Neural networks are all the rage right now with increasing numbers of hackers, students, researchers, and businesses getting involved. The last resurgence was in the 80s and 90s, when there was little or no World Wide Web and few neural network tools. The current resurgence started around 2006. From a hacker’s perspective, what tools and other resources were available back then, what’s available now, and what should we expect for the future? For myself, a GPU on the Raspberry Pi would be nice.
Eager to get deeper into robotics after dipping my toe in the water with my BB-8 droid, I purchased a Raspberry Pi 3 Model B. The first step was to connect to it. But while it has built-in 802.11n wireless, I at first didn’t have a wireless access point, though I eventually did get one. That meant I went through different ways of finding it and connecting to it with my desktop computer. Surely there are others seeking to do the same so let’s take a look at the secret incantations used to connect a Pi to a computer directly, and indirectly.
I had great fun writing neural network software in the 90s, and I have been anxious to try creating some using TensorFlow.
Google’s machine intelligence framework is the new hotness right now. And when TensorFlow became installable on the Raspberry Pi, working with it became very easy to do. In a short time I made a neural network that counts in binary. So I thought I’d pass on what I’ve learned so far. Hopefully this makes it easier for anyone else who wants to try it, or for anyone who just wants some insight into neural networks.
Adulterated food is food that has a substance added to it to save on manufacturing costs. It can have a negative effect, it can reduce the food’s potency or it can have no effect at all. In many cases it’s done illegally. It’s also a widespread problem, one which [G. Vignesh] has decided to take on as his entry for the 2017 Hackaday Prize, an AI Based Adulteration Detector.
On his hackaday.io Project Details page he outlines some existing methods for testing food, some which you can do at home: adulterated sugar may have chalk added to it, so put it in water and the sugar will dissolve while the chalk will not. His approach is to instead take high-definition photos of the food and, on a Raspberry Pi, apply filters to them to reveal various properties such as density, size, color, texture and so on. He also mentions doing image analysis using a deep learning neural network. This project touches us all and we’ll be watching it with interest.
If all this talk of adulterated food makes you nervous about your food supply then consider growing our own, hacker style. One such project we’ve seen here on Hackaday is Farmbot, an open-source CNC farming robot. Another such is MIT’s OpenAg Food Computer, a robotic control and monitoring growing chamber.
[Slider2732] got his Orange Pi Zero working with a 3 watt amplifier, wireless keyboard (with built-in mouse), and car reversing monitor. But he needed a case to house it in. He remembered that he used to make parameters for ghost hunting by filling PC mouse cases with all sorts of electronics. So why not put the Orange Pi Zero in a mouse too? Looking through his mouse collection, he picked out an old Logitech optical mouse and went to work.
We like that the Logitech has transparent bottom halves, perfect for proving to anyone who might be skeptical that the PC really is in the mouse. A great enhancement we think would be to make the mouse actually be the mouse too! But there doesn’t seem to be enough room left for that. What’s smaller than a Pi Zero that will also run the armbian Linux distribution, OpenELEC Mediacenter, Kodi and a bunch of games?
He even set up the wireless networking for watching YouTube videos. Check out the build and demo video after the break.
One reason we really like [Rulof]’s hacks is that he combines the most unlikely things to create something unexpected. This time he makes a fast-moving loop of cotton string undulate in time to music.
To do this he uses cotton string, hard drive parts, two wheels from a toy Ferrari, two DC motors, a plastic straw, a speaker, and an amplifier. The loop of string sits in the air by being rapidly rotated in between the two wheels. The hard drive parts, driven by the amplifier, give the string a tap with an amplitude, and at a time determined by the music. The result is music made visible in the air in front of you, or in his living room in this case. Check out how he made it, and see it in action in the video below the break.
In the comments to our recent article about Wimshurst machines, we saw that some hackers had never heard of them, reminding us that we all have different backgrounds and much to share. Well here’s one I’m guessing even fewer will have heard of. It’s never even shown up in a single Hackaday article, something that was also pointed out in a comment to that Wimshurst article. It is the Lord Kelvin’s Water Dropper aka Lord Kelvin’s Thunderstorm, invented in the 1860s by William Thomson, 1st Baron Kelvin, the same fellow for whom the Kelvin temperature scale is named. It’s a device that produces a high voltage and sparks from falling drops of water.