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7 Fast Facts About AIM to Make You LOL

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David Silverman/Getty Images

AIM, the chat service that ruled the '90s and the early 2000s, is dead. AOL’s parent company Oath has announced that it would be retiring the service (which, to be honest, we didn’t realize was still kicking), sending that yellow running man off into the sunset on December 15, 2017. In fond remembrance of the pre-social-media days when the beeps and door-shutting sound effects of AIM were the soundtrack to procrastination everywhere, here are seven facts about the pioneering chat service:

1. IT STARTED OFF AS AN OFF-THE-BOOKS COMPANY PROJECT …

IM-ing had long been a part of AOL’s functionality, but in 1996, a very small group of AOL employees began working on the idea of a free (remember when you paid for AOL?) standalone messaging service. They didn’t pitch the idea to AOL’s executives, and worked on the project unofficially using servers that someone at the company’s data centers had “lost,” as the engineers who started the project told Mashable in 2014. Once it was added to AOL’s public servers, AIM was an instant success, despite the fact that you had to download it directly from a server address—there wasn’t even a webpage for it. By 1999, it had 40 million users and was the “de facto standard for instant messaging over the Internet,” according to The New York Times. In 2003, it was handling about 2 billion messages a day.

2. … AND SOME OF ITS MOST ICONIC FEATURES WERE LAUNCHED WITHOUT COMPANY APPROVAL.

The engineers who had created AIM as an under-the-radar project were also quick to update it without permission from up the chain. This process led to some of the system’s most iconic features, including the buddy icon. Despite the massive successes of the software, the corporate overlords at AOL never quite got behind it, in part because they couldn’t come up with a way to monetize it that fit with the rest of the AOL subscription service.

3. IT CHANGED THE WAY PEOPLE TALKED ONLINE.

AOL offered its users a built-in selection of 16 smiley faces in the late '90s, according to CNN. And then there were the LOLs. In a story on AIM and teens in 2003, The New York Times wrote, “In fact, instant messaging has become an unofficial dialect, and devising misspelled versions of words lacking as many vowels as possible has become a literary form.”

4. IT WAS DESIGNED TO LET PEOPLE CHAT AT WORK, WHETHER THEIR BOSSES LIKED IT OR NOT.

According to Mashable’s 2014 history on the subject, programmers working on AIM “made the program the bane of IT departments.” The engineers were focused on consumers, not their irate bosses, and created features in the software that allowed it to circumvent network blocks, allowing users to ROFL about their bosses unimpeded.

5. IT WAS AT THE CENTER OF A TECH FEUD.

In the late 1990s, AOL fought hard to keep competitors from getting in on the instant-messenger game, and refused to make its software open to outside developers. Both Microsoft and Yahoo tried to create software that would allow their users to see and communicate with AIM users—like how you can send an email to someone even if you’ve got an Outlook account and they use Gmail. AOL was not happy, and blocked the software immediately. Microsoft responded by tweaking MSN Messenger to get past AOL’s block. AOL blocked it again. According to AIM creator Eric Bosco, the two companies went through the same dance 21 different times before Microsoft gave up. For what it’s worth: MSN Messenger shut down in 2014.

6. IT COULD HAVE BEEN THE NEXT NAPSTER.

Another intriguing tidbit from Mashable’s interviews with AIM’s creators: AOL engineers tried to give the chat software capabilities similar to the infamous file-sharing service Napster. They called the project “Aimster” internally, creating functions where users could search their friends’ files and transfer them to their own computers. It never made it out of the development phase. (There was, actually, a file-sharing service called Aimster founded in 2000, but AOL sued the company for copyright infringement, forcing it to become Madster.)

7. IT INFLUENCED GCHAT IMMENSELY.

Unsurprisingly, AOL’s pioneering chat service made a huge mark on the instant messaging of today. Justin Uberti, a lead software architect for Google messaging apps, had also played a large role in AIM. “You can definitely see the influence of the early work that Justin did,” Bosco told Digital Trends in 2016. “You can see a lot of that taking shape in some of the Google offerings.”

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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]

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These LED Crosswalks Adapt to Whoever Is Crossing
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Courtesy Umbrellium

Crosswalks are an often-neglected part of urban design; they’re usually just white stripes on dark asphalt. But recently, they’re getting more exciting—and safer—makeovers. In the Netherlands, there is a glow-in-the-dark crosswalk. In western India, there is a 3D crosswalk. And now, in London, there’s an interactive LED crosswalk that changes its configuration based on the situation, as Fast Company reports.

Created by the London-based design studio Umbrellium, the Starling Crossing (short for the much more tongue-twisting STigmergic Adaptive Responsive LearnING Crossing) changes its layout, size, configuration, and other design factors based on who’s waiting to cross and where they’re going.

“The Starling Crossing is a pedestrian crossing, built on today’s technology, that puts people first, enabling them to cross safely the way they want to cross, rather than one that tells them they can only cross in one place or a fixed way,” the company writes. That means that the system—which relies on cameras and artificial intelligence to monitor both pedestrian and vehicle traffic—adapts based on road conditions and where it thinks a pedestrian is going to go.

Starling Crossing - overview from Umbrellium on Vimeo.

If a bike is coming down the street, for example, it will project a place for the cyclist to wait for the light in the crosswalk. If the person is veering left like they’re going to cross diagonally, it will move the light-up crosswalk that way. During rush hour, when there are more pedestrians trying to get across the street, it will widen to accommodate them. It can also detect wet or dark conditions, making the crosswalk path wider to give pedestrians more of a buffer zone. Though the neural network can calculate people’s trajectories and velocity, it can also trigger a pattern of warning lights to alert people that they’re about to walk right into an oncoming bike or other unexpected hazard.

All this is to say that the system adapts to the reality of the road and traffic patterns, rather than forcing pedestrians to stay within the confines of a crosswalk system that was designed for car traffic.

The prototype is currently installed on a TV studio set in London, not a real road, and it still has plenty of safety testing to go through before it will appear on a road near you. But hopefully this is the kind of road infrastructure we’ll soon be able to see out in the real world.

[h/t Fast Company]

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