Art Project Analyzes Every Public Recording Of Facebook’s CEO Since 2004

[Benjamin Grosser] had a simple question: “What does Mark Zuckerberg think about?” The resulting art project is named ORDER OF MAGNITUDE and to create it he researched archives of every public utterance the founder and CEO of the world’s largest social media network has made, going as far back as 2004.

The end product is a nearly fifty-minute film consisting entirely of cuts centered around what [Benjamin] says are three of the Facebook CEO’s most favored and often-used terms:

  • The word “more”
  • The word “grow”
  • Metrics such as “ninety-nine percent”, “two million”, and terms of that nature.

The idea is that the resulting video provides insight into what Mark Zuckerberg thinks about, has focused on, and how that has (or has not) changed between 2004 and now.  How well does ORDER OF MAGNITUDE do that? Watch the video below, and judge for yourself.

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Robot Telephone Operator Handles Social Media For You

Social media has become pervasive in modern life. It can be impossible to get so much as an invite to a party without offering up your personal data at the altar of the various tech companies. [David] wanted to avoid the pressures of seeing countless photos of people climbing mountains and eating tacos, but also didn’t want to ostracize himself by avoiding social media altogether. Naturally, automation was the answer.

[David] aptly named his robot Telephone Operator, and that’s precisely what it does. Stepper motors and a servo allow the robot’s capacitive appendage to interact with the touch screen on [David]’s iPhone. A camera is fitted, and combined with OpenCV, the robot is capable of a great many important tasks.

Liking Instagram posts? Done. Reposting inane tweets? Easy. Asking your pal Mike what’s up? Yep, Telephone Operator has it covered. Given the low quality of human interaction on such platforms, it’s entirely possible [David] has the Turing Test beat without even trying. The robot even has that lazy continuous Sunday morning scroll down pat. It’s spooky stuff.

Of course, if you’re too in love with social media to trust an automaton, you might instead prefer to wear your likes on your sleeve. Video after the break.

[Thanks to dechemist for the tip!]

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2018: As The Hardware World Turns

2018 is almost over, and we have another year in the dataset: an improbable number of celebrities died in 2016. The stock market is down, and everyone thinks a crash is coming. Journalists are being killed around the world. Fidget spinners aren’t cool anymore. Fortnite. Trade wars.

But not everything is terrible: Makerbot released a new printer and oddly no one complained. It was just accepted that it was an overpriced pile of suck. Elon Musk is having a great year, press and Joe Rogan notwithstanding, by launching a record number of rockets and shipping a record number of cars, and he built a subway that we’re not calling a subway. FPGA development is getting easier with new platforms and new boards. There is a vast untapped resource in 18650 cells just sitting on sidewalks in the form of scooters, and I’m going to keep mentioning this until someone actually builds a power wall out of scooters.

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Facebook Wants To Teach Machine Learning

When you think of technical education about machine learning, Facebook might not be the company that pops into your head. However, the company uses machine learning, and they’ve rolled out a six-part video series that they say “shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems.”

The videos correspond to what they say are the six aspects of machine learning development:

  1. Problem definition
  2. Data
  3. Evaluation
  4. Features
  5. Model
  6. Experimentation

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Facebook’s Universal Music Translator

Star Trek has its universal language translator and now researchers from Facebook Artificial Intelligence Research (FAIR) has developed a universal music translator. Much of it is based on Google’s WaveNet, a version of which was also used in the recently announced Google Duplex AI.

Universal music translator architectureThe inspiration for it came from the human ability to hear music played by any instrument and to then be able to whistle or hum it, thereby translating it from one instrument to another. This is something computers have had trouble doing well, until now. The researchers fed their translator a string quartet playing Haydn and had it translate the music to a chorus and orchestra singing and playing in the style of Bach. They’ve even fed it someone whistling the theme from Indiana Jones and had it translate the tune to a symphony in the style of Mozart.

