the latest versions. And maybe that's intentional, because what better motivation do you need to learn how to use the Windows Store than to get your hands on your favorite games? Maybe they're still teaching by stealth, even after all these years.

This post originally appeared on our UK site.

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11-Year-Old Creates a Better Way to Test for Lead in Water
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In the wake of the water crisis in Flint, Michigan, a Colorado middle schooler has invented a better way to test lead levels in water, as The Cut reports.

Gitanjali Rao, an 11-year-old seventh grader in Lone Tree, Colorado just won the 2017 Discovery Education 3M Young Scientist Challenge, taking home $25,000 for the water-quality testing device she invented, called Tethys.

Rao was inspired to create the device after watching Flint's water crisis unfold over the last few years. In 2014, after the city of Flint cut costs by switching water sources used for its tap water and failed to treat it properly, lead levels in the city's water skyrocketed. By 2015, researchers testing the water found that 40 percent of homes in the city had elevated lead levels in their water, and recommended the state declare Flint's water unsafe for drinking or cooking. In December of that year, the city declared a state of emergency. Researchers have found that the lead-poisoned water resulted in a "horrifyingly large" impact on fetal death rates as well as leading to a Legionnaires' disease outbreak that killed 12 people.

A close-up of the Tethys device

Rao's parents are engineers, and she watched them as they tried to test the lead in their own house, experiencing firsthand how complicated it could be. She spotted news of a cutting-edge technology for detecting hazardous substances on MIT's engineering department website (which she checks regularly just to see "if there's anything new," as ABC News reports) then set to work creating Tethys. The device works with carbon nanotube sensors to detect lead levels faster than other current techniques, sending the results to a smartphone app.

As one of 10 finalists for the Young Scientist Challenge, Rao spent the summer working with a 3M scientist to refine her device, then presented the prototype to a panel of judges from 3M and schools across the country.

The contamination crisis in Flint is still ongoing, and Rao's invention could have a significant impact. In March 2017, Flint officials cautioned that it could be as long as two more years until the city's tap water will be safe enough to drink without filtering. The state of Michigan now plans to replace water pipes leading to 18,000 households by 2020. Until then, residents using water filters could use a device like Tethys to make sure the water they're drinking is safe. Rao plans to put most of the $25,000 prize money back into her project with the hopes of making the device commercially available.

[h/t The Cut]

All images by Andy King, courtesy of the Discovery Education 3M Young Scientist Challenge.

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Google's AI Can Make Its Own AI Now
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Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]