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YouTube / Adobe Photoshop

The Photoshop Version 1 Demo

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YouTube / Adobe Photoshop

The very first version of Photoshop shipped in late 1988, bundled with slide scanners. The image editing tool was designed to let home computer users retouch photographs—something that had previously required serious hardware to do (whether that was massive computer hardware or a darkroom, either way was rough). This super-early version only shipped a few hundred copies bundled with scanners, and Adobe waited until February 19, 1990 to release a standalone version of the app. It ran only on the Mac, but it was amazing.

Adobe is celebrating "25 years of Photoshop" now, though I think they should have started partying with us two years ago. Anyway, technicalities.

So in the video below we have a historical gem: John Knoll, one of the two brothers who created Photoshop, gives a demo of the software. This is not an old video—he's redoing the demo he did decades ago—but it's a fascinating look at what the state of the art was in Photoshop version 1.0.7.

Some things to watch for, if you're a geek:

1. Knoll appears to be using a Macintosh Quadra 800 series computer, which was released in 1993. For comparison, the Mac models released in 1990 included the Mac Classic, IIfx, and LC. I presume the IIfx would have been the fastest available machine to run Photoshop when it was released, but for the demo's sake, something slightly more modern is close enough.

2. Knoll is using an Apple Pro Keyboard (and mouse), which is a USB model introduced in the year 2000. Some minor wizardry has been employed to connect these modern input devices to a computer from the early 1990s (that, of course, lacked USB because it hadn't been invented yet).

3. When we first see the Mac's screen, earlier versions of PhotoShop are visible in the upper left. These are pre-release versions prior to version 1.0. You can also see plenty of versions of "ImagePro," which was the name of the application before release. I wonder what those even older versions are like.

4. Notice how grainy the photo looks on the computer. Knoll notes that it's a "24-bit image on an 8-bit display," meaning that the image file has full color fidelity, but the computer hardware could only show 256 colors at once. This makes the image look like a GIF (which also is limited to 256 colors, being an old file format).

5. Check out how slow it is, and how the "wristwatch" cursor is shown instead of the ultra-modern "spinning pizza of death" seen on Mac OS X while the system is working. It's also interesting to see the black-and-white menus and dialog boxes. Those were the days.

I use Photoshop every day. It's vastly faster, smarter, and more capable—but it's clearly still the same basic application. Here's to 25 more years!

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technology
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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TIM SLOAN/AFP/Getty Images

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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