Sealed Packs Of Pokémon Cards Give Up Their Secrets Without Opening Them

[Ahron Wayne] succeeded in something he’s been trying to accomplish for some time: figuring out what’s inside a sealed Pokémon card packet without opening it. There’s a catch, however. It took buying an X-ray CT scanner off eBay, refurbishing and calibrating it, then putting a load of work into testing and scanning techniques. Then finally combining the data with machine learning in order to make useful decisions. It’s a load of work but [Ahron] succeeded by developing some genuinely novel techniques.

While using an X-ray machine to peek inside a sealed package seems conceptually straightforward, there are in fact all kinds of challenges in actually pulling it off.  There’s loads of noise. So much that the resulting images give a human eyeball very little to work with. Luckily, there are also some things that make the job a little easier.

For example, it’s not actually necessary to image an entire card in order to positively identify it. Teasing out the individual features such as a fist, a tentacle, or a symbol are all useful to eliminate possibilities. Interestingly, as a side effect the system can easily spot counterfeit cards; the scans show up completely different.

When we first covered [Ahron]’s fascinating journey of bringing CT scanners back to life, he was able to scan cards but made it clear he wasn’t able to scan sealed packages. We’re delighted that he ultimately succeeded, and also documented the process. Check it out in the video below.

Continue reading “Sealed Packs Of Pokémon Cards Give Up Their Secrets Without Opening Them”

Embedded Python: MicroPython Is Amazing

In case you haven’t heard, about a month ago MicroPython has celebrated its 11th birthday. I was lucky that I was able to start hacking with it soon after pyboards have shipped – the first tech talk I remember giving was about MicroPython, and that talk was how I got into the hackerspace I subsequently spent years in. Since then, MicroPython been a staple in my projects, workshops, and hacking forays.

If you’re friends with Python or you’re willing to learn, you might just enjoy it a lot too. What’s more, MicroPython is an invaluable addition to a hacker’s toolkit, and I’d like to show you why. Continue reading “Embedded Python: MicroPython Is Amazing”

PeLEDs: Using Perovskites To Create LEDs Which Also Sense Light

With both of the dominant display technologies today – LCD and OLED – being far from perfect, there is still plenty of room in the market for the Next Big Thing. One of the technologies being worked on is called PeLED, for Perovskite LED. As a semiconductor material, it can both be induced to emit photons as well as respond rather strongly to incoming photons. That is a trick that today’s displays haven’t managed without integrating additional sensors. This technology could be used to create e.g. touch screens without additional hardware, as recently demonstrated by [Chunxiong Bao] and colleagues at Linköping University in Sweden and Nanjing University in China.

Their paper in Nature Electronics describes the construction of photo-responsive metal halide perovskite pixels, covering the typical red (CsPbI3−xBrx), green (FAPbBr3), and blue (CsPbBr3−xClx) wavelengths. The article also describes the display’s photo-sensing ability to determine where a finger is placed on the display. In addition, it can work as an ambient light sensor, a scanner, and a solar cell to charge a capacitor. In related research by [Yun Gao] et al. in Nature Electronics, PeLEDs are demonstrated with 1 microsecond response time.

As usual with perovskites, their lack of stability remains their primary obstacle. In the article by [Chunxiong Bao] et al. the manufactured device with red pixels was reduced to 80% of initial brightness after 18.5 hours. While protecting the perovskites from oxygen, moisture, etc. helps, this inherent instability may prevent PeLEDs from ever becoming commercialized in display technology. Sounds like a great challenge for the next Hackaday Prize!

3D Scanning, Phone Edition

It seems to make sense. If you have a 3D printer, you might wish you could just scan some kind of part and print it — sort of like a 3D photocopier. Every time we think about this, though, we watch a few videos and are instantly disappointed by the results, especially with cheap scanners. If you go the hardware route, even cheap is relative. However, you can — in theory — put an app on your phone to do the scanning. Some of the apps are free, and some have varying costs, but, again, it seems like a lot of work for an often poor result. So we were very interested in the video from [My 3D Print Lab] where he uses his phone and quite a few different apps and objectively compares them.

Unsurprisingly, one of the most expensive packages that required a monthly or annual subscription created an excellent scan. He didn’t print from it, though, because it would not let you download any models without a fee. The subject part was an ornate chess piece, and the program seems to have captured it nicely. He removed the background and turntable he was using with no problems.

Other apps didn’t fare as well, either missing some of the parts or failing to omit background elements. You may have to do some post-processing. Some of the other expensive options have free trials or other limits, but you can at least try them for free. One of the free trials let you do three free scans, but each scan took about 8 hours to process.

Continue reading “3D Scanning, Phone Edition”

Human Brains Can Tell Deepfake Voices From Real Ones

Although it’s generally accepted that synthesized voices which mimic real people’s voices (so-called ‘deepfakes’) can be pretty convincing, what does our brain really think of these mimicry attempts? To answer this question, researchers at the University of Zurich put a number of volunteers into fMRI scanners, allowing them to observe how their brains would react to real and a synthesized voices.  The perhaps somewhat surprising finding is that the human brain shows differences in two brain regions depending on whether it’s hearing a real or fake voice, meaning that on some level we are aware of the fact that we are listening to a deepfake.

The detailed findings by [Claudia Roswandowitz] and colleagues are published in Communications Biology. For the study, 25 volunteers were asked to accept or reject the voice samples they heard as being natural or synthesized, as well as perform identity matching with the supposed speaker. The natural voices came from four male (German) speakers, whose voices were also used to train the synthesis model with. Not only did identity matching performance crater with the synthesized voices, the resulting fMRI scans showed very different brain activity depending on whether it was the natural or synthesized voice.

One of these regions was the auditory cortex, which clearly indicates that there were acoustic differences between the natural and fake voice, the other was the nucleus accumbens (NAcc). This part of the basal forebrain is involved in the cognitive processing of e.g. motivation, reward and reinforcement learning, which plays a key role in social, maternal and addictive behavior. Overall, the deepfake voices are characterized by acoustic imperfections, and do not elicit the same sense of recognition (and thus reward sensation) as natural voices do.

Until deepfake voices can be made much better, it would appear that we are still safe, for now.

Weird Old Stereo Accessories

Some people trick out their cars. Some, their computers. There are even people who max out their audio systems, although back in 1979, there was more of that going on, probably, than today where you discresionary income is split so many ways. Case in point: [Alan Cross] remembers how excited he was to get the Radio Shack catalog that year. He was working at a grocery store, saved his money, and — over time — picked up a haul ranging from an equalizer to a strobe light.

Who didn’t need a power meter or a “light organ?” These gadgets seem cheap until you realize it was 1979 and [Alan] was a student working at a grocery store. He points out that the $20 power meter is about the same as $80 today.

Continue reading “Weird Old Stereo Accessories”

FLOSS Weekly Episode 784: I’ll Buy You A Poutine

This week Jonathan Bennett and Dan Lynch talk with François Proulx about Poutine, the Open Source security scanner for build pipeline vulnerabilities. This class of vulnerability isn’t as well known as it should be, and threatens to steal secrets, or even allow for supply chain attacks in FLOSS software.

Poutine does a scan over an organization or individual repository, looking specifically for pipeline issues. It runs on both GitHub and GitLab, with more to come!

Continue reading “FLOSS Weekly Episode 784: I’ll Buy You A Poutine”