Shown here is the architecture of their network. Note that all the different music is fed into the same encoder network but each instrument which that music can be translated into has its own decoder network. It was implemented in PyTorch and trained using eight Tesla V100 GPUs over a total of six days. Efforts were made during training to ensure that the encoder extracted high-level semantic features from the music fed into it rather than just memorizing the music. More details can be found in their paper.

So if you want to hear how an electric guitar played in the style of Metallica might have been translated to the piano by Beethoven then listen to the samples in the video below.

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Hackaday Links: April 2, 2017

Toorcamp registration is open. It’s June 20-24th on Orcas Island, Washington.

Hey, you. The guy still using Mentor Graphics. Yeah, you. Siemens has acquired Mentor Graphics.

CNC knitting machines are incredibly complicated but exceptionally cool. Until now, most CNC knitting machines are actually conversions of commercial machines. Beginning with [Travis Goodspeed] and  [Fabienne Serriere] hack of a knitting machine, [Becky Stern]’s efforts, and the Knitic project, these knitting machines are really just brain transplants of old Brother knitting machines. A few of the folks from the OpenKnit project have been working to change this, and now they’re ready for production. Kniterate is a project on Kickstarter that’s a modern knitting machine, and basically a 2D woolen printer. This is an expensive machine at about $4500, but if you’ve ever seen the inside of one of these knitting machines, you’ll know building one of these things from scratch is challenging.

There was a time when a Macintosh computer could play games. Yes, I know this sounds bizarre, but you could play SimCity 2000, Diablo, and LucasArts adventure games on a machine coming out of Cupertino. [Novaspirit] wanted to relive his childhood, so he set up a Mac OS 7 emulator on a Raspberry Pi. He’s using Minivmac, beginning with an install of OS 7.1, upgrading that to 7.5.3, then upgrading that to 7.5.5. It should be noted the utility of the upgrade to 7.5.5 is questionable — the only real changes from 7.5.3  to 7.5.5 are improved virtual memory support (just change some emulator settings to get around that) and networking support (which is difficult on an emulator). If you’re going to upgrade to 7.5.5, just upgrade to 8.1 instead.

It’s getting warmer in the northern hemisphere, and you know what that means: people building swamp coolers. And you know what that means: people arguing about the thermodynamics of swamp coolers. We love these builds, so if you have a swamp cooler send it on in to the tip line.

The Prusa edition of Slic3r is out. The improvements? It’s not a single core app anymore (!), so slicing is faster. It’s got that neat variable layer slicing. Check out all the features.

It takes at least a week to delete your Facebook account. In the meantime, you can lawyer up and hit the gym. Additionally, we’re not really sure Facebook actually deletes your profile when you disable your account. Robots to the rescue. [anerdev] built a robot to delete all his content from Facebook. It’s a pair of servos with touchpad-sensitive pens. Add an Arduino, and you have a Facebook deleting machine.

Facebook Open-Sources Their Capture-the-Flag Hacking Challenges

If you want to learn how to defeat computer security, nothing beats hands-on experience. Of course, if you get your hands on someone’s system without their permission, you may end up having a very short training that ends with a jail term. And that’s where capture-the-flag (CTF) events come in.

A CTF is a system of increasingly-difficult challenges that can’t be too easy or too hard. A well-designed CTF teaches all of the participants stuff that they didn’t know, no matter how far they get and what skills they came in with. Designing a good CTF is difficult.

But since it’s also a competition, running one also involves a lot of horrible bookkeeping for the folks running it. Registering teams and providing login pages is the dirty work that you have to do in the background, that takes away time from building the systems which others are going to take apart.

Which is why it’s great that Facebook is opening up their CTF-hosting platform, along with a few starter challenges, for us all to play along. We love CTFs and related hacking challenges. If this spurs the creation of more, we’re all for it. You can find the whole setup on GitHub.

If you’re new to CTFs, here’s an awesome collection of CTF-related material on GitHub to get you started. And if your tastes run more toward hardware hacking, we’ve covered previous firmware CTFs, but frankly there’s a lot more material out there. We feel a feature post coming on…

Thanks [ag4ve] for the unintentional tip!