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Syrian Government jet (T7-SYR) anding in Abu Dhabi, UAE, for a possible meeting.
A student built a real anti-gravity machine… using an Arduino. How to Make an Acoustic Levitator: Arduino Nano + motor driver + about 60 ultrasonic transducers. They all emit ~40 kHz sound. The sound waves meet and form fixed pockets in the air. Tiny bits of styrofoam get stuck in those pockets and just hang there. If you put your hand in, the pattern breaks and they fall. Same principle labs use to move droplets or samples without touching them. Credit: u/williamlk5341 on r/arduino Based on an “Acoustic Levitator” Instructable guide: ---- Weekly robotics and AI insights. Subscribe free:
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Wtf, Arduino’s can run local LLMs like Gemma 4, Qwen on-device. - 40 TOPS of AI muscle - 16 GB RAM - Gemma 4 is already running ,Hugging Face ready.
Builds an open-source ESP32-based quadcopter from scratch with less than 2k lines of Arduino firmware.
Akashdeep Singh of The Wrench found a way to keep track of the parts he has on hand by building an @Arduino UNO Q-powered inventory management device.
Steal this idea. Allow people+agents to build custom hardware devices simply by prompting. Here's how you could make it happpen: - Index components available from partners (raspberry pi, Arduino, sensors, etc.) - Get a 3D printer or CNC machine - Expose catalogue + APIs for machines to agents, and let them use what's available to help make their human's request a reality. One prompt, order is assembled, human reviews + pays and the custom hardware comes assembled to your home in a day. It'd be so cool to have physical hardware made as easily as software, would open up so many possibilities!
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This Week in AI: 🔵 We introduced Qualcomm Intelligent Multimedia SDK 2.0, a unified toolkit for building edge AI and multimedia applications on Qualcomm Dragonwing platforms: 🔵 @arduino’s new VENTUNO Q, powered by Qualcomm #Dragonwing# IQ8, brings physical AI and on-device GenAI to developers, with the first pre-order batch selling out in under an hour: 🔵Read more to see how the same code that runs on NVIDIA and AMD GPUs can now target Qualcomm AI accelerators with the same developer experience and best-in-class performance:
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