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New Contest: Train All The Things

January 21, 2020 by 8 Comments

The old way was to write clever code that could handle every possible outcome. But what if you don’t know exactly what your inputs will look like, or just need a faster route to the final results? The answer is Machine Learning, and we want you to give it a try during the Train All the Things contest!

It’s hard to find a more buzz-worthy term than Artificial Intelligence. Right now, where the rubber hits the road in AI is Machine Learning and it’s never been so easy to get your feet wet in this realm.

From an 8-bit microcontroller to common single-board computers, you can do cool things like object recognition or color classification quite easily. Grab a beefier processor, dedicated ASIC, or lean heavily into the power of the cloud and you can do much more, like facial identification and gesture recognition. But the sky’s the limit. A big part of this contest is that we want everyone to get inspired by what you manage to pull off.

Yes, We Do Want to See Your ML “Hello World” Too!

Wait, wait, come back here. Have we already scared you off? Don’t read AI or ML and assume it’s not for you. We’ve included a category for “Artificial Intelligence Blinky” — your first attempt at doing something cool.

Need something simple to get you excited? How about Machine Learning on an ATtiny85 to sort Skittles candy by color? That uses just one color sensor for a quick and easy way to harvest data that forms a training set. But you could also climb up the ladder just a bit and make yourself a camera-based LEGO sorter or using an IMU in a magic wand to detect which spell you’re casting. Need more scientific inspiration? We’re hoping someday someone will build a training set that classifies microscope shots of micrometeorites. But we’d be equally excited with projects that tackle robot locomotion, natural language, and all the other wild ideas you can come up with.

Our guess is you don’t really need prizes to get excited about this one… most people have been itching for a reason to try out machine learning for quite some time. But we do have $100 Tindie gift certificates for the most interesting entry in each of the four contest categories: ML on the edge, ML on the gateway, AI blinky, and ML in the cloud.

Get started on your entry. The Train All The Things contest is sponsored by Digi-Key and runs until April 7th.

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Hackaday Links: December 29, 2019

December 29, 2019 by 25 Comments

The retrocomputing crowd will go to great lengths to recreate the computers of yesteryear, and no matter which species of computer is being restored, getting it just right is a badge of honor in the community. The case and keyboard obviously playing a big part in that look, so when a crowdfunding campaign to create new keycaps for the C64 was announced, Commodore fans jumped to fund it. Sadly, more than four years later, the promised keycaps haven’t been delivered. One disappointed backer, Jim Drew, decided he was sick of waiting, so he delved into the world of keycaps injection molding and started his own competing campaign. Jim details his adventures in his Kickstarter Indiegogo campaign, which makes for good reading even if you’re not into Commodore refurbishment. Here’s hoping Jim has better luck than the competition did.

Looking for anonymity in our increasingly surveilled world? You’re not alone, and in fact, we predict facial recognition spoofing products and methods will be a growth industry in the new decade. Aside from the obvious – and often illegal – approach of wearing a mask that blocks most of the features machine learning algorithms use to quantify your face, one now has another option, in the form of a colorful pattern that makes you invisible to the YOLOv2 algorithm. The pattern, which looks like a soft-focus crowd scene rendered in Mardi Gras colors, won’t make the algorithm think you’re someone else, but it will prevent you from being classified as a person. It won’t work with any other AI algorithm, but it’s still an interesting phenomenon.

We saw a great hack come this week about using an RTL-SDR to track down a water leak. Clayton’s water bill suddenly skyrocketed, and he wanted to track down the source. Luckily, his water meter uses the encoder receive-transmit (ERT) protocol on the 900 MHz ISM band to report his usage, so he threw an SDR dongle and rtlamr at the problem. After logging his data, massaging it a bit with some Python code, and graphing water consumption over time, he found that water was being used even when nobody was home. That helped him find the culprit – leaky flap valves in the toilets resulting in a slow drip that ran up the bill. There were probably other ways to attack the problem, but we like this approach just fine.

Are your flex PCBs making you cry? Friend of Hackaday Drew Fustini sent us a tip on teardrop pads to reduce the mechanical stress on traces when the board flexes. The trouble is that KiCad can’t natively create teardrop pads. Thankfully an action plugin makes teardrops a snap. Drew goes into a bit of detail on how the plugin works and shows the results of some test PCBs he made with them. It’s a nice trick to keep in mind for your flexible design work.

