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Creating the Windows 95 Startup Sound

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YouTube / bvixer

When Windows 95 was being developed, executives commissioned music legend Brian Eno to develop a "piece of music" to play when the operating system started up. This music would become known as "The Windows Sound." Eno is probably most renowned* for his ambient music -- long tracks with deep sound beds and drifting melodies. But this track had to be a little shorter. Eno related the story:

The thing from the agency said, "We want a piece of music that is inspiring, universal, blah-blah, da-da-da, optimistic, futuristic, sentimental, emotional," this whole list of adjectives, and then at the bottom it said "and it must be 3.25 seconds long."

And, of course, Eno solved the problem, creating a supremely iconic sound. But when you take his micro-music and stretch it out to two and a half minutes, it becomes suspiciously like the music we hear on his ambient albums -- slow, ethereal, moody, beautiful in a very different way. So listen to it (this is a Windows 95 ad that an enterprising YouTuber slowed way down):

(You can also listen to the normal-speed version for context.)

The shortened Eno quote above isn't the full story, though. Here's the full context from an interview -- and also keep in mind that Eno composed the sound on a Mac, saying "I've never used a PC in my life; I don't like them."

The idea came up at the time when I was completely bereft of ideas. I'd been working on my own music for a while and was quite lost, actually. And I really appreciated someone coming along and saying, "Here's a specific problem — solve it."

The thing from the agency said, "We want a piece of music that is inspiring, universal, blah-blah, da-da-da, optimistic, futuristic, sentimental, emotional," this whole list of adjectives, and then at the bottom it said "and it must be 3.25 seconds long."

I thought this was so funny and an amazing thought to actually try to make a little piece of music. It's like making a tiny little jewel.

In fact, I made 84 pieces. I got completely into this world of tiny, tiny little pieces of music. I was so sensitive to microseconds at the end of this that it really broke a logjam in my own work. Then when I'd finished that and I went back to working with pieces that were like three minutes long, it seemed like oceans of time.

* = Yes, Eno is also very well known for his work as a producer with Talking Heads, U2, David Bowie, Coldplay, you name it, as well as a brief stint with Roxy Music. But in my world, his Ambient 1: Music for Airports record is the touchstone of his music career.

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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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Who Betrayed Anne Frank? A New Investigation Reopens the Case
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The tale of Anne Frank’s years spent hiding with her family in the secret annex above her father’s warehouse is known around the world. Yet despite years of research by Otto Frank (Anne's father and the only member of her family to survive the Holocaust) and scholars, we still don’t know exactly what circumstances led to Anne and her family’s discovery. A new investigation is reopening the cold case in the hopes of finally finding out the truth, The Guardian reports.

The long-accepted theory of the Franks’ discovery and subsequent arrest is that an anonymous tip to the Sicherheitsdienst, the Nazi intelligence agency, gave their hiding place away. The 30 potential suspects identified over the years have included a warehouse worker, a housekeeper, and a man possibly blackmailing Otto Frank. In December 2016, researchers at the Anne Frank House floated a new theory: The discovery was incidental, the result of a police raid looking for proof of ration fraud at Otto Frank’s factory, in which police just happened to uncover two Jewish families living in secret. However, none of these theories has been proven definitively.

Now, a team of investigators led by a former FBI agent is taking on the cold case, reviewing the archives of the Anne Frank House in Amsterdam, examining newly declassified material in the U.S. National Archives, and using data analysis to find a conclusive answer to the decades-old mystery.

“This investigation is different from all previous attempts to find the truth,” according to the Cold Case Diary website. “It will be conducted using modern law enforcement investigative techniques. The research team is multidisciplinary, using methods of cold case detectives, historians, but also psychologists, profilers, data analysts, forensic scientists and criminologists.” Thijs Bayens and Pieter Van Twisk, a Dutch filmmaker and journalist, respectively, came up with the idea for the project, and recruited the lead investigator, retired FBI agent Vince Pankoke. Pankoke has previously worked on cases involving Colombian drug cartels.

The new Anne Frank case will focus on investigative techniques that have only become available in the last decade, like big data analysis. Already, the investigators have uncovered new information, such as a German list of informants and the names of Jews that had been arrested and betrayed in Amsterdam during the war, found in the U.S. National Archives.

The investigators hope to provide answers in time for the 75th anniversary of the Frank family’s arrest in August 2019.

[h/t The Guardian]

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