Brilliantly insane machine learning hacks

Victor designed software that locks his computer screen at regular intervals and only unlocks it if he makes five push-ups.

Machine learning that helps you kick your workout habit

Maybe it’s a time illusion, but time just passes differently on the computer. You don’t even notice, and a minute is suddenly hours and days. But our bodies aren’t built for sitting in front of a computer. So Victor Sonck decided to do something about his work rhythm. Alarm clock reminders aren’t quite the same. Snooze, snooze, snooze… you know it yourself.

Gardening robot with a flamethrower (Ultimate Weed Killing Robot)

Dave Niewinski from Canada addressed a different problem. In his spare time, he wanted to enjoy his garden and not get rid of weeds by hand. Dave had probably never heard of Hornbach, so the only logical solution popped into his head: “I need to build a crawler robot with a flamethrower, controlled autonomously by AI, to burn the weeds.” A reasonable idea.

AI dog poop recognition

Caleb Olson is our favourite machine learning inventor. In this case, he decided to identify unwanted poop in his garden from his dog Twinkie — using a camera and an AI image detection system. But in a completely different way than you might think.

DeepLabCut was initially developed at Harvard University. It can detect the movement of multiple objects or animals at the same time. Today, it’s all on GitHub.

Computer-generated sleep podcast

Stavros Korokithakis loves falling asleep with fairy tales. So, with the help of machine learning, he created a system that generates slightly disjointed and surreal fairy tales and has a synthetic voice read them to him. The project uses OpenAI’s GPT-3 language generation to create content that sounds meaningful enough, but not enough to create a real plot. Perfect for falling asleep.

A system that uses AI image recognition to detect when an infant is hungry

And one more time Caleb Olson. This time, instead of a dog, he decided to monitor his own offspring. He’s created something like a baby monitor, but on a much more sophisticated level. Again, he used body position recognition and facial expression recognition, and this time he used the Google Media Pipe Library.



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