Lego Machine Uses Machine Learning To Sort Itself Out

December 16, 2019 by 8 Comments

In our opinion, the primary evidence of a properly lived childhood is an enormous box of every conceivable Lego piece, from simple bricks to girders and gears, all with a small town’s worth of minifigs swimming through it. It takes years of birthdays and Christmases to accumulate a Lego collection best measured by the pound, but like anything worth doing, it’s worth overdoing.

But what to do with such a collection? Digging through it to find Just the Right Piece™ can be frustrating, and bringing order to the chaos with manual sorting is just so impractical. How about putting some of those bricks to work with a machine-vision Lego sorter built from Lego?

[Daniel West]’s approach is hardly new – we’ve even featured brick-built Lego sorters before – but we’re impressed by its architecture. First, the mechanical system is amazing. It uses a series of conveyors to transport bricks from a hopper, winnowing the stream down as it goes. The final step is a vibratory feeder that places one piece on a conveyor at a time. Those pass under a camera attached to a Raspberry Pi, where OpenCV does background subtraction from the video stream, applies bounding boxes to the parts, and runs the images through a convolutional neural network (CNN) that’s been trained on a database of every Lego part. Servo-controlled gates then direct the parts into one of 18 bins. See it in action in the video below.

We must admit that we’re not sure what the sorting criteria are, as some bins seem nearly as chaotic as the input mix. Still, we appreciate the fine engineering, and award extra style points for all the Lego goodness.

Continue reading “Lego Machine Uses Machine Learning To Sort Itself Out” →

Simplified AI On Microcontrollers

November 29, 2019 by 6 Comments

Artificial intelligence is taking the world by storm. Rather than a Terminator-style apocalypse, though, it seems to be more of a useful tool for getting computers to solve problems on their own. This isn’t just for supercomputers, either. You can load AI onto some of the smallest microcontrollers as well. Tensorflow Lite is a popular tool for this, but getting it to work on your particular microcontroller can be a pain, unless you’re using an Espruino.

This project adds support for Tensorflow to this class of microcontrollers without having to fuss around with obtuse build tools. Basically adding a single line of code creates an instance, all without having to compile anything or even reboot. Tensorflow is a powerful software tool for microcontrollers, and having it this accessible now is a great leap forward.

So, what can you do with this tool? The team behind this build is using Tensorflow on an open smart watch that can be used to detect hand gestures and many other things. They also opened up these tools for use in a browser, which allows use of the AI software and emulates an Espruino without needing a physical device. There’s a lot going on with this one, and it’s a bonus that it’s open source and ready to be turned into anything you might need, like turning yourself into a Street Fighter.

How Smart Are AI Chips, Really?

November 4, 2019 by 52 Comments

The best part about the term “Artificial Intelligence” is that nobody can really tell you what it exactly means. The main reason for this stems from the term “intelligence”, with definitions ranging from the ability to practice logical reasoning to the ability to perform cognitive tasks or dream up symphonies. When it comes to human intelligence, properties such as self-awareness, complex cognitive feats, and the ability to plan and motivate oneself are generally considered to be defining features. But frankly, what is and isn’t “intelligence” is open to debate.

What isn’t open to debate is that AI is a marketing goldmine. The vagueness has allowed for marketing departments around the world to go all AI-happy, declaring that their product is AI-enabled and insisting that their speech assistant responds ‘intelligently’ to one’s queries. One might begin to believe that we’re on the cusp of a fantastic future inhabited by androids and strong AIs attending to our every whim.

In this article we’ll be looking at the reality behind these claims and ponder humanity’s progress towards becoming a Type I civilization. But this is Hackaday, so we’re also going to dig into the guts of some AI chips, including the Kendryte K210 and see how the hardware of today fits into our Glorious Future. Continue reading “How Smart Are AI Chips, Really?” →

A Tamagotchi For WiFi Cracking

October 16, 2019 by 8 Comments

OK, let’s start this one by saying that it’s useful to know how to break security measures in order to understand how to better defend yourself, and that you shouldn’t break into any network you don’t have access to. That being said, if you want to learn about security and the weaknesses within the WPA standard, there’s no better way to do it than with a tool that mimics the behavior of a Tamagotchi.

Called the pwnagotchi, this package of artificial intelligence looks for information in local WiFi packets that can be used to crack WPA encryption. It’s able to modify itself in order to maximize the amount of useful information it’s able to obtain from whatever environment you happen to place it in. As an interesting design choice, the pwnagotchi behaves like an old Tamagotchi pet would, acting happy when it gets the inputs it needs.

This project is beyond a novelty though and goes deep in the weeds of network security. If you’re at all interested in the ways in which your own networks might be at risk, this might be a tool you can use to learn a little more about the ways of encryption, general security, and AI to boot. Of course, if you’re new to the network security world, make sure the networks you’re using are secured at least a little bit first.

