To automate livestock hygiene, researchers built an autonomous robot that uses AI, geolocation and a hybrid power system to clean organic waste from barns.
The machine was developed at Peru's Universidad Continental by Diego Cajachagua Guerreros, Rodrigo Ortiz Zacarias and Olga Huari Huamán, and won a gold medal at KIWIE 2026 in South Korea. Its technology stack is sophisticated; its assignment is extremely practical: clean the barn.
AI, geolocation and hybrid power all converge on one mission: clean the barn properly. Advanced robotics is very good at getting real work assigned to it.
If a toothbrush is going to target the gaps between teeth precisely, it first needs to see exactly where the liquid should go. CameraJet tackles that with a roughly 100,000-pixel macro camera, machine-learning-assisted gap detection and a targeted liquid jet. Dyson introduced the device in September 2026, and a live view of the mouth can be displayed through the MyDyson app.
To keep the camera's view clear, the system also uses specially designed low-foaming toothpaste. Adding imaging, recognition and liquid control to brushing turns even the toothpaste into part of the system design.
At this point, even the toothpaste feels like part of the hardware stack. Oral care is starting to look like systems engineering.
Whenever birds call outside, Fugleramme uses AI to identify them and displays only recently heard species as 19th-century illustrations on an e-paper frame. The Norway-based project runs BirdNET-Go on a Raspberry Pi 5.
Modern audio recognition works behind the scenes, while the visible result looks like an old natural-history book. Digital detections are transformed into a quiet, daily-changing bird guide for the immediate surroundings.
Modern AI is working hard in the background so the wall can show something that looks like an old bird book. That's luxuriously understated.
Palmimo DevKit is a tabletop AI robot that lets LLM tool calls map directly to physical actions such as walking, waving and turning its head. With six legs plus a neck, it has 21 degrees of freedom, along with a Raspberry Pi 5 and a round display face.
The warm wooden exterior is designed to feel approachable, and motions can be called from Python. Technically it is a physical-AI development kit; visually it can look like a small piece of furniture that decided to move around.
Inside it's a serious AI robot, but in a room it still looks surprisingly furniture-adjacent. That's a charming mismatch.
Generative image models usually suggest large GPUs, but this project asks whether one can be squeezed into an RP2350 microcontroller with just 4 MB of flash. It produces 128×128-pixel faces at roughly one image every 20 seconds.
The model and inference code fit into the tiny memory budget, and output can even be displayed directly through a VGA adapter. Instead of scaling AI upward, the project explores how far it can be compressed downward.
While everyone else adds GPUs, someone is removing things until the model fits in 4 MB. It's satisfying to see the race run backward.
AI, geolocation and hybrid power all converge on one mission: clean the barn properly. Advanced robotics is very good at getting real work assigned to it.