Collaborate Disseminate
There was movement in the “AM Radio in Every Vehicle Act” last week, with the bill advancing out of the US House of Representatives Energy and Commerce Committee and heading …read more Continue reading Hackaday Links: September 29, 2024
Ugly sweater season is rapidly approaching, at least here in the Northern Hemisphere. We’ve always been a bit baffled by the tradition of paying top dollar for a loud, obnoxious …read more Continue reading Render Yourself Invisible to AI with This Adversarial Sweater of Doom
You may have missed this month’s issue of Oriental Insects, in which a project by [Ildar Rakhmatulin] Heriot-Watt University in Edinburgh caught our attention. [Ildar] led a team of researchers …read more Continue reading Laser Zaps Cockroaches Over One Meter
Is it really cheating if the aimbot you’ve built plays the game worse than you do? We vote no, and while we take a dim view on cheating in general, …read more Continue reading Teaching a Machine to Be Worse at a Video Game Than You Are
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 …read more
It doesn’t take long after getting a cat in your life to learn who’s really in charge. Cats do pretty much what they want to do, when they want to do it, and for exactly as long as it suits them. Any correlation with your wants and needs is strictly …read more
Continue reading Keep Pesky Cats At Bay With A Machine-Learning Turret Gun
Finally, a useful application for machine vision! Forget all that self-driving nonsense and facial recognition stuff – we’ve finally got an AI that can count cards at the blackjack table.
The system that [Edje Electronics] has built, dubbed “Rain Man 2.0” in homage to the classic title character created by …read more
Continue reading Let The Cards Fall Where They May, With A Robotic Rain Main
Most people are familiar with the idea that machine learning can be used to detect things like objects or people, but for anyone who’s not clear on how that process actually works should check out [Kurokesu]’s example project for detecting pedestrians. It goes into detail on exactly what software is used, how it is configured, and how to train with a dataset.
The application uses a USB camera and the back end work is done with Darknet, which is an open source framework for neural networks. Running on that framework is the YOLO (You Only Look Once) real-time object detection …read more
Continue reading Project Shows How To Use Machine Learning to Detect Pedestrians
The engineers and product designers at [moovel lab] have created the Open Data Cam – an AI camera platform that can identify and count objects as they move through its field of view – along with an open source guide for making your own.
Step one: get out your ruler and utility knife. In this world of ubiquitous 3D-printers they’ve taken a decidedly low-tech approach to the project’s enclosure: a cut, folded, and zip-tied plastic box, with a cardboard frame inside to hold the electronic bits. It’s “splash proof” and certainly cheap to make, but we’re a little worried about …read more
They probably weren’t inspired by [Jeff Dunham’s] jalapeno on a stick, but Intel have created the Movidius neural compute stick which is in effect a neural network in a USB stick form factor. They don’t rely on the cloud, they require no fan, and you can get one for well under $100. We were interested in [Jeff Johnson’s] use of these sticks with a Pynq-Z1. He also notes that it is a great way to put neural net power on a Raspberry Pi or BeagleBone. He shows us YOLO — an image recognizer — and applies it to an HDMI …read more