Thanks to [Itay] for the tip!

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Hackaday Links: October 13, 2019

October 13, 2019 by 20 Comments

Trouble in the Golden State this week, as parts of California were subjected to planned blackouts. Intended to prevent a repeat of last year’s deadly wildfires, which were tied in part to defective electrical distribution equipment, the blackouts could plunge millions in the counties surrounding Sacramento into the dark for days. Schools have canceled classes, the few stores that are open are taking cash only, and hospitals are running on generators. It seems a drastic move for PG&E, the utility that promptly went into bankruptcy after being blamed for last year’s fires, but it has the support of the governor, so the plan is likely to continue as long as the winds do. One group is not likely to complain, though;  California amateur radio operators must be enjoying a greatly decreased noise floor in the blackout areas, thanks to the loss of millions of switch-mode power supplies and their RF noise.

Good news, bad news for Fusion 360 users. Autodesk, the company behind the popular and remarkably capable CAD/CAM/CAE package, has announced changes to its licensing scheme, which went into effect this week. Users no longer have to pay for the “Ultimate” license tier to get goodies like 5-axis machining and generative design tools, as all capabilities are now included in the single paid version of Fusion 360. That’s good because plenty of users were unwilling to bump their $310 annual “Standard” license fee up to $1535 to get those features, but it’s bad because now the annual rate goes to $495. In a nice nod to the current userbase, those currently on the Standard license, as well as early adopters, will get to keep the $310 annual rate as long as they renew, and The $495 pricing tier went into effect in November of 2018, while anyone still on the $310 annual price was grandfathered in (and will remain to be). At that time there was still a $1535 tier called Ultimate, whose price will now be going away but the features remain in the $495 tier which is now the only pricing option for Fusion 360. Ultimate users will see a $1040 price drop. As for the current base of freeloaders like yours truly, fear not: Fusion 360 is still free for personal, non-commercial use. No generative design or tech support for us, though. (Editor’s Note: This paragraph was updated on 10/14/2019 to clarify the tier changes after Autodesk reached out to Hackaday via email.)

You might have had a bad day at the bench, but was it as bad as Román’s? He tipped us off to his nightmare of running into defective Wemos D1 boards – a lot of them. The 50 boards were to satisfy an order of data loggers for a customer, but all the boards seemed caught in an endless reboot loop when plugged into a USB port for programming. He changed PCs, changed cables, but nothing worked to stop the cycle except for one thing: touching the metal case of the module. His write up goes through all the dead-ends he went down to fix the problem, which ended up being a capacitor between the antenna and ground. Was it supposed to be there? Who knows, because once that cap was removed, the boards worked fine. Hats off to Román for troubleshooting this and sharing the results with us.

Ever since giving up their “Don’t be evil” schtick, Google seems to have really embraced the alternative. Now they’re in trouble for targeting the homeless in their quest for facial recognition data. The “volunteer research studies” consisted of playing what Google contractors were trained to describe as a “mini-game” on a modified smartphone, which captured video of the player’s face. Participants were compensated with $5 Starbucks gift cards but were not told that video was being captured, and if asked, contractors were allegedly trained to lie about that. Contractors were also allegedly trained to seek out people with dark skin, ostensibly to improve facial recognition algorithms that notoriously have a hard time with darker complexions. To be fair, the homeless were not exclusively targeted; college students were also given gift cards in exchange for their facial data.

For most of us, 3D-printing is a hobby, or at least in service of other hobbies. Few of us make a living at it, but professionals who do are often a great source of tips and tricks. One such pro is industrial designer Eric Strebel, who recently posted a video of his 3D-printing pro-tips. A lot of it is concerned with post-processing prints, like using a cake decorator’s spatula to pry prints off the bed, or the use of card scrapers and dental chisels to clean up prints. But the money tip from this video is the rolling cart he made for his Ultimaker. With the printer on top and storage below, it’s a great way to free up some bench space.

And finally, have you ever wondered how we hackers will rebuild society once the apocalypse hits and mutant zombie biker gangs roam the Earth? If so, then you need to check out Collapse OS, the operating system for an uncertain future. Designed to be as self-contained as possible, Collapse OS is intended to run on “field expedient” computers, cobbled together from whatever e-waste can be scrounged, as long as it includes a Z80 microprocessor. The OS has been tested on an RC2014 and a Sega Master System so far, but keep an eye out for TRS-80s, Kaypros, and the odd TI-84 graphing calculator as you pick through the remains of civilization.