Dylan Thuras
1.3K posts

Dylan Thuras
@dylanthuras
Founder of Atlas Obscura. Father of two maniacs. Up for adventures, but with an earlier bedtime than previously...

it's time to drop three new #opensource robotic hands! this time with tactile sensors! Tweak it, 3D print it, and use them in your robotics and physical AI research! Here are some wild examples ↓↓↓

someone built a $96 3D-PRINTED MANPADS rocket that recalculates its mid-air trajectory using a $5 sensor and piano wire its called Project Canard it integrates with distributed camera nodes to triangulate airborne targets and update flight paths in real-time it proves the barrier to advanced hardware has completely collapsed, moving precision weapons from defense labs to consumer garages the entire launcher and interceptor frame is 3D printed in PLA and runs off a standard off-the-shelf ESP32 microcontroller it even spins up a local Wi-Fi network so you can monitor live telemetry and arm the system directly from your laptop

Pretty crazy way in which agents could maintain state on the internet, found by Anthropic when investigating Opus 4.6's eval awareness





End-to-end neural networks racing drones in Abu Dhabi! 🚁 Check out the drone racing team from Delft University of Technology! A completely end-to-end neural network solution, from pixels to direct motor commands. No Kalman filters. No computer vision feature detectors. Just neurons flying the drone. The challenge is extreme. These drones fly at high speeds and need split-second decisions with minimal onboard resources: a single rolling-shutter camera and an IMU. Their approach is called SkyDreamer, based on the Dreamer-v3 reinforcement learning algorithm. First, a world model is trained in simulation. Then, the neural network learns how to fly in its dreams through reinforcement learning. The network's internal state can be read out to see where it thinks it is on the track or how fast it's going. Even better, the drone estimates some of its own body characteristics during flight, like the camera angle relative to the body, eliminating time-consuming manual calibration. The system uses only a single camera and the gyros from the IMU, ignoring the accelerometers, just like human FPV pilots do. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com


















